list.of.packages <- c("gdata","R.utils","FactoMineR","factoextra","data.table","stringr","sp","cluster","plyr",
"stringi","proj4","ggplot2","plotly","rgdal","rgeos","raster","randomForest")
new.packages <- list.of.packages[!(list.of.packages %in% installed.packages()[,"Package"])]
if(length(new.packages) > 0) install.packages(new.packages)
lapply(list.of.packages, FUN = function(X) {
do.call("require", list(X))
})
Loading required package: gdata gdata: read.xls support for 'XLS' (Excel 97-2004) files ENABLED. gdata: read.xls support for 'XLSX' (Excel 2007+) files ENABLED. Attaching package: ‘gdata’ The following object is masked from ‘package:stats’: nobs The following object is masked from ‘package:utils’: object.size The following object is masked from ‘package:base’: startsWith Loading required package: R.utils Loading required package: R.oo Loading required package: R.methodsS3 R.methodsS3 v1.8.1 (2020-08-26 16:20:06 UTC) successfully loaded. See ?R.methodsS3 for help. R.oo v1.24.0 (2020-08-26 16:11:58 UTC) successfully loaded. See ?R.oo for help. Attaching package: ‘R.oo’ The following object is masked from ‘package:R.methodsS3’: throw The following objects are masked from ‘package:gdata’: ll, trim The following objects are masked from ‘package:methods’: getClasses, getMethods The following objects are masked from ‘package:base’: attach, detach, load, save R.utils v2.10.1 (2020-08-26 22:50:31 UTC) successfully loaded. See ?R.utils for help. Attaching package: ‘R.utils’ The following objects are masked from ‘package:gdata’: env, resample The following object is masked from ‘package:utils’: timestamp The following objects are masked from ‘package:base’: cat, commandArgs, getOption, inherits, isOpen, nullfile, parse, warnings Loading required package: FactoMineR Loading required package: factoextra Loading required package: ggplot2 Welcome! Want to learn more? See two factoextra-related books at https://goo.gl/ve3WBa Loading required package: data.table Attaching package: ‘data.table’ The following objects are masked from ‘package:gdata’: first, last Loading required package: stringr Loading required package: sp Loading required package: cluster Loading required package: plyr Loading required package: stringi Loading required package: proj4 Loading required package: plotly Attaching package: ‘plotly’ The following objects are masked from ‘package:plyr’: arrange, mutate, rename, summarise The following object is masked from ‘package:ggplot2’: last_plot The following object is masked from ‘package:stats’: filter The following object is masked from ‘package:graphics’: layout Loading required package: rgdal rgdal: version: 1.5-23, (SVN revision 1121) Geospatial Data Abstraction Library extensions to R successfully loaded Loaded GDAL runtime: GDAL 2.2.3, released 2017/11/20 Path to GDAL shared files: /usr/share/gdal/2.2 GDAL binary built with GEOS: TRUE Loaded PROJ runtime: Rel. 4.9.3, 15 August 2016, [PJ_VERSION: 493] Path to PROJ shared files: (autodetected) Linking to sp version:1.4-5 Attaching package: ‘rgdal’ The following object is masked from ‘package:proj4’: project The following object is masked from ‘package:R.oo’: getDescription Loading required package: rgeos rgeos version: 0.5-5, (SVN revision 640) GEOS runtime version: 3.6.2-CAPI-1.10.2 Linking to sp version: 1.4-5 Polygon checking: TRUE Loading required package: raster Attaching package: ‘raster’ The following object is masked from ‘package:plotly’: select The following object is masked from ‘package:data.table’: shift The following objects are masked from ‘package:R.utils’: extract, resample The following objects are masked from ‘package:R.oo’: extend, trim The following objects are masked from ‘package:gdata’: resample, trim Loading required package: randomForest randomForest 4.6-14 Type rfNews() to see new features/changes/bug fixes. Attaching package: ‘randomForest’ The following object is masked from ‘package:ggplot2’: margin The following object is masked from ‘package:gdata’: combine
In this excercise, we will emulate some of the analyses described in the "Data mining the past" vignette. This will compare the concepts that have been mapped to the Jardabok dataARC observations with those in the Saga Maps.
As part of this exercise, we'll have to import csv files. The default directory to which files will be downloaded is the current working directory. If you'd like to specify a different folder, change "getwd()" to the filepath with frontslashes between quotes. (e.g. "I:/DataArc/"). We'll also define the projection we want to use. Here, we'll use the EPSG:9040 conformal conic employed by Iceland, defined according to the WGS1984 spheroid. The init file for proj4 included in this binder release does not have access to the complete list of EPSG codes, and as such the simple EPSG import has been commented out in this script. Users may employ that line if they are running the notebook or associated scripts locally. The projections, however, are identical.
path <- getwd()
setwd(path)
set.seed(1601720)
#proj <- CRS("+init=epsg:9040 +datum=WGS84")
proj <- CRS("+proj=lcc +lat_0=52 +lon_0=10 +lat_1=35 +lat_2=65 +x_0=4000000 +y_0=2800000
+datum=WGS84 +units=m +no_defs")
Next, we'll import the dataARC dataset either using the Provided_Results.gz compressed CSV from all dataARC observations in Iceland as of March 3, 2021, or the arc.dataconvert function for user-obtained output jsons from the dataARC API. This will convert the dataARC API output into a parsable data.table. We'll then convert it to a data.table object, and use the trimws function to remove any whitespace before column entries. This will make the columns parsable when we compare hashes.
if (file.exists("Provided_Results.gz")) {
arc <- fread("Provided_Results.gz", encoding="UTF-8")
} else {
source("Translator.R")
arc <- arc.dataconvert("results.json.gz")
}
setnames(arc,names(arc),c("NUMBER","ID","X","Y","DATASET","CATEGORY",
"ENTRY","CONCEPT","COMBINATOR","RELATED","CONTEXT"))
arc[, names(arc) := lapply(.SD,trimws,which='left')]
head(arc)
NUMBER | ID | X | Y | DATASET | CATEGORY | ENTRY | CONCEPT | COMBINATOR | RELATED | CONTEXT |
---|---|---|---|---|---|---|---|---|---|---|
<chr> | <chr> | <chr> | <chr> | <chr> | <chr> | <chr> | <chr> | <chr> | <chr> | <chr> |
463198 | 5FD9474424B939001C692303 | 64.1 | -22 | 5F41CAE4B2E723864080817C | ID | 38282 | 5F430A73836C1E48136B4F66:5F430A73836C1E48136B4F67:5F430A73836C1E48136B4F68:5F430A73836C1E48136B4F69:5F430A74836C1E48136B4F6E:5F430A74836C1E48136B4F76:5F430A74836C1E48136B4F7A:5F430A74836C1E48136B4F7E:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F98:5F430A74836C1E48136B4F9E:5F430A74836C1E48136B4F9F:5F430A75836C1E48136B4FA3:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FB4:5F430A75836C1E48136B4FBD:5F430A75836C1E48136B4FC5:5F430A75836C1E48136B4FC6:5F430A75836C1E48136B4FC7:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD4:5F430A76836C1E48136B4FDA:5F430A76836C1E48136B4FE4:5F430A76836C1E48136B4FEB:5F430A76836C1E48136B4FF0:5F430A76836C1E48136B4FF2:5F430A76836C1E48136B4FF5:5F430A77836C1E48136B4FFF:5F430A77836C1E48136B5001:5F430A77836C1E48136B5002:5F430A77836C1E48136B5009:5F430A77836C1E48136B5012:5F430A77836C1E48136B5018:5F430A77836C1E48136B5023:5F430A77836C1E48136B5025:5F430A78836C1E48136B5044:5F430A78836C1E48136B5057:5F430A78836C1E48136B505C:5F430A78836C1E48136B5068 | 5F41CADEB2E7238640808014:5F41CADEB2E7238640808016:5F41CADEB2E7238640808017:5F41CADDB2E723864080800B:5F41CADEB2E7238640808013:5F41CADEB2E723864080801A:5F41CADEB2E723864080801F:5F41CADEB2E7238640808020:5F41CADEB2E7238640808018:5F41CADEB2E7238640808019:5F41CADEB2E723864080800E:5F41CADEB2E7238640808012:5F41CADEB2E723864080801C:5F41CADEB2E723864080800F:5F41CADEB2E7238640808010:5F41CADEB2E7238640808023:5F41CADDB2E7238640808008:5F41CADEB2E723864080801B:5F41CADEB2E7238640808022 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
463199 | 5FD9474424B939001C692303 | 64.1 | -22 | 5F41CAE4B2E723864080817C | COUNTRY | Iceland | 5F430A73836C1E48136B4F66:5F430A73836C1E48136B4F67:5F430A73836C1E48136B4F68:5F430A73836C1E48136B4F69:5F430A74836C1E48136B4F6E:5F430A74836C1E48136B4F76:5F430A74836C1E48136B4F7A:5F430A74836C1E48136B4F7E:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F98:5F430A74836C1E48136B4F9E:5F430A74836C1E48136B4F9F:5F430A75836C1E48136B4FA3:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FB4:5F430A75836C1E48136B4FBD:5F430A75836C1E48136B4FC5:5F430A75836C1E48136B4FC6:5F430A75836C1E48136B4FC7:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD4:5F430A76836C1E48136B4FDA:5F430A76836C1E48136B4FE4:5F430A76836C1E48136B4FEB:5F430A76836C1E48136B4FF0:5F430A76836C1E48136B4FF2:5F430A76836C1E48136B4FF5:5F430A77836C1E48136B4FFF:5F430A77836C1E48136B5001:5F430A77836C1E48136B5002:5F430A77836C1E48136B5009:5F430A77836C1E48136B5012:5F430A77836C1E48136B5018:5F430A77836C1E48136B5023:5F430A77836C1E48136B5025:5F430A78836C1E48136B5044:5F430A78836C1E48136B5057:5F430A78836C1E48136B505C:5F430A78836C1E48136B5068 | 5F41CADEB2E7238640808014:5F41CADEB2E7238640808016:5F41CADEB2E7238640808017:5F41CADDB2E723864080800B:5F41CADEB2E7238640808013:5F41CADEB2E723864080801A:5F41CADEB2E723864080801F:5F41CADEB2E7238640808020:5F41CADEB2E7238640808018:5F41CADEB2E7238640808019:5F41CADEB2E723864080800E:5F41CADEB2E7238640808012:5F41CADEB2E723864080801C:5F41CADEB2E723864080800F:5F41CADEB2E7238640808010:5F41CADEB2E7238640808023:5F41CADDB2E7238640808008:5F41CADEB2E723864080801B:5F41CADEB2E7238640808022 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
463200 | 5FD9474424B939001C692303 | 64.1 | -22 | 5F41CAE4B2E723864080817C | SAMPLEDATA_SITE_ID | 2142 | 5F430A73836C1E48136B4F66:5F430A73836C1E48136B4F67:5F430A73836C1E48136B4F68:5F430A73836C1E48136B4F69:5F430A74836C1E48136B4F6E:5F430A74836C1E48136B4F76:5F430A74836C1E48136B4F7A:5F430A74836C1E48136B4F7E:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F98:5F430A74836C1E48136B4F9E:5F430A74836C1E48136B4F9F:5F430A75836C1E48136B4FA3:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FB4:5F430A75836C1E48136B4FBD:5F430A75836C1E48136B4FC5:5F430A75836C1E48136B4FC6:5F430A75836C1E48136B4FC7:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD4:5F430A76836C1E48136B4FDA:5F430A76836C1E48136B4FE4:5F430A76836C1E48136B4FEB:5F430A76836C1E48136B4FF0:5F430A76836C1E48136B4FF2:5F430A76836C1E48136B4FF5:5F430A77836C1E48136B4FFF:5F430A77836C1E48136B5001:5F430A77836C1E48136B5002:5F430A77836C1E48136B5009:5F430A77836C1E48136B5012:5F430A77836C1E48136B5018:5F430A77836C1E48136B5023:5F430A77836C1E48136B5025:5F430A78836C1E48136B5044:5F430A78836C1E48136B5057:5F430A78836C1E48136B505C:5F430A78836C1E48136B5068 | 5F41CADEB2E7238640808014:5F41CADEB2E7238640808016:5F41CADEB2E7238640808017:5F41CADDB2E723864080800B:5F41CADEB2E7238640808013:5F41CADEB2E723864080801A:5F41CADEB2E723864080801F:5F41CADEB2E7238640808020:5F41CADEB2E7238640808018:5F41CADEB2E7238640808019:5F41CADEB2E723864080800E:5F41CADEB2E7238640808012:5F41CADEB2E723864080801C:5F41CADEB2E723864080800F:5F41CADEB2E7238640808010:5F41CADEB2E7238640808023:5F41CADDB2E7238640808008:5F41CADEB2E723864080801B:5F41CADEB2E7238640808022 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
463201 | 5FD9474424B939001C692303 | 64.1 | -22 | 5F41CAE4B2E723864080817C | SAMPLEDATA_SITE_NAME | Bessastadir | 5F430A73836C1E48136B4F66:5F430A73836C1E48136B4F67:5F430A73836C1E48136B4F68:5F430A73836C1E48136B4F69:5F430A74836C1E48136B4F6E:5F430A74836C1E48136B4F76:5F430A74836C1E48136B4F7A:5F430A74836C1E48136B4F7E:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F98:5F430A74836C1E48136B4F9E:5F430A74836C1E48136B4F9F:5F430A75836C1E48136B4FA3:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FB4:5F430A75836C1E48136B4FBD:5F430A75836C1E48136B4FC5:5F430A75836C1E48136B4FC6:5F430A75836C1E48136B4FC7:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD4:5F430A76836C1E48136B4FDA:5F430A76836C1E48136B4FE4:5F430A76836C1E48136B4FEB:5F430A76836C1E48136B4FF0:5F430A76836C1E48136B4FF2:5F430A76836C1E48136B4FF5:5F430A77836C1E48136B4FFF:5F430A77836C1E48136B5001:5F430A77836C1E48136B5002:5F430A77836C1E48136B5009:5F430A77836C1E48136B5012:5F430A77836C1E48136B5018:5F430A77836C1E48136B5023:5F430A77836C1E48136B5025:5F430A78836C1E48136B5044:5F430A78836C1E48136B5057:5F430A78836C1E48136B505C:5F430A78836C1E48136B5068 | 5F41CADEB2E7238640808014:5F41CADEB2E7238640808016:5F41CADEB2E7238640808017:5F41CADDB2E723864080800B:5F41CADEB2E7238640808013:5F41CADEB2E723864080801A:5F41CADEB2E723864080801F:5F41CADEB2E7238640808020:5F41CADEB2E7238640808018:5F41CADEB2E7238640808019:5F41CADEB2E723864080800E:5F41CADEB2E7238640808012:5F41CADEB2E723864080801C:5F41CADEB2E723864080800F:5F41CADEB2E7238640808010:5F41CADEB2E7238640808023:5F41CADDB2E7238640808008:5F41CADEB2E723864080801B:5F41CADEB2E7238640808022 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
