ReLTER is an R package that provides access to DEIMS-SDR, allowing to interact with software implemented by eLTER Research Infrastructure (RI) and improving the data/information shared among the Long Term Ecological Research (LTER) network. This package was conceived within eLTER H2020 project and will help advance the development of European Long-Term Ecosystem Research Infrastructures (eLTER RI).
The ReLTER package functions in particular allows to:
retrieve the information about entities (e.g. sites, datasets, and activities) shared by DEIMS-SDR (see e.g. get_site_info function);
elaborate the information of single site or merge info from national network sites or entire International LTER (ILTER) in order to provide maps, figures, graphs etc (see e.g. get_network_sites, produce_site_map or produce_site_parameters_pie functions);
interact with the ODSEurope managed by members of the Geo-harmonizer project starting with the dataset shared by DEIMS-SDR (see e.g. get_site_ODS function);
improve the quality of the dataset (see e.g. get_id_worms).
Functions currently implemented are derived from the discussion of the needs declared by eLTER users community.
The ReLTER package will follow the progress of eLTER-RI infrastructure and evolve with improvements and development of new tools.
📔 Citation
To cite ReLTER please use: Alessandro Oggioni, Micha Silver, Luigi Ranghetti & Paolo Tagliolato. (2022). ropensci/ReLTER: ReLTER v1.1.0 (1.1.0). Zenodo. https://doi.org/10.5281/zenodo.5576813
or:
@software{alessandro_oggioni_2021_5576813,
author = {Alessandro Oggioni and Micha Silver and Luigi Ranghetti and Paolo Tagliolato},
title = {ropensci/ReLTER: ReLTER v1.1.0},
month = nov,
year = 2022,
publisher = {Zenodo},
version = {1.1.0},
doi = {10.5281/zenodo.5576813},
url = {https://doi.org/10.5281/zenodo.5576813}
}📖 Documentation
Visit the ReLTER website at docs.ropensci.org/ReLTER/ for further documentation, examples, and installation of the package.
⏬ Installation
You can install the main version of ReLTER from GitHub with:
install.packages("devtools")
devtools::install_github("ropensci/ReLTER")
library(ReLTER)If you want to install different package branch (e.g. ‘dev’) can you use this command:
devtools::install_github('https://github.com/ropensci/ReLTER', ref = 'dev')The ReLTER package is part of the R-universe community and it can be installed also use this command:
utils::install.packages("ReLTER", repos = "https://ropensci.r-universe.dev")Alternatively {ReLTER} can be used in a Docker container.
If you wish to help develop this package, please follow the contributing guidelines.
📝 Examples
Some examples of the possible capabilities of this library appear below. These examples demonstrate interaction with the DEIMS-SDR API.
get_ilter_generalinfo()
In this initial example, the get_ilter_generalinfo function is called to find the DEIMS ID for a specific eLTER site. The function takes parameters “country_name” and “site_name”, and returns the site URL (the DEIMS ID) in the DEIMS SDR infrastructure.
# Obtain DEIMS ID for the Eisenwurzen site in Austria
eisenwurzen <- ReLTER::get_ilter_generalinfo(country_name = "Austri",
site_name = "Eisen")
# extract DEIMS ID
(eisenwurzen_deimsid <- eisenwurzen$uri)
#> [1] "https://deims.org/d0a8da18-0881-4ebe-bccf-bc4cb4e25701"In some countries, many sites have similar names. Here is a method to find the DEIMS ID of the specific site of interest.
# Obtain DEIMS ID for sites in Germany, with names like "TERENO"
sites_germany <- ReLTER::get_ilter_generalinfo(country_name = "Germ",
site_name = "TERENO")
# List full names of these sites
sites_germany$title
#> [1] "TERENO Harz/Central German Lowland LTER - Germany"
#> [2] "TERENO - Bad Lauchstaedt - Germany"
#> [3] "TERENO - Bode catchment - Germany"
#> [4] "TERENO - Friedeburg - Germany"
#> [5] "TERENO - Gimritz - Germany"
#> [6] "TERENO - Greifenhagen - Germany"
#> [7] "TERENO - Schafstaedt - Germany"
#> [8] "TERENO - Siptenfelde - Germany"
#> [9] "TERENO - Wanzleben - Germany"
#> [10] "TERENO - Wüstebach - Germany"
#> [11] "TERENO - Harsleben - Germany"
#> [12] "TERENO Harz - central german lowland - Hohes Holz - Germany"
#> [13] "TERENO - Rollesbroich - Germany"
#> [14] "TERENO - Selhausen - Germany"
#> [15] "TERENO Eifel Lower Rhine Valley - Germany"
# Get the DEIMS ID of the site of interest by partial string match on the title
idx <- which(stringr::str_detect(sites_germany$title,
"Friedeburg"))
(friedeburg_deims_id <- sites_germany$uri[idx])
#> [1] "https://deims.org/a4dc71c4-de05-4883-ae53-7f57d51555fc"get_site_info(category = “Boundaries”)
Next, the get_site_info function, using category “Boundaries”, returns an sf object. Furthermore, a map overlayed with the boundaries of the site is displayed, using the site geographical boundaries provided by DEIMS-SDR.
