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The Ag Data Commons is migrating

The Ag Data Commons is migrating to a new institutional portal on Figshare. The current system is available for search and download only. The new platform is open for submission with assistance from Ag Data Commons curators. Please contact NAL-ADC-Curator@usda.gov, if you need to publish or update your datasets.

ARDN

About the The Agricultural Research Data Network (ARDN)

ARDN is a network of datasets which can be harmonized and aggregated using a common vocabulary and format through the use of annotations. Datasets in ARDN are connected by a common protocol for annotating data which allows these datasets, in their raw format, to be interpreted in an automated way. The goal of ARDN is to create a distributed network for harmonized crop systems research data and to make these data available through existing data portals such as USDA’s Ag Data Commons and CGIAR’s GARDIAN.

ARDN data providers have data that they wish to make available to researchers in a format that can be interpreted in an automated way. ARDN tools assist these users to “ARDN-ize” their data thereby making these datasets reusable. End users of ARDN data make use of the interoperability of these datasets and can download, combine, and transform the data into formats that can be used in modeling applications, data analytics, meta-analyses, and other quantitative uses. Currently ARDN contains mainly agronomic research data and does not (yet) include data from other agricultural domains such as livestock, pest and diseases, aquaculture, socioeconomics, or genetics. ARDN is mainly developed for quantitative data that are used in modeling and analytics. We hope that in the future, datasets are collected from the field using standardized vocabularies and ontologies so that the ARDN data annotation method is no longer needed. But until then, we offer these interoperability hacks!

For more information, please visit https://agmip.github.io/ARDN/.

Funding sources
Development of ARDN infrastructure was funded by:

  • USDA NIFA, Award #2019-67021-29921 – development of data tools, refinement of data annotation formats, implementation of ARDN on Ag Data Commons, preparation of initial ADC ARDN data
  • International Food Policy Research Institute, Research Agreement No. 2018X212.UOF – design of initial data annotation protocols and development of translator API, implementation of ARDN on GARDIAN
  • IFDC AGR DTD 08-03-2018 - VMapper testing and debugging
  • AgMIP DFID / USDA 59-3625-1-745 and 59-5030-5-018 - design of ACE format and development of original AgMIP translators for crop model users

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    ARDN Datasets

    13 datasets

    UGA Variety Testing Soybean Evaluations 2016-2019

      This data was collected and published by University of Georgia's Statewide Variety Testing program from 2016-2019. It consists of experimental (non-regulated) and commercially-released soybean germplasm entered by seed companies and public institutions.

      UGA Variety Testing Soybean Evaluations 2016-2019: ARDN products

        ARDN (Agricultural Research Data Network) annotations for UGA Variety Testing Soybean Evaluations 2016-2019. This data was collected and published by University of Georgia's Statewide Variety Testing program from 2016-2019. It consists of experimental (non-regulated) and commercially-released soybean germplasm entered by seed companies, universities and USDA breeding programs.

        UGA Variety Testing Corn Silage Evaluations 2016-2019: ARDN products

          ARDN (Agricultural Research Data Network) annotations for UGA Variety Testing Corn Silage Evaluations 2016-2019. This data was collected and published by University of Georgia's Statewide Variety Testing program from 2014-2019. It consists of experimental (non-regulated) and commercially-released corn hybrids entered by seed companies.

          UGA Variety Testing Corn Silage Evaluations 2016-2019

            This data was collected and published by University of Georgia's Statewide Variety Testing program from 2016-2019. It consists of experimental (non-regulated) and commercially-released corn hybrids entered by seed companies.

            UGA Variety Testing Corn Grain Evaluations 2014-2019: ARDN products

              ARDN (Agricultural Research Data Network) annotations for UGA Variety Testing Corn Grain Evaluations 2014-2019. This data was collected and published by University of Georgia's Statewide Variety Testing program from 2014-2019. It consists of experimental (non-regulated) and commercially-released corn hybrids entered by seed companies.

              UGA Variety Testing Corn Grain Evaluations 2014-2019

                This data was collected and published by University of Georgia's Statewide Variety Testing program from 2014-2019. It consists of experimental (non-regulated) and commercially-released corn hybrids entered by seed companies.

                TERRA-REF Season 4 and 6 Sorghum phenotypes and agronomic metadata in BrAPI format

                  This data represents a small subset of the TERRA-REF release available on Dryad (LeBauer et al 2020), including harvested biomass for each cultivar, plot location, planting date, harvest date, fertilizer application, genotype / accession names and metadata, and additional agronomic management metadata for a population of Sorghum bicolor evaluated over two growing seasons. The data can be accessed through a BrAPI-compliant endpoint at terraref.org/brapi. This dataset is a snapshot of the TERRA-REF BrAPI endpoint contents, representing the minimum data and metadata required to run a crop model.

                  Floridan Aquifer Collaborative Engagement for Sustainability (FACETS) - Field trial data from University of Georgia Stripling Irrigation Research Park (SIRP): ARDN Products

                    ARDN (Agricultural Research Data Network) annotations for "Floridan Aquifer Collaborative Engagement for Sustainability (FACETS) - Field trial data from University of Georgia Stripling Irrigation Research Park (SIRP)". The ARDN project (https://data.nal.usda.gov/ardn) is a network of datasets harmonized and aggregated using the ICASA vocabulary, as recommended by USDA NAL (https://data.nal.usda.gov/data-dictionary-examples) and described in detail here: www.tinyurl.com/icasa-mvl”. The original dataset presents evaluations of different irrigation and fertilization treatments (corn and cotton have three nitrogen fertilization and three irrigation treatments, peanut has nine irrigation treatments and no N fertilizer treatment) at the University of Georgia’s Stripling Irrigation Research Park (SIRP) located near Camilla, Georgia in a 4 ha research field.

                    Floridan Aquifer Collaborative Engagement for Sustainability (FACETS) - Field trial data from Live Oak, Florida: ARDN products

                      ARDN (Agricultural Research Data Network) annotations for "Floridan Aquifer Collaborative Engagement for Sustainability (FACETS) - Field trial data from Live Oak, Florida". The ARDN project (https://data.nal.usda.gov/ardn) is a network of datasets harmonized and aggregated using a common vocabulary termed ICASA. ICASA is a recommended data dictionary by USDA NAL (https://data.nal.usda.gov/data-dictionary-examples) described in detail here: www.tinyurl.com/icasa-mvl. Research was conducted at the North Florida Research and Education Center - Suwannee Valley, located near Live Oak, Florida (30°18’22” N, 82°54’00” W). Corn, carrots, peanuts, and rye (cover crop) were grown on Hurricane, Chipley, and Blanton soil complexes that are all over 90% sand. The experimental design utilized a randomized complete block design with split plot that incorporated two fields with eight blocks (treatment replicates) and fifteen plots per block. The main plots contained four irrigation treatments, and the sub-plots contained three different nitrogen rates. The SMS irrigation treatment contained three additional nitrogen treatments. The north field in the study (System 2) was a corn-cover crop-peanut-cover crop rotation, while the south field (System 1) was a corn-carrot-peanut-cover crop rotation. During each growing season, soil moisture was monitored using capacitance type soil moisture sensors, soil nitrogen was measured through bi-weekly soil samples at four depths, and biomass was collected four times with the final sample being collected just prior to harvest.