463202 | 5FD9474424B939001C692303 | 64.1 | -22 | 5F41CAE4B2E723864080817C | SAMPLEDATA_SAMPLE_NAME | S10 | 5F430A73836C1E48136B4F66:5F430A73836C1E48136B4F67:5F430A73836C1E48136B4F68:5F430A73836C1E48136B4F69:5F430A74836C1E48136B4F6E:5F430A74836C1E48136B4F76:5F430A74836C1E48136B4F7A:5F430A74836C1E48136B4F7E:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F98:5F430A74836C1E48136B4F9E:5F430A74836C1E48136B4F9F:5F430A75836C1E48136B4FA3:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FB4:5F430A75836C1E48136B4FBD:5F430A75836C1E48136B4FC5:5F430A75836C1E48136B4FC6:5F430A75836C1E48136B4FC7:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD4:5F430A76836C1E48136B4FDA:5F430A76836C1E48136B4FE4:5F430A76836C1E48136B4FEB:5F430A76836C1E48136B4FF0:5F430A76836C1E48136B4FF2:5F430A76836C1E48136B4FF5:5F430A77836C1E48136B4FFF:5F430A77836C1E48136B5001:5F430A77836C1E48136B5002:5F430A77836C1E48136B5009:5F430A77836C1E48136B5012:5F430A77836C1E48136B5018:5F430A77836C1E48136B5023:5F430A77836C1E48136B5025:5F430A78836C1E48136B5044:5F430A78836C1E48136B5057:5F430A78836C1E48136B505C:5F430A78836C1E48136B5068 | 5F41CADEB2E7238640808014:5F41CADEB2E7238640808016:5F41CADEB2E7238640808017:5F41CADDB2E723864080800B:5F41CADEB2E7238640808013:5F41CADEB2E723864080801A:5F41CADEB2E723864080801F:5F41CADEB2E7238640808020:5F41CADEB2E7238640808018:5F41CADEB2E7238640808019:5F41CADEB2E723864080800E:5F41CADEB2E7238640808012:5F41CADEB2E723864080801C:5F41CADEB2E723864080800F:5F41CADEB2E7238640808010:5F41CADEB2E7238640808023:5F41CADDB2E7238640808008:5F41CADEB2E723864080801B:5F41CADEB2E7238640808022 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
463203 | 5FD9474424B939001C692303 | 64.1 | -22 | 5F41CAE4B2E723864080817C | SAMPLEDATA_SAMPLE_GROUP_ID | 6940 | 5F430A73836C1E48136B4F66:5F430A73836C1E48136B4F67:5F430A73836C1E48136B4F68:5F430A73836C1E48136B4F69:5F430A74836C1E48136B4F6E:5F430A74836C1E48136B4F76:5F430A74836C1E48136B4F7A:5F430A74836C1E48136B4F7E:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F98:5F430A74836C1E48136B4F9E:5F430A74836C1E48136B4F9F:5F430A75836C1E48136B4FA3:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FB4:5F430A75836C1E48136B4FBD:5F430A75836C1E48136B4FC5:5F430A75836C1E48136B4FC6:5F430A75836C1E48136B4FC7:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD4:5F430A76836C1E48136B4FDA:5F430A76836C1E48136B4FE4:5F430A76836C1E48136B4FEB:5F430A76836C1E48136B4FF0:5F430A76836C1E48136B4FF2:5F430A76836C1E48136B4FF5:5F430A77836C1E48136B4FFF:5F430A77836C1E48136B5001:5F430A77836C1E48136B5002:5F430A77836C1E48136B5009:5F430A77836C1E48136B5012:5F430A77836C1E48136B5018:5F430A77836C1E48136B5023:5F430A77836C1E48136B5025:5F430A78836C1E48136B5044:5F430A78836C1E48136B5057:5F430A78836C1E48136B505C:5F430A78836C1E48136B5068 | 5F41CADEB2E7238640808014:5F41CADEB2E7238640808016:5F41CADEB2E7238640808017:5F41CADDB2E723864080800B:5F41CADEB2E7238640808013:5F41CADEB2E723864080801A:5F41CADEB2E723864080801F:5F41CADEB2E7238640808020:5F41CADEB2E7238640808018:5F41CADEB2E7238640808019:5F41CADEB2E723864080800E:5F41CADEB2E7238640808012:5F41CADEB2E723864080801C:5F41CADEB2E723864080800F:5F41CADEB2E7238640808010:5F41CADEB2E7238640808023:5F41CADDB2E7238640808008:5F41CADEB2E723864080801B:5F41CADEB2E7238640808022 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
When we import the dataARC dataset, the XY coordinates are imported as character strings since not every observation has an entry. The XY coordinates are also in latitude/longitude format, which is inappropriate for many types of spatial operations. To convert it to the projected coordinate system we defined above, we first need to convert the degrees to radians (a pecularity with the proj4string library), and then we can transform to EPSG:9040.
arc[,c("X","Y") := lapply(.SD,as.numeric), .SDcols = c("X","Y")] # Convert to numeric
arc[, `:=`(X = X * ..pi / 180, Y = Y * ..pi / 180)] # Convert to radians
arc[,`:=`(X = ptransform(.(X,Y),src.proj=CRS("+proj=longlat +datum=WGS84"), # Project the coordinates
dst.proj=proj)[[1]],
Y = ptransform(.(X,Y),src.proj=CRS("+proj=longlat +datum=WGS84"),
dst.proj=proj)[[2]])]
The dataARC dataset has its concepts and constituent datasets listed as hashes. Since we'll want to work with their actual values later on, we'll import both right now.
concepts <- read.csv("CONCEPT_DATA_FRAME.csv",
stringsAsFactors = FALSE)
concepts <- as.data.table(concepts)
concepts[,names(concepts) := lapply(.SD,trimws,which='left')]
head(concepts)
HASH | NAME |
---|---|
<chr> | <chr> |
5F430A73836C1E48136B4F65 | administrative unit |
5F430A73836C1E48136B4F67 | agricultural landscape |
5F430A73836C1E48136B4F64 | abandoned place |
5F430A73836C1E48136B4F66 | agricultural building |
5F430A73836C1E48136B4F69 | animal husbandry |
5F430A73836C1E48136B4F6C | avian |
datasets <- read.csv("DATASET_HASH_OUT.csv",
stringsAsFactors = FALSE,
encoding='UTF-8')
datasets <- as.data.table(datasets)
datasets[,names(datasets) := lapply(.SD,trimws,which='left')]
datasets
HASH | NAME |
---|---|
<chr> | <chr> |
5fc98f37960aba3111930cbe | Pollen Data (Iceland) |
5fc98f5e960aba3111930cc0 | Paleoclimate Iceland |
5f41cae4b2e723864080818b | Icelandic Excavation Data - Key finds and archaeological data by stratigraphic units |
5f41cae4b2e7238640808188 | Icelandic Excavation Data - Finds from each group of stratigraphic units |
5f41cae4b2e723864080817f | Icelandic Sagas Database |
5f41cae4b2e7238640808183 | Northwest Icelandic Cairns |
5f41cae4b2e7238640808182 | Icelandic Farm Histories Database |
5f41cae4b2e723864080818a | Icelandic Excavation Data - Unit Descriptions |
5f41cae4b2e7238640808187 | Environmental Threats to Icelandic Archaeological Sites |
5f41cae4b2e723864080817c | Strategic Environmental Archaeology Database (SEAD) |
5f41cae4b2e7238640808180 | Tephrabase |
5f41cae4b2e7238640808184 | Zooarchaeological Data from NABO Excavations (NABONOSEAD) |
Now let's pull out the observations for the Jardabok, contained in the Icelandic Farm Histories Database. We'll use the latter's acronym (fhd) as a variable name for expediency's sake. For this, we'll query the datasets data.table with "Farm Histories", and filter the dataARC entries by the resulting hash.
query <- "Farm Histories"
fhd_hash <- datasets[str_detect(NAME,query),HASH]
fhd_hash <- toupper(fhd_hash) # Since the dataARC hashes are all capitalized
fhd <- arc[DATASET == fhd_hash,] # Filter dataARC and assign to new variable
fhd
NUMBER | ID | X | Y | DATASET | CATEGORY | ENTRY | CONCEPT | COMBINATOR | RELATED | CONTEXT |
---|---|---|---|---|---|---|---|---|---|---|
<chr> | <chr> | <dbl> | <dbl> | <chr> | <chr> | <chr> | <chr> | <chr> | <chr> | <chr> |
173315 | 5FC9E27E7C39E36162AF5123 | 13934448 | -2917322 | 5F41CAE4B2E7238640808182 | START_DATE | 900 | 5F430A73836C1E48136B4F67:5F430A74836C1E48136B4F71:5F430A74836C1E48136B4F77:5F430A74836C1E48136B4F86:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F9A:5F430A75836C1E48136B4FA0:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A76836C1E48136B4FD8:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B5011:5F430A77836C1E48136B5014:5F430A77836C1E48136B501F:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045:5F430A78836C1E48136B5050 | 5F41CADEB2E7238640808031:5F41CADEB2E7238640808030:5F41CADEB2E7238640808035:5F41CADEB2E723864080802F | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
173316 | 5FC9E27E7C39E36162AF5123 | 13934448 | -2917322 | 5F41CAE4B2E7238640808182 | END_DATE | 1900 | 5F430A73836C1E48136B4F67:5F430A74836C1E48136B4F71:5F430A74836C1E48136B4F77:5F430A74836C1E48136B4F86:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F9A:5F430A75836C1E48136B4FA0:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A76836C1E48136B4FD8:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B5011:5F430A77836C1E48136B5014:5F430A77836C1E48136B501F:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045:5F430A78836C1E48136B5050 | 5F41CADEB2E7238640808031:5F41CADEB2E7238640808030:5F41CADEB2E7238640808035:5F41CADEB2E723864080802F | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
173317 | 5FC9E27E7C39E36162AF5123 | 13934448 | -2917322 | 5F41CAE4B2E7238640808182 | SHIRE_NAME | Akrahreppur | 5F430A73836C1E48136B4F67:5F430A74836C1E48136B4F71:5F430A74836C1E48136B4F77:5F430A74836C1E48136B4F86:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F9A:5F430A75836C1E48136B4FA0:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A76836C1E48136B4FD8:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B5011:5F430A77836C1E48136B5014:5F430A77836C1E48136B501F:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045:5F430A78836C1E48136B5050 | 5F41CADEB2E7238640808031:5F41CADEB2E7238640808030:5F41CADEB2E7238640808035:5F41CADEB2E723864080802F | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
173318 | 5FC9E27E7C39E36162AF5123 | 13934448 | -2917322 | 5F41CAE4B2E7238640808182 | PARISH_NAME | Flugumýrarsókn | 5F430A73836C1E48136B4F67:5F430A74836C1E48136B4F71:5F430A74836C1E48136B4F77:5F430A74836C1E48136B4F86:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F9A:5F430A75836C1E48136B4FA0:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A76836C1E48136B4FD8:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B5011:5F430A77836C1E48136B5014:5F430A77836C1E48136B501F:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045:5F430A78836C1E48136B5050 | 5F41CADEB2E7238640808031:5F41CADEB2E7238640808030:5F41CADEB2E7238640808035:5F41CADEB2E723864080802F | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
173319 | 5FC9E27E7C39E36162AF5123 | 13934448 | -2917322 | 5F41CAE4B2E7238640808182 | TITLE | Flugumýri | 5F430A73836C1E48136B4F67:5F430A74836C1E48136B4F71:5F430A74836C1E48136B4F77:5F430A74836C1E48136B4F86:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F9A:5F430A75836C1E48136B4FA0:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A76836C1E48136B4FD8:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B5011:5F430A77836C1E48136B5014:5F430A77836C1E48136B501F:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045:5F430A78836C1E48136B5050 | 5F41CADEB2E7238640808031:5F41CADEB2E7238640808030:5F41CADEB2E7238640808035:5F41CADEB2E723864080802F | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
173320 | 5FC9E27E7C39E36162AF5123 | 13934448 | -2917322 | 5F41CAE4B2E7238640808182 | FARM_NUMBER | SK-235 | 5F430A73836C1E48136B4F67:5F430A74836C1E48136B4F71:5F430A74836C1E48136B4F77:5F430A74836C1E48136B4F86:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F9A:5F430A75836C1E48136B4FA0:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A76836C1E48136B4FD8:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B5011:5F430A77836C1E48136B5014:5F430A77836C1E48136B501F:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045:5F430A78836C1E48136B5050 | 5F41CADEB2E7238640808031:5F41CADEB2E7238640808030:5F41CADEB2E7238640808035:5F41CADEB2E723864080802F | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
173321 | 5FC9E27E7C39E36162AF5123 | 13934448 | -2917322 | 5F41CAE4B2E7238640808182 | ISLEIF_FARMS_ID | 4901 | 5F430A73836C1E48136B4F67:5F430A74836C1E48136B4F71:5F430A74836C1E48136B4F77:5F430A74836C1E48136B4F86:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F9A:5F430A75836C1E48136B4FA0:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A76836C1E48136B4FD8:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B5011:5F430A77836C1E48136B5014:5F430A77836C1E48136B501F:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045:5F430A78836C1E48136B5050 | 5F41CADEB2E7238640808031:5F41CADEB2E7238640808030:5F41CADEB2E7238640808035:5F41CADEB2E723864080802F | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
173322 | 5FC9E27E7C39E36162AF5123 | 13934448 | -2917322 | 5F41CAE4B2E7238640808182 | VALUATION | 100 | 5F430A73836C1E48136B4F67:5F430A74836C1E48136B4F71:5F430A74836C1E48136B4F77:5F430A74836C1E48136B4F86:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F9A:5F430A75836C1E48136B4FA0:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A76836C1E48136B4FD8:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B5011:5F430A77836C1E48136B5014:5F430A77836C1E48136B501F:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045:5F430A78836C1E48136B5050 | 5F41CADEB2E7238640808031:5F41CADEB2E7238640808030:5F41CADEB2E7238640808035:5F41CADEB2E723864080802F | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
173323 | 5FC9E27E7C39E36162AF5123 | 13934448 | -2917322 | 5F41CAE4B2E7238640808182 | 1861_ADJUSTED_VALUE | 55.6 | 5F430A73836C1E48136B4F67:5F430A74836C1E48136B4F71:5F430A74836C1E48136B4F77:5F430A74836C1E48136B4F86:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F9A:5F430A75836C1E48136B4FA0:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A76836C1E48136B4FD8:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B5011:5F430A77836C1E48136B5014:5F430A77836C1E48136B501F:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045:5F430A78836C1E48136B5050 | 5F41CADEB2E7238640808031:5F41CADEB2E7238640808030:5F41CADEB2E7238640808035:5F41CADEB2E723864080802F | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