library(dplyr)
siteBoundaries <- ReLTER::get_site_info(
deimsid = 'https://deims.org/f30007c4-8a6e-4f11-ab87-569db54638fe',
category = "Boundaries"
)
tmap::tmap_mode("plot")
r <- tmaptools::read_osm(siteBoundaries)
tmap::tm_shape(r) +
tmap::tm_rgb() +
tmap::tm_shape(siteBoundaries) +
tmap::tm_fill(col="blue", alpha = 0.5) +
tmap::tm_borders(col = "blue")
get_network_parameters()
The get_network_parameters function retrieves a list of parameters collected by sites that are part of a given network (e.g. LTER-Italy). Information is gathered from those sites that are part of the specified network id, on DEIMS-SDR. The function returns a tibble.
library(dplyr)
invisible(
utils::capture.output(
listParams <- ReLTER::get_network_parameters(
networkDEIMSID = 'https://deims.org/network/7fef6b73-e5cb-4cd2-b438-ed32eb1504b3'
)
)
)
knitr::kable(listParams[1:10, ] %>% dplyr::rows_insert(tibble(parameterLabel = "...", parameterUri = "...")))| parameterLabel | parameterUri |
|---|---|
| chlorophyll content of water | http://vocabs.lter-europe.net/EnvThes/10088 |
| community composition | http://vocabs.lter-europe.net/EnvThes/22086 |
| dissolved nutrient | http://vocabs.lter-europe.net/EnvThes/22107 |
| diversity index | http://vocabs.lter-europe.net/EnvThes/21513 |
| ecosystem parameter | http://vocabs.lter-europe.net/EnvThes/20939 |
| ecosystem structure | http://vocabs.lter-europe.net/EnvThes/21475 |
| faunistic diversity | http://vocabs.lter-europe.net/EnvThes/22119 |
| floristic diversity | http://vocabs.lter-europe.net/EnvThes/22122 |
| inorganic nutrient content | http://vocabs.lter-europe.net/EnvThes/22137 |
| secchi depth | http://vocabs.lter-europe.net/EnvThes/22226 |
| … | … |
get_dataset_info()
The get_dataset_info function retrieves a table with information about specific datasets shared through DEIMS-SDR.
tDataset <- ReLTER::get_dataset_info(datasetid = "https://deims.org/dataset/38d604ef-decb-4d67-8ac3-cc843d10d3ef")
print(tDataset)
#> Simple feature collection with 1 feature and 33 fields
#> Geometry type: POLYGON
#> Dimension: XY
#> Bounding box: xmin: 11.88721 ymin: 43.20518 xmax: 15.86426 ymax: 45.91294
#> Geodetic CRS: WGS 84
#> # A tibble: 1 × 34
#> title abstract keywords uri type dateRange.from dateRange.to relatedSite
#> * <chr> <chr> <list> <chr> <chr> <chr> <lgl> <list>
#> 1 LTER No… The pre… <df> http… data… 1965-01-01 NA <df>
#> # … with 26 more variables: contacts.corresponding <list>,
#> # contacts.creator <list>, contacts.metadataProvider <lgl>,
#> # observationParameters <list>, observationSpecies <list>, dataPolicy <list>,
#> # doi <chr>, onlineLocation <list>, legal.accessUse <list>,
#> # legal.rights <lgl>, legal.legalAct <lgl>, legal.citation <lgl>,
#> # method.instrumentation <lgl>, method.qualityAssurance <lgl>,
#> # method.methodUrl <list>, method.methodDescription <list>, …
tmap::tmap_mode("plot")
r <- tmaptools::read_osm(tDataset)
tmap::tm_shape(r) +
tmap::tm_rgb() +
tmap::tm_shape(tDataset) +
tmap::tm_fill(col="blue", alpha = 0.5) +
tmap::tm_borders(col = "blue")
get_site_info(category = “RelateRes”)
The get_site_info function, using category = “RelateRes”, provides a list of related resources associated with a site within DEIMS-SDR.