173324 | 5FC9E27E7C39E36162AF5123 | 13934448 | -2917322 | 5F41CAE4B2E7238640808182 | FODDER_PRODUCTIVITY | 6 | 5F430A73836C1E48136B4F67:5F430A74836C1E48136B4F71:5F430A74836C1E48136B4F77:5F430A74836C1E48136B4F86:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F9A:5F430A75836C1E48136B4FA0:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A76836C1E48136B4FD8:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B5011:5F430A77836C1E48136B5014:5F430A77836C1E48136B501F:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045:5F430A78836C1E48136B5050 | 5F41CADEB2E7238640808031:5F41CADEB2E7238640808030:5F41CADEB2E7238640808035:5F41CADEB2E723864080802F | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
173325 | 5FC9E27E7C39E36162AF5123 | 13934448 | -2917322 | 5F41CAE4B2E7238640808182 | ENTITY_NAME | Biskupsstóllinn Hólar | 5F430A73836C1E48136B4F67:5F430A74836C1E48136B4F71:5F430A74836C1E48136B4F77:5F430A74836C1E48136B4F86:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F9A:5F430A75836C1E48136B4FA0:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A76836C1E48136B4FD8:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B5011:5F430A77836C1E48136B5014:5F430A77836C1E48136B501F:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045:5F430A78836C1E48136B5050 | 5F41CADEB2E7238640808031:5F41CADEB2E7238640808030:5F41CADEB2E7238640808035:5F41CADEB2E723864080802F | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
173326 | 5FC9E27E7C39E36162AF5123 | 13934448 | -2917322 | 5F41CAE4B2E7238640808182 | ENTITY_TYPE_ALIAS | bishop | 5F430A73836C1E48136B4F67:5F430A74836C1E48136B4F71:5F430A74836C1E48136B4F77:5F430A74836C1E48136B4F86:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F9A:5F430A75836C1E48136B4FA0:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A76836C1E48136B4FD8:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B5011:5F430A77836C1E48136B5014:5F430A77836C1E48136B501F:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045:5F430A78836C1E48136B5050 | 5F41CADEB2E7238640808031:5F41CADEB2E7238640808030:5F41CADEB2E7238640808035:5F41CADEB2E723864080802F | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
173327 | 5FC9E27E7C39E36162AF5124 | 13946356 | -2918053 | 5F41CAE4B2E7238640808182 | START_DATE | 900 | 5F430A73836C1E48136B4F67:5F430A74836C1E48136B4F71:5F430A74836C1E48136B4F77:5F430A74836C1E48136B4F86:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F9A:5F430A75836C1E48136B4FA0:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A76836C1E48136B4FD8:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B5011:5F430A77836C1E48136B5014:5F430A77836C1E48136B501F:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045:5F430A78836C1E48136B5050 | 5F41CADEB2E7238640808031:5F41CADEB2E7238640808030:5F41CADEB2E7238640808035:5F41CADEB2E723864080802F | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
173328 | 5FC9E27E7C39E36162AF5124 | 13946356 | -2918053 | 5F41CAE4B2E7238640808182 | END_DATE | 1900 | 5F430A73836C1E48136B4F67:5F430A74836C1E48136B4F71:5F430A74836C1E48136B4F77:5F430A74836C1E48136B4F86:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F9A:5F430A75836C1E48136B4FA0:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A76836C1E48136B4FD8:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B5011:5F430A77836C1E48136B5014:5F430A77836C1E48136B501F:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045:5F430A78836C1E48136B5050 | 5F41CADEB2E7238640808031:5F41CADEB2E7238640808030:5F41CADEB2E7238640808035:5F41CADEB2E723864080802F | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
173329 | 5FC9E27E7C39E36162AF5124 | 13946356 | -2918053 | 5F41CAE4B2E7238640808182 | SHIRE_NAME | Akrahreppur | 5F430A73836C1E48136B4F67:5F430A74836C1E48136B4F71:5F430A74836C1E48136B4F77:5F430A74836C1E48136B4F86:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F9A:5F430A75836C1E48136B4FA0:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A76836C1E48136B4FD8:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B5011:5F430A77836C1E48136B5014:5F430A77836C1E48136B501F:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045:5F430A78836C1E48136B5050 | 5F41CADEB2E7238640808031:5F41CADEB2E7238640808030:5F41CADEB2E7238640808035:5F41CADEB2E723864080802F | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
173330 | 5FC9E27E7C39E36162AF5124 | 13946356 | -2918053 | 5F41CAE4B2E7238640808182 | PARISH_NAME | Flugumýrarsókn | 5F430A73836C1E48136B4F67:5F430A74836C1E48136B4F71:5F430A74836C1E48136B4F77:5F430A74836C1E48136B4F86:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F9A:5F430A75836C1E48136B4FA0:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A76836C1E48136B4FD8:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B5011:5F430A77836C1E48136B5014:5F430A77836C1E48136B501F:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045:5F430A78836C1E48136B5050 | 5F41CADEB2E7238640808031:5F41CADEB2E7238640808030:5F41CADEB2E7238640808035:5F41CADEB2E723864080802F | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
173331 | 5FC9E27E7C39E36162AF5124 | 13946356 | -2918053 | 5F41CAE4B2E7238640808182 | TITLE | Frostastaðir | 5F430A73836C1E48136B4F67:5F430A74836C1E48136B4F71:5F430A74836C1E48136B4F77:5F430A74836C1E48136B4F86:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F9A:5F430A75836C1E48136B4FA0:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A76836C1E48136B4FD8:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B5011:5F430A77836C1E48136B5014:5F430A77836C1E48136B501F:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045:5F430A78836C1E48136B5050 | 5F41CADEB2E7238640808031:5F41CADEB2E7238640808030:5F41CADEB2E7238640808035:5F41CADEB2E723864080802F | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
173332 | 5FC9E27E7C39E36162AF5124 | 13946356 | -2918053 | 5F41CAE4B2E7238640808182 | FARM_NUMBER | SK-245 | 5F430A73836C1E48136B4F67:5F430A74836C1E48136B4F71:5F430A74836C1E48136B4F77:5F430A74836C1E48136B4F86:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F9A:5F430A75836C1E48136B4FA0:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A76836C1E48136B4FD8:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B5011:5F430A77836C1E48136B5014:5F430A77836C1E48136B501F:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045:5F430A78836C1E48136B5050 | 5F41CADEB2E7238640808031:5F41CADEB2E7238640808030:5F41CADEB2E7238640808035:5F41CADEB2E723864080802F | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
173333 | 5FC9E27E7C39E36162AF5124 | 13946356 | -2918053 | 5F41CAE4B2E7238640808182 | ISLEIF_FARMS_ID | 4911 | 5F430A73836C1E48136B4F67:5F430A74836C1E48136B4F71:5F430A74836C1E48136B4F77:5F430A74836C1E48136B4F86:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F9A:5F430A75836C1E48136B4FA0:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A76836C1E48136B4FD8:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B5011:5F430A77836C1E48136B5014:5F430A77836C1E48136B501F:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045:5F430A78836C1E48136B5050 | 5F41CADEB2E7238640808031:5F41CADEB2E7238640808030:5F41CADEB2E7238640808035:5F41CADEB2E723864080802F | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
173334 | 5FC9E27E7C39E36162AF5124 | 13946356 | -2918053 | 5F41CAE4B2E7238640808182 | VALUATION | 80 | 5F430A73836C1E48136B4F67:5F430A74836C1E48136B4F71:5F430A74836C1E48136B4F77:5F430A74836C1E48136B4F86:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F9A:5F430A75836C1E48136B4FA0:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A76836C1E48136B4FD8:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B5011:5F430A77836C1E48136B5014:5F430A77836C1E48136B501F:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045:5F430A78836C1E48136B5050 | 5F41CADEB2E7238640808031:5F41CADEB2E7238640808030:5F41CADEB2E7238640808035:5F41CADEB2E723864080802F | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
173335 | 5FC9E27E7C39E36162AF5124 | 13946356 | -2918053 | 5F41CAE4B2E7238640808182 | 1861_ADJUSTED_VALUE | 28.5 | 5F430A73836C1E48136B4F67:5F430A74836C1E48136B4F71:5F430A74836C1E48136B4F77:5F430A74836C1E48136B4F86:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F9A:5F430A75836C1E48136B4FA0:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A76836C1E48136B4FD8:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B5011:5F430A77836C1E48136B5014:5F430A77836C1E48136B501F:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045:5F430A78836C1E48136B5050 | 5F41CADEB2E7238640808031:5F41CADEB2E7238640808030:5F41CADEB2E7238640808035:5F41CADEB2E723864080802F | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
173336 | 5FC9E27E7C39E36162AF5124 | 13946356 | -2918053 | 5F41CAE4B2E7238640808182 | FODDER_PRODUCTIVITY | 7 | 5F430A73836C1E48136B4F67:5F430A74836C1E48136B4F71:5F430A74836C1E48136B4F77:5F430A74836C1E48136B4F86:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F9A:5F430A75836C1E48136B4FA0:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A76836C1E48136B4FD8:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B5011:5F430A77836C1E48136B5014:5F430A77836C1E48136B501F:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045:5F430A78836C1E48136B5050 | 5F41CADEB2E7238640808031:5F41CADEB2E7238640808030:5F41CADEB2E7238640808035:5F41CADEB2E723864080802F | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
173337 | 5FC9E27E7C39E36162AF5124 | 13946356 | -2918053 | 5F41CAE4B2E7238640808182 | ENTITY_NAME | Biskupsstóllinn Hólar | 5F430A73836C1E48136B4F67:5F430A74836C1E48136B4F71:5F430A74836C1E48136B4F77:5F430A74836C1E48136B4F86:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F9A:5F430A75836C1E48136B4FA0:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A76836C1E48136B4FD8:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B5011:5F430A77836C1E48136B5014:5F430A77836C1E48136B501F:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045:5F430A78836C1E48136B5050 | 5F41CADEB2E7238640808031:5F41CADEB2E7238640808030:5F41CADEB2E7238640808035:5F41CADEB2E723864080802F | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
173338 | 5FC9E27E7C39E36162AF5124 | 13946356 | -2918053 | 5F41CAE4B2E7238640808182 | ENTITY_TYPE_ALIAS | bishop | 5F430A73836C1E48136B4F67:5F430A74836C1E48136B4F71:5F430A74836C1E48136B4F77:5F430A74836C1E48136B4F86:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F9A:5F430A75836C1E48136B4FA0:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A76836C1E48136B4FD8:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B5011:5F430A77836C1E48136B5014:5F430A77836C1E48136B501F:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045:5F430A78836C1E48136B5050 | 5F41CADEB2E7238640808031:5F41CADEB2E7238640808030:5F41CADEB2E7238640808035:5F41CADEB2E723864080802F | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
173522 | 5FC9E27E7C39E36162AF5134 | 13921103 | -2922671 | 5F41CAE4B2E7238640808182 | RELATIONSHIPS_LOOKUP_RESOURCE_EN | driftwood | 5F430A73836C1E48136B4F67:5F430A74836C1E48136B4F6F:5F430A74836C1E48136B4F71:5F430A74836C1E48136B4F77:5F430A74836C1E48136B4F86:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F93:5F430A74836C1E48136B4F9A:5F430A75836C1E48136B4FA0:5F430A75836C1E48136B4FA4:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FC2:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A76836C1E48136B4FD8:5F430A76836C1E48136B4FE3:5F430A76836C1E48136B4FE5:5F430A76836C1E48136B4FE7:5F430A76836C1E48136B4FF1:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B5008:5F430A77836C1E48136B5014:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045:5F430A78836C1E48136B5068:5F430A78836C1E48136B506B | 5F41CADEB2E7238640808031:5F41CADFB2E7238640808043:5F41CADEB2E723864080802E:5F41CADEB2E7238640808035 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
173523 | 5FC9E27E7C39E36162AF5134 | 13921103 | -2922671 | 5F41CAE4B2E7238640808182 | RELATIONSHIPS_LOOKUP_RESOURCE_EN | outfield pasture | 5F430A73836C1E48136B4F67:5F430A74836C1E48136B4F6F:5F430A74836C1E48136B4F71:5F430A74836C1E48136B4F77:5F430A74836C1E48136B4F86:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F93:5F430A74836C1E48136B4F9A:5F430A75836C1E48136B4FA0:5F430A75836C1E48136B4FA4:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FC2:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A76836C1E48136B4FD8:5F430A76836C1E48136B4FE3:5F430A76836C1E48136B4FE5:5F430A76836C1E48136B4FE7:5F430A76836C1E48136B4FF1:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B5008:5F430A77836C1E48136B5014:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045:5F430A78836C1E48136B5068:5F430A78836C1E48136B506B | 5F41CADEB2E7238640808031:5F41CADFB2E7238640808043:5F41CADEB2E723864080802E:5F41CADEB2E7238640808035 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
173524 | 5FC9E27E7C39E36162AF5134 | 13921103 | -2922671 | 5F41CAE4B2E7238640808182 | RELATIONSHIPS_LOOKUP_RESOURCE_EN | woodland | 5F430A73836C1E48136B4F67:5F430A74836C1E48136B4F6F:5F430A74836C1E48136B4F71:5F430A74836C1E48136B4F77:5F430A74836C1E48136B4F86:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F93:5F430A74836C1E48136B4F9A:5F430A75836C1E48136B4FA0:5F430A75836C1E48136B4FA4:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FC2:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A76836C1E48136B4FD8:5F430A76836C1E48136B4FE3:5F430A76836C1E48136B4FE5:5F430A76836C1E48136B4FE7:5F430A76836C1E48136B4FF1:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B5008:5F430A77836C1E48136B5014:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045:5F430A78836C1E48136B5068:5F430A78836C1E48136B506B | 5F41CADEB2E7238640808031:5F41CADFB2E7238640808043:5F41CADEB2E723864080802E:5F41CADEB2E7238640808035 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
173525 | 5FC9E27E7C39E36162AF5134 | 13921103 | -2922671 | 5F41CAE4B2E7238640808182 | START_DATE | 900 | 5F430A73836C1E48136B4F67:5F430A74836C1E48136B4F6F:5F430A74836C1E48136B4F71:5F430A74836C1E48136B4F77:5F430A74836C1E48136B4F86:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F93:5F430A74836C1E48136B4F9A:5F430A75836C1E48136B4FA0:5F430A75836C1E48136B4FA4:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FC2:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A76836C1E48136B4FD8:5F430A76836C1E48136B4FE3:5F430A76836C1E48136B4FE5:5F430A76836C1E48136B4FE7:5F430A76836C1E48136B4FF1:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B5008:5F430A77836C1E48136B5014:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045:5F430A78836C1E48136B5068:5F430A78836C1E48136B506B | 5F41CADEB2E7238640808031:5F41CADFB2E7238640808043:5F41CADEB2E723864080802E:5F41CADEB2E7238640808035 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
173526 | 5FC9E27E7C39E36162AF5134 | 13921103 | -2922671 | 5F41CAE4B2E7238640808182 | START_DATE | 900 | 5F430A73836C1E48136B4F67:5F430A74836C1E48136B4F6F:5F430A74836C1E48136B4F71:5F430A74836C1E48136B4F77:5F430A74836C1E48136B4F86:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F93:5F430A74836C1E48136B4F9A:5F430A75836C1E48136B4FA0:5F430A75836C1E48136B4FA4:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FC2:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A76836C1E48136B4FD8:5F430A76836C1E48136B4FE3:5F430A76836C1E48136B4FE5:5F430A76836C1E48136B4FE7:5F430A76836C1E48136B4FF1:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B5008:5F430A77836C1E48136B5014:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045:5F430A78836C1E48136B5068:5F430A78836C1E48136B506B | 5F41CADEB2E7238640808031:5F41CADFB2E7238640808043:5F41CADEB2E723864080802E:5F41CADEB2E7238640808035 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
173527 | 5FC9E27E7C39E36162AF5134 | 13921103 | -2922671 | 5F41CAE4B2E7238640808182 | START_DATE | 900 | 5F430A73836C1E48136B4F67:5F430A74836C1E48136B4F6F:5F430A74836C1E48136B4F71:5F430A74836C1E48136B4F77:5F430A74836C1E48136B4F86:5F430A74836C1E48136B4F90:5F430A74836C1E48136B4F93:5F430A74836C1E48136B4F9A:5F430A75836C1E48136B4FA0:5F430A75836C1E48136B4FA4:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FC2:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A76836C1E48136B4FD8:5F430A76836C1E48136B4FE3:5F430A76836C1E48136B4FE5:5F430A76836C1E48136B4FE7:5F430A76836C1E48136B4FF1:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B5008:5F430A77836C1E48136B5014:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045:5F430A78836C1E48136B5068:5F430A78836C1E48136B506B | 5F41CADEB2E7238640808031:5F41CADFB2E7238640808043:5F41CADEB2E723864080802E:5F41CADEB2E7238640808035 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ |
221356 | 5FC9E27F7C39E36162AF5F61 | 14134129 | -3111405 | 5F41CAE4B2E7238640808182 | TITLE | Valdalækur | 5F430A74836C1E48136B4F77:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045 | 5F41CADEB2E7238640808035 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
221357 | 5FC9E27F7C39E36162AF5F61 | 14134129 | -3111405 | 5F41CAE4B2E7238640808182 | FARM_NUMBER | HV-104 | 5F430A74836C1E48136B4F77:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045 | 5F41CADEB2E7238640808035 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
221358 | 5FC9E27F7C39E36162AF5F61 | 14134129 | -3111405 | 5F41CAE4B2E7238640808182 | ISLEIF_FARMS_ID | 1219 | 5F430A74836C1E48136B4F77:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045 | 5F41CADEB2E7238640808035 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
221359 | 5FC9E27F7C39E36162AF5F61 | 14134129 | -3111405 | 5F41CAE4B2E7238640808182 | VALUATION | 16 | 5F430A74836C1E48136B4F77:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045 | 5F41CADEB2E7238640808035 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
221360 | 5FC9E27F7C39E36162AF5F61 | 14134129 | -3111405 | 5F41CAE4B2E7238640808182 | 1861_ADJUSTED_VALUE | 16.3 | 5F430A74836C1E48136B4F77:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045 | 5F41CADEB2E7238640808035 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
221361 | 5FC9E27F7C39E36162AF5F61 | 14134129 | -3111405 | 5F41CAE4B2E7238640808182 | ENTITY_NAME | Konungseignir - Þingeyrarklaustur | 5F430A74836C1E48136B4F77:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045 | 5F41CADEB2E7238640808035 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
221362 | 5FC9E27F7C39E36162AF5F61 | 14134129 | -3111405 | 5F41CAE4B2E7238640808182 | ENTITY_TYPE_ALIAS | king | 5F430A74836C1E48136B4F77:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045 | 5F41CADEB2E7238640808035 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
221363 | 5FC9E27F7C39E36162AF5F62 | 14107078 | -3122697 | 5F41CAE4B2E7238640808182 | START_DATE | 900 | 5F430A74836C1E48136B4F77:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045 | 5F41CADEB2E7238640808035 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
221364 | 5FC9E27F7C39E36162AF5F62 | 14107078 | -3122697 | 5F41CAE4B2E7238640808182 | END_DATE | 1900 | 5F430A74836C1E48136B4F77:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045 | 5F41CADEB2E7238640808035 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
221365 | 5FC9E27F7C39E36162AF5F62 | 14107078 | -3122697 | 5F41CAE4B2E7238640808182 | SHIRE_NAME | Þverárhreppur | 5F430A74836C1E48136B4F77:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045 | 5F41CADEB2E7238640808035 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
221366 | 5FC9E27F7C39E36162AF5F62 | 14107078 | -3122697 | 5F41CAE4B2E7238640808182 | PARISH_NAME | Vesturhópshólasókn | 5F430A74836C1E48136B4F77:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045 | 5F41CADEB2E7238640808035 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
221367 | 5FC9E27F7C39E36162AF5F62 | 14107078 | -3122697 | 5F41CAE4B2E7238640808182 | TITLE | Vatnsendi | 5F430A74836C1E48136B4F77:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045 | 5F41CADEB2E7238640808035 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
221368 | 5FC9E27F7C39E36162AF5F62 | 14107078 | -3122697 | 5F41CAE4B2E7238640808182 | FARM_NUMBER | HV-133 | 5F430A74836C1E48136B4F77:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045 | 5F41CADEB2E7238640808035 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
221369 | 5FC9E27F7C39E36162AF5F62 | 14107078 | -3122697 | 5F41CAE4B2E7238640808182 | ISLEIF_FARMS_ID | 1419 | 5F430A74836C1E48136B4F77:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045 | 5F41CADEB2E7238640808035 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
221370 | 5FC9E27F7C39E36162AF5F62 | 14107078 | -3122697 | 5F41CAE4B2E7238640808182 | VALUATION | 16 | 5F430A74836C1E48136B4F77:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045 | 5F41CADEB2E7238640808035 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
221371 | 5FC9E27F7C39E36162AF5F62 | 14107078 | -3122697 | 5F41CAE4B2E7238640808182 | 1861_ADJUSTED_VALUE | 11.9 | 5F430A74836C1E48136B4F77:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045 | 5F41CADEB2E7238640808035 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
221372 | 5FC9E27F7C39E36162AF5F62 | 14107078 | -3122697 | 5F41CAE4B2E7238640808182 | ENTITY_NAME | Steinun Erlendsdóttir & Þórður Þorleifsson | 5F430A74836C1E48136B4F77:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045 | 5F41CADEB2E7238640808035 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
221373 | 5FC9E27F7C39E36162AF5F62 | 14107078 | -3122697 | 5F41CAE4B2E7238640808182 | ENTITY_TYPE_ALIAS | person | 5F430A74836C1E48136B4F77:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045 | 5F41CADEB2E7238640808035 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
221400 | 5FC9E27F7C39E36162AF5F64 | 14117087 | -3128667 | 5F41CAE4B2E7238640808182 | START_DATE | 900 | 5F430A74836C1E48136B4F77:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045 | 5F41CADEB2E7238640808035:5F41CADFB2E7238640808040 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
221401 | 5FC9E27F7C39E36162AF5F64 | 14117087 | -3128667 | 5F41CAE4B2E7238640808182 | END_DATE | 1900 | 5F430A74836C1E48136B4F77:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045 | 5F41CADEB2E7238640808035:5F41CADFB2E7238640808040 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
221402 | 5FC9E27F7C39E36162AF5F64 | 14117087 | -3128667 | 5F41CAE4B2E7238640808182 | SHIRE_NAME | Þverárhreppur | 5F430A74836C1E48136B4F77:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045 | 5F41CADEB2E7238640808035:5F41CADFB2E7238640808040 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
221403 | 5FC9E27F7C39E36162AF5F64 | 14117087 | -3128667 | 5F41CAE4B2E7238640808182 | PARISH_NAME | Vesturhópshólasókn | 5F430A74836C1E48136B4F77:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045 | 5F41CADEB2E7238640808035:5F41CADFB2E7238640808040 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
221404 | 5FC9E27F7C39E36162AF5F64 | 14117087 | -3128667 | 5F41CAE4B2E7238640808182 | TITLE | Þorfinnstaðir | 5F430A74836C1E48136B4F77:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045 | 5F41CADEB2E7238640808035:5F41CADFB2E7238640808040 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
221405 | 5FC9E27F7C39E36162AF5F64 | 14117087 | -3128667 | 5F41CAE4B2E7238640808182 | FARM_NUMBER | HV-112 | 5F430A74836C1E48136B4F77:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045 | 5F41CADEB2E7238640808035:5F41CADFB2E7238640808040 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
221406 | 5FC9E27F7C39E36162AF5F64 | 14117087 | -3128667 | 5F41CAE4B2E7238640808182 | ISLEIF_FARMS_ID | 1279 | 5F430A74836C1E48136B4F77:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045 | 5F41CADEB2E7238640808035:5F41CADFB2E7238640808040 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
221407 | 5FC9E27F7C39E36162AF5F64 | 14117087 | -3128667 | 5F41CAE4B2E7238640808182 | VALUATION | 10 | 5F430A74836C1E48136B4F77:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045 | 5F41CADEB2E7238640808035:5F41CADFB2E7238640808040 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
221408 | 5FC9E27F7C39E36162AF5F64 | 14117087 | -3128667 | 5F41CAE4B2E7238640808182 | 1861_ADJUSTED_VALUE | 7.1 | 5F430A74836C1E48136B4F77:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045 | 5F41CADEB2E7238640808035:5F41CADFB2E7238640808040 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
221409 | 5FC9E27F7C39E36162AF5F64 | 14117087 | -3128667 | 5F41CAE4B2E7238640808182 | FODDER_PRODUCTIVITY | 2 | 5F430A74836C1E48136B4F77:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045 | 5F41CADEB2E7238640808035:5F41CADFB2E7238640808040 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
221410 | 5FC9E27F7C39E36162AF5F64 | 14117087 | -3128667 | 5F41CAE4B2E7238640808182 | ENTITY_NAME | Beneficium Vesturhópshólar | 5F430A74836C1E48136B4F77:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045 | 5F41CADEB2E7238640808035:5F41CADFB2E7238640808040 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
221411 | 5FC9E27F7C39E36162AF5F64 | 14117087 | -3128667 | 5F41CAE4B2E7238640808182 | ENTITY_TYPE_ALIAS | beneficium | 5F430A74836C1E48136B4F77:5F430A75836C1E48136B4FA5:5F430A75836C1E48136B4FA6:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FCB:5F430A76836C1E48136B4FCF:5F430A76836C1E48136B4FD0:5F430A76836C1E48136B4FD2:5F430A76836C1E48136B4FD7:5F430A77836C1E48136B5024:5F430A78836C1E48136B5045 | 5F41CADEB2E7238640808035:5F41CADFB2E7238640808040 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
We'll do the same for the Saga Map sites.