tSiteRelatedResources <- ReLTER::get_site_info(
deimsid = "https://deims.org/f30007c4-8a6e-4f11-ab87-569db54638fe",
category = "RelateRes"
)
print(tSiteRelatedResources$relatedResources[[1]])
#> relatedResourcesTitle
#> 1 Biovolume of Phytoplankton in Lake Maggiore site code IT_SI001137_within the period 1981 - 2010
#> 2 Atmospheric deposition in Pallanza, Lake Maggiore watershed, 1980-2018
#> 3 Phytoplankton_Biomass_Lake Maggiore_Ghiffa_station-1984-2018
#> 4 Water chemistry of Lake Maggiore, Ghiffa station, 1988-2018
#> 5 Transparency (Secchi depth) of Lake Maggiore, Ghiffa station, 1988-2018
#> 6 Chlorophyll a_Lake_Maggiore_Ghiffa_Station-1984-2018
#> 7 Water discharge of River Ticino, Lake Maggiore outlet, 1988-2018
#> relatedResourcesChanged
#> 1 2021-08-25 16:38:00
#> 2 2020-12-13 20:06:00
#> 3 2020-12-16 10:46:00
#> 4 2021-11-03 06:10:00
#> 5 2022-02-16 11:36:00
#> 6 2021-01-10 21:48:00
#> 7 2021-07-21 12:35:00
#> uri
#> 1 https://deims.org/dataset/d9e94776-e7a8-11e2-a655-005056ab003f
#> 2 https://deims.org/dataset/0ce46362-0aab-482a-b1f0-a444a5dada39
#> 3 https://deims.org/dataset/0ab8425a-d574-4575-8ba9-5275c607b0c5
#> 4 https://deims.org/dataset/69564188-89de-4879-ad88-4aa97c1d005d
#> 5 https://deims.org/dataset/e538c743-2149-49e3-9025-14a04ea7c90d
#> 6 https://deims.org/dataset/c857c8e2-48aa-4dcd-a7fb-e089bd4c5c4e
#> 7 https://deims.org/dataset/fb3a8fec-0c1f-4c3a-81d5-364c7e6078c4produce_site_parameters_waffle()
The produce_site_parameters_waffle function provides a grouping of parameters, as measured within a site, in a “waffle chart” representation.
ReLTER::produce_site_parameters_waffle(
deimsid = "https://deims.org/f30007c4-8a6e-4f11-ab87-569db54638fe")
#> # A tibble: 11 × 4
#> parameterGroups n freq label
#> <chr> <int> <dbl> <chr>
#> 1 agricultural parameters 1 0.0105 1%
#> 2 atmospheric parameters 14 0.147 15%
#> 3 biological parameters 8 0.0842 8%
#> 4 chemical parameters 24 0.253 25%
#> 5 ecosystem parameters 23 0.242 24%
#> 6 genetic parameters 2 0.0211 2%
#> 7 landscape parameters 4 0.0421 4%
#> 8 physical parameters 1 0.0105 1%
#> 9 remote sensing parameters 1 0.0105 1%
#> 10 soil parameters 1 0.0105 1%
#> 11 water parameters 16 0.168 17%get_site_ODS()
The get_site_ODS function retrieves datasets from OpenDataScience, and crops to the boundary of the specified eLTER site.
siteNDVI <- ReLTER::get_site_ODS(
deimsid = "https://deims.org/d0a8da18-0881-4ebe-bccf-bc4cb4e25701",
dataset = "ndvi_summer"
)
siteBoundary <- ReLTER::get_site_info(
deimsid = "https://deims.org/d0a8da18-0881-4ebe-bccf-bc4cb4e25701",
category = "Boundaries"
)
tmap::tmap_mode("plot")
pal <- RColorBrewer::brewer.pal("RdYlGn", n = 5)
r <- tmaptools::read_osm(siteBoundary)
tmap::tm_shape(r) +
tmap::tm_rgb() +
tmap::tm_shape(siteNDVI, raster.downsample = TRUE) +
tmap::tm_raster(palette = pal, alpha = 0.7) +
tmap::tm_shape(siteBoundary) +
tmap::tm_borders("black")
👩💻 Persons involved 👨💻
Alessandro Oggioni https://orcid.org/0000-0002-7997-219X (CNR, Institute for Electromagnetic Sensing of the Environment - IREA)
Micha Silver https://orcid.org/0000-0002-1128-1325 (Ben Gurion University - BGU)
Luigi Ranghetti https:://orcid.org/0000-0001-6207-5188 (CNR, Institute for Electromagnetic Sensing of the Environment - IREA)
Paolo Tagliolato https:://orcid.org/0000-0002-0261-313X (CNR, Institute for Electromagnetic Sensing of the Environment - IREA)
For a exhaustive list of contributors please visit authors page.
👍 Acknowledgements
This work has been partially funded from the European Union’s Horizon 2020 research and innovation programme under the H2020 eLTER-Plus Project grant agreement No 871128.
Thanks to the reviewers and the editor (more about authors) for their work.