query <- "Sagas"
saga_hash <- datasets[str_detect(NAME,query),HASH]
saga_hash <- toupper(saga_hash)
saga <- arc[DATASET == saga_hash,]
head(saga)
NUMBER | ID | X | Y | DATASET | CATEGORY | ENTRY | CONCEPT | COMBINATOR | RELATED | CONTEXT |
---|---|---|---|---|---|---|---|---|---|---|
<chr> | <chr> | <dbl> | <dbl> | <chr> | <chr> | <chr> | <chr> | <chr> | <chr> | <chr> |
50716 | 5FC9E2227C39E36162AF2098 | 13711383 | -2648585 | 5F41CAE4B2E723864080817F | ID | 158 | 5F430A73836C1E48136B4F67:5F430A73836C1E48136B4F68:5F430A73836C1E48136B4F69:5F430A74836C1E48136B4F6E:5F430A74836C1E48136B4F7A:5F430A74836C1E48136B4F7B:5F430A74836C1E48136B4F83:5F430A74836C1E48136B4F8D:5F430A74836C1E48136B4F90:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FA9:5F430A75836C1E48136B4FBD:5F430A75836C1E48136B4FC1:5F430A75836C1E48136B4FC4:5F430A75836C1E48136B4FC9:5F430A76836C1E48136B4FD9:5F430A76836C1E48136B4FED:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B4FF9:5F430A77836C1E48136B4FFA:5F430A77836C1E48136B500B:5F430A77836C1E48136B500D:5F430A77836C1E48136B5014:5F430A77836C1E48136B5018:5F430A78836C1E48136B5035:5F430A78836C1E48136B5040 | 5F41CADEB2E723864080802C:5F41CADEB2E7238640808038 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
50717 | 5FC9E2227C39E36162AF2098 | 13711383 | -2648585 | 5F41CAE4B2E723864080817F | NAME | Ljósvetninga saga | 5F430A73836C1E48136B4F67:5F430A73836C1E48136B4F68:5F430A73836C1E48136B4F69:5F430A74836C1E48136B4F6E:5F430A74836C1E48136B4F7A:5F430A74836C1E48136B4F7B:5F430A74836C1E48136B4F83:5F430A74836C1E48136B4F8D:5F430A74836C1E48136B4F90:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FA9:5F430A75836C1E48136B4FBD:5F430A75836C1E48136B4FC1:5F430A75836C1E48136B4FC4:5F430A75836C1E48136B4FC9:5F430A76836C1E48136B4FD9:5F430A76836C1E48136B4FED:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B4FF9:5F430A77836C1E48136B4FFA:5F430A77836C1E48136B500B:5F430A77836C1E48136B500D:5F430A77836C1E48136B5014:5F430A77836C1E48136B5018:5F430A78836C1E48136B5035:5F430A78836C1E48136B5040 | 5F41CADEB2E723864080802C:5F41CADEB2E7238640808038 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
50718 | 5FC9E2227C39E36162AF2098 | 13711383 | -2648585 | 5F41CAE4B2E723864080817F | SAGAID | 4 | 5F430A73836C1E48136B4F67:5F430A73836C1E48136B4F68:5F430A73836C1E48136B4F69:5F430A74836C1E48136B4F6E:5F430A74836C1E48136B4F7A:5F430A74836C1E48136B4F7B:5F430A74836C1E48136B4F83:5F430A74836C1E48136B4F8D:5F430A74836C1E48136B4F90:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FA9:5F430A75836C1E48136B4FBD:5F430A75836C1E48136B4FC1:5F430A75836C1E48136B4FC4:5F430A75836C1E48136B4FC9:5F430A76836C1E48136B4FD9:5F430A76836C1E48136B4FED:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B4FF9:5F430A77836C1E48136B4FFA:5F430A77836C1E48136B500B:5F430A77836C1E48136B500D:5F430A77836C1E48136B5014:5F430A77836C1E48136B5018:5F430A78836C1E48136B5035:5F430A78836C1E48136B5040 | 5F41CADEB2E723864080802C:5F41CADEB2E7238640808038 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
50719 | 5FC9E2227C39E36162AF2098 | 13711383 | -2648585 | 5F41CAE4B2E723864080817F | SAGANAME | Ljósvetninga saga | 5F430A73836C1E48136B4F67:5F430A73836C1E48136B4F68:5F430A73836C1E48136B4F69:5F430A74836C1E48136B4F6E:5F430A74836C1E48136B4F7A:5F430A74836C1E48136B4F7B:5F430A74836C1E48136B4F83:5F430A74836C1E48136B4F8D:5F430A74836C1E48136B4F90:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FA9:5F430A75836C1E48136B4FBD:5F430A75836C1E48136B4FC1:5F430A75836C1E48136B4FC4:5F430A75836C1E48136B4FC9:5F430A76836C1E48136B4FD9:5F430A76836C1E48136B4FED:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B4FF9:5F430A77836C1E48136B4FFA:5F430A77836C1E48136B500B:5F430A77836C1E48136B500D:5F430A77836C1E48136B5014:5F430A77836C1E48136B5018:5F430A78836C1E48136B5035:5F430A78836C1E48136B5040 | 5F41CADEB2E723864080802C:5F41CADEB2E7238640808038 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
50720 | 5FC9E2227C39E36162AF2098 | 13711383 | -2648585 | 5F41CAE4B2E723864080817F | TYPE | farm | 5F430A73836C1E48136B4F67:5F430A73836C1E48136B4F68:5F430A73836C1E48136B4F69:5F430A74836C1E48136B4F6E:5F430A74836C1E48136B4F7A:5F430A74836C1E48136B4F7B:5F430A74836C1E48136B4F83:5F430A74836C1E48136B4F8D:5F430A74836C1E48136B4F90:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FA9:5F430A75836C1E48136B4FBD:5F430A75836C1E48136B4FC1:5F430A75836C1E48136B4FC4:5F430A75836C1E48136B4FC9:5F430A76836C1E48136B4FD9:5F430A76836C1E48136B4FED:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B4FF9:5F430A77836C1E48136B4FFA:5F430A77836C1E48136B500B:5F430A77836C1E48136B500D:5F430A77836C1E48136B5014:5F430A77836C1E48136B5018:5F430A78836C1E48136B5035:5F430A78836C1E48136B5040 | 5F41CADEB2E723864080802C:5F41CADEB2E7238640808038 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
50721 | 5FC9E2227C39E36162AF2098 | 13711383 | -2648585 | 5F41CAE4B2E723864080817F | CHAPTER | 1. kafli | 5F430A73836C1E48136B4F67:5F430A73836C1E48136B4F68:5F430A73836C1E48136B4F69:5F430A74836C1E48136B4F6E:5F430A74836C1E48136B4F7A:5F430A74836C1E48136B4F7B:5F430A74836C1E48136B4F83:5F430A74836C1E48136B4F8D:5F430A74836C1E48136B4F90:5F430A75836C1E48136B4FA7:5F430A75836C1E48136B4FA9:5F430A75836C1E48136B4FBD:5F430A75836C1E48136B4FC1:5F430A75836C1E48136B4FC4:5F430A75836C1E48136B4FC9:5F430A76836C1E48136B4FD9:5F430A76836C1E48136B4FED:5F430A76836C1E48136B4FF2:5F430A77836C1E48136B4FF9:5F430A77836C1E48136B4FFA:5F430A77836C1E48136B500B:5F430A77836C1E48136B500D:5F430A77836C1E48136B5014:5F430A77836C1E48136B5018:5F430A78836C1E48136B5035:5F430A78836C1E48136B5040 | 5F41CADEB2E723864080802C:5F41CADEB2E7238640808038 | 5f430a75836c1e48136b4fa7:5f430a76836c1e48136b4fd8:5f430a76836c1e48136b4fe1 | 5f430a75836c1e48136b4fa6:5f430a76836c1e48136b4fd2:5f430a76836c1e48136b4fe4:5f430a73836c1e48136b4f66:5f430a76836c1e48136b4fd7:5f430a76836c1e48136b4fd9:5f430a75836c1e48136b4fb4:5f430a76836c1e48136b4ff8:5f430a74836c1e48136b4f99 |
Right now, the data.table is structured such that each variable/attribute is stored in its own row under the "CATEGORY" and "ENTRY" columns, when they should instead be columns all pertaining to the same site. We need to cast those rows into new columns, reducing the number of rows in the process to one per Jardabok entry.
First select the observation types we want to keep. In the vignette, we were interested in variables that may be related to economic wellbeing (1861 Adjusted Valuation, Fodder Productivity, Owner, and Resource), so we'll fiter by those.
entries <- c("ENTITY_TYPE_ALIAS", "RELATIONSHIPS_LOOKUP_RESOURCE_EN", # Entries by which to filter
"FODDER_PRODUCTIVITY", "1861_ADJUSTED_VALUE")
fhd_socio <- fhd[CATEGORY %in% entries,][,.(ID,CATEGORY,ENTRY)] # Apply the filter, keeping only the ID and new cols
head(fhd_socio)
ID | CATEGORY | ENTRY |
---|---|---|
<chr> | <chr> | <chr> |
5FC9E27E7C39E36162AF5123 | 1861_ADJUSTED_VALUE | 55.6 |
5FC9E27E7C39E36162AF5123 | FODDER_PRODUCTIVITY | 6 |
5FC9E27E7C39E36162AF5123 | ENTITY_TYPE_ALIAS | bishop |
5FC9E27E7C39E36162AF5124 | 1861_ADJUSTED_VALUE | 28.5 |
5FC9E27E7C39E36162AF5124 | FODDER_PRODUCTIVITY | 7 |
5FC9E27E7C39E36162AF5124 | ENTITY_TYPE_ALIAS | bishop |
Now we can cast the rows into new columns, and "smush" the rows for each observation into a single row removing NAs in the process.
fhd_socio <- dcast(fhd_socio, ID+ENTRY~CATEGORY, value.var="ENTRY", # Cast the rows
fun.aggregate = function (x) paste(x,collapse = "; "))
fhd_socio <- setDT(fhd_socio)[order(ID), # And smush them
lapply(.SD, function(x) x[!is.na(x) & x != ""][1]),
by=ID]
head(fhd_socio)
ID | ENTRY | 1861_ADJUSTED_VALUE | ENTITY_TYPE_ALIAS | FODDER_PRODUCTIVITY | RELATIONSHIPS_LOOKUP_RESOURCE_EN |
---|---|---|---|---|---|
<chr> | <chr> | <chr> | <chr> | <chr> | <chr> |
5FC9E27E7C39E36162AF511B | 17.1 | 17.1 | bishop | 2 | outfield pasture |
5FC9E27E7C39E36162AF511C | 2 | 33.2 | bishop | 2 | outfield pasture |
5FC9E27E7C39E36162AF511D | 0.5 | 9.9 | bishop | 0.5 | NA |
5FC9E27E7C39E36162AF511E | 19.9 | 19.9 | bishop | 2 | outfield pasture |
5FC9E27E7C39E36162AF511F | 15.6 | 15.6 | bishop | 2 | NA |
5FC9E27E7C39E36162AF5120 | 18.5 | 18.5 | bishop | 4 | NA |
Note that a lot of the entires are "NA"---these farmsteads did not have additional access to other resources. We'll replace the NAs with "NOTHING", and drop any remaining NAs in other columns.
fhd_socio[is.na(RELATIONSHIPS_LOOKUP_RESOURCE_EN),
RELATIONSHIPS_LOOKUP_RESOURCE_EN := "NOTHING"]
fhd_socio <- na.omit(fhd_socio)
head(fhd_socio)
ID | ENTRY | 1861_ADJUSTED_VALUE | ENTITY_TYPE_ALIAS | FODDER_PRODUCTIVITY | RELATIONSHIPS_LOOKUP_RESOURCE_EN |
---|---|---|---|---|---|
<chr> | <chr> | <chr> | <chr> | <chr> | <chr> |
5FC9E27E7C39E36162AF511B | 17.1 | 17.1 | bishop | 2 | outfield pasture |
5FC9E27E7C39E36162AF511C | 2 | 33.2 | bishop | 2 | outfield pasture |
5FC9E27E7C39E36162AF511D | 0.5 | 9.9 | bishop | 0.5 | NOTHING |
5FC9E27E7C39E36162AF511E | 19.9 | 19.9 | bishop | 2 | outfield pasture |
5FC9E27E7C39E36162AF511F | 15.6 | 15.6 | bishop | 2 | NOTHING |
5FC9E27E7C39E36162AF5120 | 18.5 | 18.5 | bishop | 4 | NOTHING |
A small subset of farmstead had access to more than one pasture or more than one site for a single type of resource
unique(fhd_socio$RELATIONSHIPS_LOOKUP_RESOURCE_EN)
These will complicate our analyses later on. Since none of the sites appear to have direct access to more than one type of resource, we'll truncate the lists to only their first entry.
fhd_socio[, RELATIONSHIPS_LOOKUP_RESOURCE_EN :=
list(strsplit(RELATIONSHIPS_LOOKUP_RESOURCE_EN, "; "))] # Split any multi-resource entries
fhd_socio[, RELATIONSHIPS_LOOKUP_RESOURCE_EN :=
lapply(RELATIONSHIPS_LOOKUP_RESOURCE_EN, function(x) x[1])] # Keep only the first one
unique(fhd_socio$RELATIONSHIPS_LOOKUP_RESOURCE_EN)
Finally we'll convert the two numeric columns to numeric type using "as.numeric"
fhd_socio[, c("FODDER_PRODUCTIVITY","1861_ADJUSTED_VALUE") :=
lapply(.SD,as.numeric), .SDcols = c("FODDER_PRODUCTIVITY","1861_ADJUSTED_VALUE")]
fhd_socio <- na.omit(fhd_socio)
Warning message in lapply(.SD, as.numeric): “NAs introduced by coercion” Warning message in lapply(.SD, as.numeric): “NAs introduced by coercion”
We're now almost ready to perform dimensionality reduction. We have four input variables, two of them are numeric (Fodder productivity and adjusted valuation), and two of them are nominal. The appropriate method is Factor Analysis of Mixed Data, provided by the FactoMineR and factoextra libraries thorugh the FAMD function.
The function expects all numeric variables to be of numeric type, and nominal variables to be of factor type. Currently, RELATIONSHIPS_LOOKUP_RESOURCE_EN is a list class object given the truncating step we performed above. ENTITY_TYPE_ALIAS is a character class. We'll create a new data table with only the columns of interest, convert the list and characters to a factor, and perform the FAMD.
This overview of FAMD is written by the original author of both the method and R package, and provides detailed guidance as to how to interpret the output.
vars <- c(entries) # The entries variable already has stored the variables of interest
fhd_famd <- fhd_socio[,..vars] # Extract only the columns we want
fhd_famd[, "RELATIONSHIPS_LOOKUP_RESOURCE_EN" := # Convert list to character type
as.character(RELATIONSHIPS_LOOKUP_RESOURCE_EN)]
fhd_famd[, c("ENTITY_TYPE_ALIAS","RELATIONSHIPS_LOOKUP_RESOURCE_EN") :=
lapply(.SD,as.factor), # Convert character to factor
.SDcols = c("ENTITY_TYPE_ALIAS", "RELATIONSHIPS_LOOKUP_RESOURCE_EN")]
famd <- FAMD(fhd_famd,ncp=nrow(fhd_famd),graph=FALSE) # Perform the FAMD
famd
*The results are available in the following objects: name description 1 "$eig" "eigenvalues and inertia" 2 "$var" "Results for the variables" 3 "$ind" "results for the individuals" 4 "$quali.var" "Results for the qualitative variables" 5 "$quanti.var" "Results for the quantitative variables"
The first thing we'll look at is how much each principal dimension contributes to the total variance of the dataset. We can generally ignore dimensions that contain less than 5% of the variance
famd$eig
eigenvalue | percentage of variance | cumulative percentage of variance | |
---|---|---|---|
comp 1 | 1.7024016 | 9.457787 | 9.457787 |
comp 2 | 1.2870958 | 7.150532 | 16.608319 |
comp 3 | 1.1278996 | 6.266109 | 22.874427 |
comp 4 | 1.1010667 | 6.117037 | 28.991465 |
comp 5 | 1.0354254 | 5.752363 | 34.743828 |
comp 6 | 1.0277375 | 5.709653 | 40.453481 |
comp 7 | 1.0115212 | 5.619562 | 46.073043 |
comp 8 | 1.0000000 | 5.555556 | 51.628599 |
comp 9 | 1.0000000 | 5.555556 | 57.184154 |
comp 10 | 1.0000000 | 5.555556 | 62.739710 |
comp 11 | 1.0000000 | 5.555556 | 68.295265 |
comp 12 | 0.9750489 | 5.416938 | 73.712204 |
comp 13 | 0.9655096 | 5.363942 | 79.076146 |
comp 14 | 0.9486539 | 5.270300 | 84.346445 |
comp 15 | 0.8731255 | 4.850697 | 89.197142 |
comp 16 | 0.8370884 | 4.650491 | 93.847633 |
comp 17 | 0.7138361 | 3.965756 | 97.813389 |
comp 18 | 0.3935899 | 2.186611 | 100.000000 |
It looks like with the first 13 variables (all those at or above 5%) we can capture about three-fourths of the total variance.
Next we'll look at the percent contribution to each dimesnsion from each input variable. The higher the contribution, the more closely related they are.
famd$var$contrib
Dim.1 | Dim.2 | Dim.3 | Dim.4 | Dim.5 | Dim.6 | Dim.7 | Dim.8 | Dim.9 | Dim.10 | Dim.11 | Dim.12 | Dim.13 | Dim.14 | Dim.15 | Dim.16 | Dim.17 | Dim.18 | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
FODDER_PRODUCTIVITY | 41.384077 | 0.003288726 | 0.5341104 | 0.5747235 | 0.98273714 | 0.04494208 | 1.2019299 | 4.441518e-60 | 0.000000e+00 | 0.000000e+00 | 1.957389e-26 | 0.399701731 | 1.2197966 | 2.193599 | 1.5015851 | 3.128009 | 0.05739694 | 46.7741030 |
1861_ADJUSTED_VALUE | 42.878437 | 0.353733811 | 0.2533428 | 1.4147496 | 0.01074523 | 0.53488810 | 0.5280508 | 5.527263e-29 | 3.866343e-27 | 1.761603e-27 | 8.312826e-27 | 0.001642099 | 0.8357081 | 1.141222 | 0.1432517 | 1.924446 | 0.97197314 | 49.0078092 |
ENTITY_TYPE_ALIAS | 5.532352 | 49.785919828 | 45.1498956 | 49.1936918 | 49.31270922 | 47.06162588 | 1.5242762 | 2.851314e-26 | 4.434982e-26 | 1.658536e-26 | 9.895320e-27 | 42.278341235 | 43.9746267 | 23.575151 | 41.8028886 | 50.422267 | 49.52221900 | 0.8640357 |
RELATIONSHIPS_LOOKUP_RESOURCE_EN | 10.205134 | 49.857057635 | 54.0626512 | 48.8168350 | 49.69380841 | 52.35854394 | 96.7457431 | 1.000000e+02 | 1.000000e+02 | 1.000000e+02 | 1.000000e+02 | 57.320314935 | 53.9698686 | 73.090028 | 56.5522747 | 44.525277 | 49.44841092 | 3.3540522 |
We can plot these relationships for quantitative variables in a circle plot. Here this is for all combinations of the first three dimensions
fviz_famd_var(famd, "quanti.var", repel = TRUE,col.var = "black", axes=c(1,2))
fviz_famd_var(famd, "quanti.var", repel = TRUE,col.var = "black", axes=c(2,3))
fviz_famd_var(famd, "quanti.var", repel = TRUE,col.var = "black", axes=c(1,3))
For qualitative variables we can plot scatter plots
fviz_famd_var(famd, "quali.var", repel = TRUE,col.var = "black", axes=c(1,2))
fviz_famd_var(famd, "quali.var", repel = TRUE,col.var = "black", axes=c(2,3))
fviz_famd_var(famd, "quali.var", repel = TRUE,col.var = "black", axes=c(1,3))
To plot the Dimension scores themselves, let's create a new data.table that merges both the input and output values
famd_out <- as.data.table(famd$call$X)
setnames(famd_out,c("1861_ADJUSTED_VALUE","ENTITY_TYPE_ALIAS","RELATIONSHIPS_LOOKUP_RESOURCE_EN"),
c("VALUE","OWNER","RIGHTS_TO"))
famd_out[,colnames(famd$ind$coord) := as.data.table(..famd$ind$coord)]
And we plot the first three dimensions in a 3D scatterplot using ggplot2 and plotly
p1 <- plot_ly(x = famd_out$Dim.1, y = famd_out$Dim.2, z = famd_out$Dim.3,
type = "scatter3d",
mode = "markers",
color = famd_out$OWNER,
text = paste("RIGHTS TO:",famd_out$RIGHTS_TO))
p1
Now that we know a bit more about the Jardabok data and its distribution across different dimensions, we can compare it to entries in the Saga sites. Unfortunately they don't have any entries/variables in common according to the observations in dataARC; however they have all been mapped to concepts, of which a number are shared between the two.
The next two cells are large blocks of code, but each sub-section does the same thing for three types of concepts. Concepts that are directly linked are "matched" concepts, and are listed under the "CONCEPT" column. Concpets two linkages away are "RELATED", and "CONTEXT" are thre linkages away. The concepts for each type for each observation are stored in strings, with each individual context separated by a colon.
For each type, the script
fhd_byconcept <- fhd[, .(CONCEPT = unlist(tstrsplit(CONCEPT,":"))), by=c("ID")]
fhd_byconcept <- fhd_byconcept[,.(CONCEPT = unique(CONCEPT)),by=ID][, WEIGHT := 3]
fhd_concepts <- fhd_byconcept
fhd_concepts[,CONCEPT := ..concepts$NAME[match(CONCEPT,..concepts$HASH)]]
fhd_byrelated <- fhd[, .(RELATED = unlist(tstrsplit(RELATED,":"))), by=c("ID")]
fhd_byrelated <- fhd_byrelated[,.(RELATED = unique(RELATED)),by=ID][,WEIGHT := 2]
fhd_related <- fhd_byrelated
fhd_related[,RELATED := ..concepts$NAME[match(RELATED,..concepts$HASH)]]
fhd_bycontext <- fhd[, .(CONTEXT = unlist(tstrsplit(CONTEXT,":"))), by=c("ID")]
fhd_bycontext <- fhd_bycontext[,.(CONTEXT = unique(CONTEXT)),by=ID][,WEIGHT := 1]
fhd_context <- fhd_bycontext
fhd_context[,CONTEXT := ..concepts$NAME[match(CONTEXT,..concepts$HASH)]]
head(fhd_concepts)
ID | CONCEPT | WEIGHT |
---|---|---|
<chr> | <chr> | <dbl> |
5FC9E27E7C39E36162AF5123 | agricultural landscape | 3 |
5FC9E27E7C39E36162AF5123 | bishops church | 3 |
5FC9E27E7C39E36162AF5123 | built environment | 3 |
5FC9E27E7C39E36162AF5123 | church farm | 3 |
5FC9E27E7C39E36162AF5123 | cultivation farming | 3 |
5FC9E27E7C39E36162AF5123 | domestic animal | 3 |
saga_byconcept <- saga[, .(CONCEPT = unlist(tstrsplit(CONCEPT,":"))), by=c("ID")]
saga_byconcept <- saga_byconcept[,.(CONCEPT = unique(CONCEPT)),by=ID][, WEIGHT := 3]
saga_concepts <- saga_byconcept
saga_concepts[,CONCEPT := ..concepts$NAME[match(CONCEPT,..concepts$HASH)]]
saga_byrelated <- saga[, .(RELATED = unlist(tstrsplit(RELATED,":"))), by=c("ID")]
saga_byrelated <- saga_byrelated[,.(RELATED = unique(RELATED)),by=ID][,WEIGHT := 2]
saga_related <- saga_byrelated
saga_related[,RELATED := ..concepts$NAME[match(RELATED,..concepts$HASH)]]
saga_bycontext <- saga[, .(CONTEXT = unlist(tstrsplit(CONTEXT,":"))), by=c("ID")]
saga_bycontext <- saga_bycontext[,.(CONTEXT = unique(CONTEXT)),by=ID][,WEIGHT := 1]
saga_context <- saga_bycontext
saga_context[,CONTEXT := ..concepts$NAME[match(CONTEXT,..concepts$HASH)]]
head(saga_concepts)
ID | CONCEPT | WEIGHT |
---|---|---|
<chr> | <chr> | <dbl> |
5FC9E2227C39E36162AF2098 | agricultural landscape | 3 |
5FC9E2227C39E36162AF2098 | animal | 3 |
5FC9E2227C39E36162AF2098 | animal husbandry | 3 |
5FC9E2227C39E36162AF2098 | barn | 3 |
5FC9E2227C39E36162AF2098 | butchery | 3 |
5FC9E2227C39E36162AF2098 | byre | 3 |
Again, the next two cells are large blocks of code that do the same thing for the Sagas and Jardabok for each type of concept.
n = length(unique(fhd$ID))
fhd_concepts <- fhd_concepts[,.N,by=CONCEPT][N != n]
fhd_related <- fhd_related[,.N, by=RELATED][N != n]
setnames(fhd_byrelated,"RELATED","CONCEPT")
fhd_context <- fhd_context[,.N, by=CONTEXT][N != n]
setnames(fhd_bycontext,"CONTEXT","CONCEPT")
fhd_byconcept <- do.call(rbind,list(fhd_byconcept,fhd_byrelated,fhd_bycontext))
fhd_byconcept[,WEIGHT := sum(WEIGHT),by=.(ID,CONCEPT)]
head(fhd_byconcept)
ID | CONCEPT | WEIGHT |
---|---|---|
<chr> | <chr> | <dbl> |
5FC9E27E7C39E36162AF5123 | agricultural landscape | 3 |
5FC9E27E7C39E36162AF5123 | bishops church | 3 |
5FC9E27E7C39E36162AF5123 | built environment | 3 |
5FC9E27E7C39E36162AF5123 | church farm | 3 |
5FC9E27E7C39E36162AF5123 | cultivation farming | 3 |
5FC9E27E7C39E36162AF5123 | domestic animal | 3 |
n = length(unique(saga$ID))
saga_concepts <- saga_concepts[,.N,by=CONCEPT][N != n]
saga_related <- saga_related[,.N, by=RELATED][N != n]
setnames(saga_byrelated,"RELATED","CONCEPT")
saga_context <- saga_context[,.N, by=CONTEXT][N != n]
setnames(saga_bycontext,"CONTEXT","CONCEPT")
saga_byconcept <- do.call(rbind,list(saga_byconcept,saga_byrelated,saga_bycontext))
saga_byconcept[,WEIGHT := sum(WEIGHT),by=.(ID,CONCEPT)]
head(saga_byconcept)
ID | CONCEPT | WEIGHT |
---|---|---|
<chr> | <chr> | <dbl> |
5FC9E2227C39E36162AF2098 | agricultural landscape | 3 |
5FC9E2227C39E36162AF2098 | animal | 3 |
5FC9E2227C39E36162AF2098 | animal husbandry | 3 |
5FC9E2227C39E36162AF2098 | barn | 3 |
5FC9E2227C39E36162AF2098 | butchery | 3 |
5FC9E2227C39E36162AF2098 | byre | 3 |
Now we need to get a list of the concepts we're interested in. These would be the ones that are shared in common between the Jardabok and Sagas databases
var_list <- unique(saga_byconcept$CONCEPT[saga_byconcept$CONCEPT %in% fhd_byconcept$CONCEPT])
var_list <- na.omit(var_list)
as.list(var_list)
Each unique concept and observation has its own row. We need to cast these so that each concept has its own column, with the entry being the weights and the rows representing each observation.
fhd_byconcept <- fhd_byconcept[CONCEPT %in% var_list] # Get only the concepts of interest
fhd_byconcept <- dcast(fhd_byconcept, ID+WEIGHT~CONCEPT, value.var="WEIGHT",
fun.aggregate = mean) # Cast the concepts into their own rows
fhd_byconcept <- setDT(fhd_byconcept)[order(ID),
lapply(.SD, function(x) x[!is.na(x) & x != ""][1]),
by=ID] # Smush them so that there's only one row per observation
setnafill(fhd_byconcept,fill=0,cols=var_list) # If a concept doesn't apply, give it weight of 1
fhd_byconcept[, SUM := rowSums(.SD),.SDcols=var_list][, c("WEIGHT","SUM") := NULL]
head(fhd_byconcept)
ID | agricultural landscape | beach | coastal ocean | cultivation farming | exchange | exploration | farm | gathering | humans | managed landscape area | power | resources | sea | whale dolphin |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
<chr> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> |
5FC9E27E7C39E36162AF511B | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 |
5FC9E27E7C39E36162AF511C | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 |
5FC9E27E7C39E36162AF511D | 0 | 0 | 0 | 0 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 |
5FC9E27E7C39E36162AF511E | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 |
5FC9E27E7C39E36162AF511F | 0 | 0 | 0 | 0 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 |
5FC9E27E7C39E36162AF5120 | 0 | 0 | 0 | 0 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 |
Let's reincorporate the concepts into a data.table with the resource table we'll predict later on. We'll save it to a new fhd_rf variable that we'll use for the Random Forest classification.
name <- c("RELATIONSHIPS_LOOKUP_RESOURCE_EN")
fhd_rf <- fhd[CATEGORY %in% name, .(ID,X,Y,ENTRY)]
fhd_rf <- fhd_byconcept[fhd_rf,on="ID"]
fhd_rf[,ENTRY := as.factor(ENTRY)]
fhd_rf
ID | agricultural landscape | beach | coastal ocean | cultivation farming | exchange | exploration | farm | gathering | humans | managed landscape area | power | resources | sea | whale dolphin | X | Y | ENTRY |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
<chr> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <fct> |
5FC9E27E7C39E36162AF5134 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13921103 | -2922671 | driftwood |
5FC9E27E7C39E36162AF5134 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13921103 | -2922671 | outfield pasture |
5FC9E27E7C39E36162AF5134 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13921103 | -2922671 | woodland |
5FC9E27E7C39E36162AF5136 | 3 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13914266 | -2921322 | outfield pasture |
5FC9E27E7C39E36162AF5137 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13927346 | -2921497 | outfield pasture |
5FC9E27E7C39E36162AF5137 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13927346 | -2921497 | pasture |
5FC9E27E7C39E36162AF5137 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13927346 | -2921497 | pasture |
5FC9E27E7C39E36162AF5137 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13927346 | -2921497 | woodland |
5FC9E27E7C39E36162AF5139 | 3 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13909886 | -2920307 | outfield pasture |
5FC9E27E7C39E36162AF513B | 3 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13919323 | -2923124 | outfield pasture |
5FC9E27E7C39E36162AF513C | 3 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13922834 | -2921007 | outfield pasture |
5FC9E27E7C39E36162AF513C | 3 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13922834 | -2921007 | trout |
5FC9E27E7C39E36162AF513F | 3 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13888180 | -2913645 | outfield pasture |
5FC9E27E7C39E36162AF5146 | 3 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13903372 | -2917264 | outfield pasture |
5FC9E27E7C39E36162AF51B3 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 13811594 | -2731003 | beached whale |
5FC9E27E7C39E36162AF51B3 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 13811594 | -2731003 | beached whale |
5FC9E27E7C39E36162AF51B3 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 13811594 | -2731003 | driftwood |
5FC9E27E7C39E36162AF51B3 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 13811594 | -2731003 | driftwood |
5FC9E27E7C39E36162AF542D | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13816409 | -2757454 | pasture |
5FC9E27E7C39E36162AF542D | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13816409 | -2757454 | woodland |
5FC9E27E7C39E36162AF5432 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13818294 | -2766260 | woodland |
5FC9E27E7C39E36162AF54C0 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 14552905 | -3376286 | beached whale |
5FC9E27E7C39E36162AF54C0 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 14552905 | -3376286 | beached whale |
5FC9E27E7C39E36162AF54C0 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 14552905 | -3376286 | beached whale |
5FC9E27E7C39E36162AF54C0 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 14552905 | -3376286 | beached whale |
5FC9E27E7C39E36162AF54C0 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 14552905 | -3376286 | driftwood |
5FC9E27E7C39E36162AF54C0 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 14552905 | -3376286 | driftwood |
5FC9E27E7C39E36162AF54C0 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 14552905 | -3376286 | driftwood |
5FC9E27E7C39E36162AF54C0 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 14552905 | -3376286 | driftwood |
5FC9E27E7C39E36162AF54C0 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 14552905 | -3376286 | driftwood |
⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ |
5FC9E27F7C39E36162AF5EB0 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14154179 | -3023916 | shieling place |
5FC9E27F7C39E36162AF5EB1 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14118058 | -3021944 | hay |
5FC9E27F7C39E36162AF5EB6 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14157458 | -3024670 | hay |
5FC9E27F7C39E36162AF5EB9 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14150803 | -3022316 | ship place |
5FC9E27F7C39E36162AF5EBA | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14156580 | -3018872 | pasture |
5FC9E27F7C39E36162AF5EC2 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14072307 | -3012047 | pasture |
5FC9E27F7C39E36162AF5EC8 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14083534 | -3031668 | pasture |
5FC9E27F7C39E36162AF5ECB | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14068034 | -3004768 | pasture |
5FC9E27F7C39E36162AF5ED6 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14101932 | -3030110 | hay |
5FC9E27F7C39E36162AF5EE2 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14654545 | -3582477 | pasture |
5FC9E27F7C39E36162AF5EE5 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14638403 | -3572114 | ship place |
5FC9E27F7C39E36162AF5F0D | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14099572 | -3136776 | pasture |
5FC9E27F7C39E36162AF5F13 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14094606 | -3134687 | outfield pasture |
5FC9E27F7C39E36162AF5F14 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14087044 | -3123400 | hay |
5FC9E27F7C39E36162AF5F14 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14087044 | -3123400 | outfield pasture |
5FC9E27F7C39E36162AF5F16 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14070207 | -3139797 | pasture |
5FC9E27F7C39E36162AF5F17 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14089921 | -3140868 | driftwood |
5FC9E27F7C39E36162AF5F17 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14089921 | -3140868 | outfield pasture |
5FC9E27F7C39E36162AF5F17 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14089921 | -3140868 | shieling place |
5FC9E27F7C39E36162AF5F1A | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14084666 | -3106467 | outfield pasture |
5FC9E27F7C39E36162AF5F30 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 13912373 | -2746480 | hay |
5FC9E27F7C39E36162AF5F30 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 13912373 | -2746480 | pasture |
5FC9E27E7C39E36162AF5299 | 0 | 0 | 0 | 0 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 13972406 | -2996031 | pasture |
5FC9E27E7C39E36162AF52BA | 0 | 0 | 0 | 0 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14018549 | -3013242 | pasture |
5FC9E27E7C39E36162AF52BA | 0 | 0 | 0 | 0 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14018549 | -3013242 | peat |
5FC9E27F7C39E36162AF5BD4 | 0 | 0 | 0 | 0 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14020276 | -2938536 | pasture |
5FC9E27F7C39E36162AF5BD4 | 0 | 0 | 0 | 0 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14020276 | -2938536 | pasture |
5FC9E27F7C39E36162AF5BD4 | 0 | 0 | 0 | 0 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14020276 | -2938536 | pasture |
5FC9E27F7C39E36162AF5BD4 | 0 | 0 | 0 | 0 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14020276 | -2938536 | pasture |
5FC9E27F7C39E36162AF5F0C | 0 | 0 | 0 | 0 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14095349 | -3121047 | pasture |
It's wise to make sure that we have enough observations for all of the categories we'll predict, otherwise the classifier will do a poor job. We should also change the class to "factor" from character so that RandomForest knows it's nominal.
count(as.character(fhd_rf$ENTRY))
fhd_rf[,ENTRY := unlist(ENTRY)]
fhd_rf <- na.omit(fhd_rf)
x | freq |
---|---|
<fct> | <int> |
beached whale | 168 |
bird hunt | 2 |
driftwood | 186 |
dulse | 16 |
egg | 6 |
hay | 98 |
lamb rearing | 10 |
outfield pasture | 111 |
pasture | 187 |
peat | 19 |
seal | 2 |
shieling place | 59 |
ship place | 43 |
stone | 1 |
toll | 1 |
trout | 5 |
turf | 26 |
twigs | 14 |
use of unoccupied farm | 14 |
woodland | 87 |
Since most of the resource types have very few observations, it would be a good idea to combine similar resources into resource types/strategies. The "Strategies.csv" file contains a lookup table we could use. We'll import it, and assign a new column based on the relate.
strategies <- read.csv('Strategies.csv')
fhd_rf[,ENTRY := toupper(ENTRY)]
fhd_rf <- fhd_rf[strategies,on="ENTRY"]
fhd_rf[, STRATEGY := as.factor(STRATEGY)]
fhd_rf <- na.omit(fhd_rf)
head(fhd_rf[,.(ID,ENTRY,STRATEGY)])
ID | ENTRY | STRATEGY |
---|---|---|
<chr> | <chr> | <fct> |
5FC9E27E7C39E36162AF5134 | OUTFIELD PASTURE | PASTURE |
5FC9E27E7C39E36162AF5136 | OUTFIELD PASTURE | PASTURE |
5FC9E27E7C39E36162AF5137 | OUTFIELD PASTURE | PASTURE |
5FC9E27E7C39E36162AF5139 | OUTFIELD PASTURE | PASTURE |
5FC9E27E7C39E36162AF513B | OUTFIELD PASTURE | PASTURE |
5FC9E27E7C39E36162AF513C | OUTFIELD PASTURE | PASTURE |
Now we need to split our data into training datasets and testing datasets. We first pick random integers representing 10% of all the numbers between 1 and the number of observations. We subset all the observations with indexes matching those randomly-chosen integers into a "test" dataset, and all others into a "train" dataset
test <- sample(1:nrow(fhd_rf), nrow(fhd_rf) %/% 10, replace=F)
train <- fhd_rf[!test,]
test <- fhd_rf[test,]
train
ID | agricultural landscape | beach | coastal ocean | cultivation farming | exchange | exploration | farm | gathering | humans | managed landscape area | power | resources | sea | whale dolphin | X | Y | ENTRY | FID | STRATEGY |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
<chr> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <chr> | <int> | <fct> |
5FC9E27E7C39E36162AF5134 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13921103 | -2922671 | OUTFIELD PASTURE | 1 | PASTURE |
5FC9E27E7C39E36162AF5136 | 3 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13914266 | -2921322 | OUTFIELD PASTURE | 1 | PASTURE |
5FC9E27E7C39E36162AF5137 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13927346 | -2921497 | OUTFIELD PASTURE | 1 | PASTURE |
5FC9E27E7C39E36162AF5139 | 3 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13909886 | -2920307 | OUTFIELD PASTURE | 1 | PASTURE |
5FC9E27E7C39E36162AF513B | 3 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13919323 | -2923124 | OUTFIELD PASTURE | 1 | PASTURE |
5FC9E27E7C39E36162AF513C | 3 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13922834 | -2921007 | OUTFIELD PASTURE | 1 | PASTURE |
5FC9E27E7C39E36162AF513F | 3 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13888180 | -2913645 | OUTFIELD PASTURE | 1 | PASTURE |
5FC9E27E7C39E36162AF5146 | 3 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13903372 | -2917264 | OUTFIELD PASTURE | 1 | PASTURE |
5FC9E27E7C39E36162AF5570 | 3 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13691201 | -2611398 | OUTFIELD PASTURE | 1 | PASTURE |
5FC9E27E7C39E36162AF5598 | 3 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13715720 | -2598655 | OUTFIELD PASTURE | 1 | PASTURE |
5FC9E27E7C39E36162AF5598 | 3 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13715720 | -2598655 | OUTFIELD PASTURE | 1 | PASTURE |
5FC9E27E7C39E36162AF55E4 | 3 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13926750 | -2852909 | OUTFIELD PASTURE | 1 | PASTURE |
5FC9E27E7C39E36162AF567D | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13762784 | -2750176 | OUTFIELD PASTURE | 1 | PASTURE |
5FC9E27F7C39E36162AF5C17 | 3 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13635072 | -2439813 | OUTFIELD PASTURE | 1 | PASTURE |
5FC9E27F7C39E36162AF5D91 | 3 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13886622 | -2784247 | OUTFIELD PASTURE | 1 | PASTURE |
5FC9E27F7C39E36162AF5A0D | 0 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 13596991 | -2420983 | OUTFIELD PASTURE | 1 | PASTURE |
5FC9E27F7C39E36162AF5C14 | 0 | 3 | 0 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13515497 | -2428548 | OUTFIELD PASTURE | 1 | PASTURE |
5FC9E27E7C39E36162AF511B | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 13829221 | -2883797 | OUTFIELD PASTURE | 1 | PASTURE |
5FC9E27E7C39E36162AF511E | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 13834856 | -2887327 | OUTFIELD PASTURE | 1 | PASTURE |
5FC9E27E7C39E36162AF5131 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 13926179 | -2915272 | OUTFIELD PASTURE | 1 | PASTURE |
5FC9E27E7C39E36162AF5132 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 13849797 | -2897685 | OUTFIELD PASTURE | 1 | PASTURE |
5FC9E27E7C39E36162AF513A | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 13920872 | -2919063 | OUTFIELD PASTURE | 1 | PASTURE |
5FC9E27E7C39E36162AF5141 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 13874191 | -2910306 | OUTFIELD PASTURE | 1 | PASTURE |
5FC9E27E7C39E36162AF5143 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 13906166 | -2919720 | OUTFIELD PASTURE | 1 | PASTURE |
5FC9E27E7C39E36162AF55B6 | 0 | 0 | 0 | 0 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14001497 | -2886948 | OUTFIELD PASTURE | 1 | PASTURE |
5FC9E27E7C39E36162AF55D7 | 0 | 0 | 0 | 0 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 13997977 | -2888052 | OUTFIELD PASTURE | 1 | PASTURE |
5FC9E27E7C39E36162AF55E5 | 0 | 0 | 0 | 0 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 13945779 | -2876377 | OUTFIELD PASTURE | 1 | PASTURE |
5FC9E27E7C39E36162AF55E6 | 0 | 0 | 0 | 0 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 13928040 | -2855779 | OUTFIELD PASTURE | 1 | PASTURE |
5FC9E27E7C39E36162AF55E7 | 0 | 0 | 0 | 0 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 13949144 | -2882869 | OUTFIELD PASTURE | 1 | PASTURE |
5FC9E27E7C39E36162AF55E9 | 0 | 0 | 0 | 0 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 13922621 | -2868979 | OUTFIELD PASTURE | 1 | PASTURE |
⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ |
5FC9E27F7C39E36162AF5980 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 14604474 | -3533360 | DULSE | 14 | MARINE |
5FC9E27F7C39E36162AF5987 | 0 | 3 | 0 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 14618637 | -3541287 | DULSE | 14 | MARINE |
5FC9E27E7C39E36162AF533E | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14082128 | -3038293 | DULSE | 14 | MARINE |
5FC9E27F7C39E36162AF5D15 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 13908495 | -3406426 | DULSE | 14 | MARINE |
5FC9E27F7C39E36162AF5D1D | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 13950748 | -3436311 | DULSE | 14 | MARINE |
5FC9E27E7C39E36162AF533F | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14083659 | -3035617 | DULSE | 14 | MARINE |
5FC9E27E7C39E36162AF541C | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14258186 | -3298538 | DULSE | 14 | MARINE |
5FC9E27F7C39E36162AF5D19 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 13926057 | -3419837 | DULSE | 14 | MARINE |
5FC9E27F7C39E36162AF5D21 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 13925246 | -3418079 | DULSE | 14 | MARINE |
5FC9E27F7C39E36162AF5D25 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 13926677 | -3422624 | DULSE | 14 | MARINE |
5FC9E27F7C39E36162AF5D28 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 13918598 | -3412402 | DULSE | 14 | MARINE |
5FC9E27F7C39E36162AF5E03 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14076978 | -3077160 | DULSE | 14 | MARINE |
5FC9E27F7C39E36162AF5C16 | 3 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 3 | 3 | 0 | 0 | 0 | 13605585 | -2430025 | EGG | 15 | OTHER |
5FC9E27F7C39E36162AF5B0C | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 0 | 0 | 0 | 3 | 3 | 13472274 | -2240856 | EGG | 15 | OTHER |
5FC9E27E7C39E36162AF544B | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 0 | 0 | 13811591 | -2738562 | EGG | 15 | OTHER |
5FC9E27E7C39E36162AF5409 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 13901120 | -3395328 | EGG | 15 | OTHER |
5FC9E27E7C39E36162AF5409 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 13901120 | -3395328 | EGG | 15 | OTHER |
5FC9E27E7C39E36162AF5701 | 0 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 0 | 0 | 0 | 3 | 3 | 13725322 | -2561161 | TOLL | 17 | OTHER |
5FC9E27F7C39E36162AF5DB6 | 3 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 3 | 0 | 0 | 14063979 | -3082554 | BIRD HUNT | 18 | OTHER |
5FC9E27F7C39E36162AF5A68 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14616078 | -3676046 | BIRD HUNT | 18 | OTHER |
5FC9E27F7C39E36162AF5B0C | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 0 | 0 | 0 | 3 | 3 | 13472274 | -2240856 | LAMB REARING | 19 | OTHER |
5FC9E27F7C39E36162AF5B0C | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 0 | 0 | 0 | 3 | 3 | 13472274 | -2240856 | LAMB REARING | 19 | OTHER |
5FC9E27F7C39E36162AF5B0C | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 0 | 0 | 0 | 3 | 3 | 13472274 | -2240856 | LAMB REARING | 19 | OTHER |
5FC9E27F7C39E36162AF5B0C | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 0 | 0 | 0 | 3 | 3 | 13472274 | -2240856 | LAMB REARING | 19 | OTHER |
5FC9E27F7C39E36162AF5B0C | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 0 | 0 | 0 | 3 | 3 | 13472274 | -2240856 | LAMB REARING | 19 | OTHER |
5FC9E27F7C39E36162AF5B0C | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 0 | 0 | 0 | 3 | 3 | 13472274 | -2240856 | LAMB REARING | 19 | OTHER |
5FC9E27F7C39E36162AF5B0C | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 0 | 0 | 0 | 3 | 3 | 13472274 | -2240856 | LAMB REARING | 19 | OTHER |
5FC9E27F7C39E36162AF5B0C | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 0 | 0 | 0 | 3 | 3 | 13472274 | -2240856 | LAMB REARING | 19 | OTHER |
5FC9E27F7C39E36162AF5B0C | 3 | 3 | 3 | 3 | 0 | 3 | 3 | 3 | 3 | 0 | 0 | 0 | 3 | 3 | 13472274 | -2240856 | LAMB REARING | 19 | OTHER |
5FC9E27F7C39E36162AF5E03 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 14076978 | -3077160 | SEAL | 20 | MARINE |
We can finally run the random forest model. x and y represent the independent and independent training variables. Our random forest will be built with 1000 random trees. We'll keep the importances so we can see what concepts were good discriminants, and we'll keep the forest to use it to predict resources for saga sites.
rf <- randomForest(x = train[,..var_list], y= train$STRATEGY,
xtest = test[,..var_list], ytest = test$STRATEGY,
ntree = 1000, importance = TRUE, keep.forest = T)
rf$importance
MARINE | MATERIAL | OTHER | PASTURE | MeanDecreaseAccuracy | MeanDecreaseGini | |
---|---|---|---|---|---|---|
agricultural landscape | 9.018492e-03 | -0.0028879143 | -0.0001523810 | 1.445118e-02 | 0.0096742658 | 11.4736758 |
cultivation farming | 8.650616e-04 | -0.0001595834 | 0.0000000000 | 3.545572e-04 | 0.0004773348 | 1.4281818 |
farm | 0.000000e+00 | 0.0000000000 | 0.0000000000 | 0.000000e+00 | 0.0000000000 | 0.0000000 |
managed landscape area | -4.468455e-04 | 0.0454444274 | -0.0011452381 | 2.775440e-02 | 0.0187345494 | 10.0114129 |
power | 2.847938e-05 | 0.0486704548 | -0.0006095238 | 2.520423e-02 | 0.0183564836 | 9.5563577 |
beach | 4.863067e-02 | 0.0662374358 | -0.0007595238 | 1.170235e-01 | 0.0814336140 | 33.7430485 |
coastal ocean | 1.008508e-01 | 0.0162788097 | 0.0002500000 | 6.396831e-02 | 0.0700266139 | 41.4928081 |
exchange | -1.328271e-03 | 0.1294378239 | -0.0005194805 | 3.309640e-02 | 0.0330589470 | 18.7377224 |
exploration | 0.000000e+00 | 0.0000000000 | 0.0000000000 | 0.000000e+00 | 0.0000000000 | 0.0000000 |
humans | 0.000000e+00 | 0.0000000000 | 0.0000000000 | 0.000000e+00 | 0.0000000000 | 0.0000000 |
resources | 5.769957e-05 | -0.0009480587 | 0.0002500000 | 1.041175e-05 | -0.0001015844 | 0.7086058 |
sea | 9.624094e-02 | 0.0166959548 | -0.0015285714 | 6.099945e-02 | 0.0669448760 | 39.7382098 |
whale dolphin | 9.726281e-02 | 0.0157730048 | -0.0005714286 | 6.422385e-02 | 0.0686336933 | 39.9850896 |
gathering | 9.808572e-02 | 0.0161508074 | -0.0014416667 | 6.208799e-02 | 0.0682484842 | 40.3362208 |
The first four columns tell you how important a variable (concept) was when deciding whether or not to classify a given observation under a particular resource strategy. Te last two are measure of how important the variables are for the whole model. Generally, the Mean Decrease in Intra-group Gini is more reliable. Bear in mind, however, that Random Forests make for great predictors but terrible descriptors, so none of these should be interpreted in a same way as a coefficient (relationship strength) in a regression. No causal or direct relationship is implied.
We can look at the confusion matrix to see how many false-positives and false-negatives were found in the test dataset. Since the number of observations is different for each target resource strategy, we have to normalize each row so that it tells us the percent false positive and percent false negative.
conf <- as.data.table(rf$conf) # Gets confusion matrix
classes <- names(conf)[1:(length(conf)-1)] # Gets strategy names
conf[, N := rowSums(.SD),.SDcols = classes] # Gets the total number of test observations
conf[, (classes) := lapply(.SD, function(x) x / N * 100), .SDcols = classes] # Normalizes
conf <- as.matrix(conf[,..classes]) # Converts from data.table to matrix
rownames(conf) <- classes # re-applies strategy names
conf <- melt(conf) # Converts from matrix to i,j list
names(conf) <- c("ACTUAL","PREDICTED","PERCENT")
p2 <- ggplot(conf,aes(PREDICTED, ACTUAL)) + geom_tile(aes(fill=PERCENT)) +
theme(axis.text.x = element_text(angle=90, vjust = 0.5, hjust = 1)) +
scale_fill_gradientn(colors = c("navy","blanchedalmond","red4"))
ggplotly(p2)
Warning message in melt(conf): “The melt generic in data.table has been passed a matrix and will attempt to redirect to the relevant reshape2 method; please note that reshape2 is deprecated, and this redirection is now deprecated as well. To continue using melt methods from reshape2 while both libraries are attached, e.g. melt.list, you can prepend the namespace like reshape2::melt(conf). In the next version, this warning will become an error.”
We re-perform the casting operation on the sagas dataset so that we can pass it to the randomForst model we generated
saga_byconcept <- saga_byconcept[CONCEPT %in% var_list] # Get concepts of interest
saga_byconcept <- dcast(saga_byconcept, ID+WEIGHT~CONCEPT, value.var="WEIGHT",
fun.aggregate = mean) # Cast concepts into their own column
saga_byconcept <- setDT(saga_byconcept)[order(ID),
lapply(.SD, function(x) x[!is.na(x) & x != ""][1]),
by=ID] # Smush them into one row per observation
setnafill(saga_byconcept,fill=0,cols=var_list[var_list %in% names(saga_byconcept)])
saga_rf <- saga[,lapply(.SD,mean),by=ID,.SDcols=c("X","Y")]
saga_rf <- saga_byconcept[saga_rf,on="ID"]
saga_rf <- na.omit(saga_rf)
head(saga_rf)
ID | WEIGHT | agricultural landscape | beach | coastal ocean | cultivation farming | exchange | exploration | farm | gathering | humans | managed landscape area | power | resources | sea | whale dolphin | X | Y |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
<chr> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> |
5FC9E2227C39E36162AF2098 | 3 | 3 | 0 | 0 | 3 | 0 | 0 | 3 | 0 | 0 | 3 | 3 | 0 | 0 | 0 | 13711383 | -2648585 |
5FC9E2227C39E36162AF2099 | 3 | 3 | 0 | 0 | 3 | 0 | 0 | 3 | 0 | 0 | 3 | 3 | 0 | 0 | 0 | 13703908 | -2592639 |
5FC9E2227C39E36162AF209B | 3 | 3 | 0 | 0 | 3 | 0 | 0 | 3 | 0 | 0 | 3 | 3 | 0 | 0 | 0 | 13610339 | -2552051 |
5FC9E2227C39E36162AF209C | 3 | 3 | 0 | 0 | 3 | 0 | 0 | 3 | 0 | 0 | 3 | 3 | 0 | 0 | 0 | 13709753 | -2570264 |
5FC9E2227C39E36162AF209D | 3 | 3 | 0 | 0 | 3 | 0 | 0 | 3 | 0 | 0 | 3 | 3 | 0 | 0 | 0 | 13677819 | -2607640 |
5FC9E2227C39E36162AF209E | 3 | 3 | 0 | 0 | 3 | 0 | 0 | 3 | 0 | 0 | 3 | 3 | 0 | 0 | 0 | 13722756 | -2584671 |
Now all that's left in terms of analysis is to predict the resources for the saga sites
saga_rf$Predictions <- predict(rf,saga_rf[,1:(length(saga_rf))]) # Make predictions
saga_rf <- cbind(saga_rf,predict(rf,saga_rf[,1:(length(saga_rf)-1)], type='prob')) # Add to data.table
head(saga_rf[,.(ID,MARINE,MATERIAL,OTHER,PASTURE)])
tail(saga_rf[,.(ID,MARINE,MATERIAL,OTHER,PASTURE)])
ID | MARINE | MATERIAL | OTHER | PASTURE |
---|---|---|---|---|
<chr> | <dbl> | <dbl> | <dbl> | <dbl> |
5FC9E2227C39E36162AF2098 | 0.023 | 0.093 | 0 | 0.884 |
5FC9E2227C39E36162AF2099 | 0.023 | 0.093 | 0 | 0.884 |
5FC9E2227C39E36162AF209B | 0.023 | 0.093 | 0 | 0.884 |
5FC9E2227C39E36162AF209C | 0.023 | 0.093 | 0 | 0.884 |
5FC9E2227C39E36162AF209D | 0.023 | 0.093 | 0 | 0.884 |
5FC9E2227C39E36162AF209E | 0.023 | 0.093 | 0 | 0.884 |
ID | MARINE | MATERIAL | OTHER | PASTURE |
---|---|---|---|---|
<chr> | <dbl> | <dbl> | <dbl> | <dbl> |
5FC9E2237C39E36162AF422D | 0.252 | 0.484 | 0.021 | 0.243 |
5FC9E2237C39E36162AF4259 | 0.252 | 0.484 | 0.021 | 0.243 |
5FC9E2237C39E36162AF426A | 0.252 | 0.484 | 0.021 | 0.243 |
5FC9E2237C39E36162AF426E | 0.252 | 0.484 | 0.021 | 0.243 |
5FC9E2237C39E36162AF4270 | 0.252 | 0.484 | 0.021 | 0.243 |
5FC9E2237C39E36162AF428B | 0.252 | 0.484 | 0.021 | 0.243 |
The columns give the percentage likelihood that a saga would belong to that class given the way the concepts were mapped IF AND ONLY IF those are the only four possible classes.
To be able to refer back to the original sagas and see if the predictions were OK or not, we can consult the "SUMMARY" entry in the dataARC data.
entries = c("SAGANAME","CHAPTER") # Set the query
saga_refs <- saga[CATEGORY %in% entries, .(ID, CATEGORY, ENTRY, X,Y)] # Filter by Entry
saga_refs <- dcast(saga_refs, ID+ENTRY~CATEGORY, value.var="ENTRY", # Cast into columns
fun.aggregate = function (x) paste(x,collapse = "; "))
saga_refs <- setDT(saga_refs)[order(ID), # Smush into one row
lapply(.SD, function(x) x[!is.na(x) & x != ""][1]),
by=ID]
head(saga_refs)
ID | ENTRY | CHAPTER | SAGANAME |
---|---|---|---|
<chr> | <chr> | <chr> | <chr> |
5FC9E2227C39E36162AF2098 | 1. kafli | 1. kafli | Ljósvetninga saga |
5FC9E2227C39E36162AF2099 | 1. kafli | 1. kafli | Ljósvetninga saga |
5FC9E2227C39E36162AF209B | 1. kafli | 1. kafli | Ljósvetninga saga |
5FC9E2227C39E36162AF209C | 1. kafli | 1. kafli | Ljósvetninga saga |
5FC9E2227C39E36162AF209D | 1. kafli | 1. kafli | Ljósvetninga saga |
5FC9E2227C39E36162AF209E | 1. kafli | 1. kafli | Ljósvetninga saga |