Inventory Of Online Public Databases And Repositories Holding Agricultural Data In 2017
Department of Agriculture
@usgov.usda_gov_inventory_of_online_public_databases_and_repo_aed8f645
Department of Agriculture
@usgov.usda_gov_inventory_of_online_public_databases_and_repo_aed8f645
United States agricultural researchers have many options for making their data available online. This dataset aggregates the primary sources of ag-related data and determines where researchers are likely to deposit their agricultural data. These data serve as both a current landscape analysis and also as a baseline for future studies of ag research data.
As sources of agricultural data become more numerous and disparate, and collaboration and open data become more expected if not required, this research provides a landscape inventory of online sources of open agricultural data.
An inventory of current agricultural data sharing options will help assess how the Ag Data Commons, a platform for USDA-funded data cataloging and publication, can best support data-intensive and multi-disciplinary research. It will also help agricultural librarians assist their researchers in data management and publication. The goals of this study were to
The National Agricultural Library team focused on Agricultural Research Service (ARS), Natural Resources Conservation Service (NRCS), and United States Forest Service (USFS) style research data, rather than ag economics, statistics, and social sciences data. To find domain-specific, general, institutional, and federal agency repositories and databases that are open to US research submissions and have some amount of ag data, resources including re3data, libguides, and ARS lists were analysed. Primarily environmental or public health databases were not included, but places where ag grantees would publish data were considered.
We first compiled a list of known domain specific USDA / ARS datasets / databases that are represented in the Ag Data Commons, including ARS Image Gallery, ARS Nutrition Databases (sub-components), SoyBase, PeanutBase, National Fungus Collection, i5K Workspace @ NAL, and GRIN. We then searched using search engines such as Bing and Google for non-USDA / federal ag databases, using Boolean variations of “agricultural data” /“ag data” / “scientific data” + NOT + USDA (to filter out the federal / USDA results). Most of these results were domain specific, though some contained a mix of data subjects.
We then used search engines such as Bing and Google to find top agricultural university repositories using variations of “agriculture”, “ag data” and “university” to find schools with agriculture programs. Using that list of universities, we searched each university web site to see if their institution had a repository for their unique, independent research data if not apparent in the initial web browser search. We found both ag specific university repositories and general university repositories that housed a portion of agricultural data. Ag specific university repositories are included in the list of domain-specific repositories. Results included Columbia University – International Research Institute for Climate and Society, UC Davis – Cover Crops Database, etc. If a general university repository existed, we determined whether that repository could filter to include only data results after our chosen ag search terms were applied. General university databases that contain ag data included Colorado State University Digital Collections, University of Michigan ICPSR (Inter-university Consortium for Political and Social Research), and University of Minnesota DRUM (Digital Repository of the University of Minnesota). We then split out NCBI (National Center for Biotechnology Information) repositories.
Next we searched the internet for open general data repositories using a variety of search engines, and repositories containing a mix of data, journals, books, and other types of records were tested to determine whether that repository could filter for data results after search terms were applied. General subject data repositories include Figshare, Open Science Framework, PANGEA, Protein Data Bank, and Zenodo.
Finally, we compared scholarly journal suggestions for data repositories against our list to fill in any missing repositories that might contain agricultural data. Extensive lists of journals were compiled, in which USDA published in 2012 and 2016, combining search results in ARIS, Scopus, and the Forest Service's TreeSearch, plus the USDA web sites Economic Research Service (ERS), National Agricultural Statistics Service (NASS), Natural Resources and Conservation Service (NRCS), Food and Nutrition Service (FNS), Rural Development (RD), and Agricultural Marketing Service (AMS). The top 50 journals' author instructions were consulted to see if they (a) ask or require submitters to provide supplemental data, or (b) require submitters to submit data to open repositories.
Data are provided for Journals based on a 2012 and 2016 study of where USDA employees publish their research studies, ranked by number of articles, including 2015/2016 Impact Factor, Author guidelines, Supplemental Data?, Supplemental Data reviewed?, Open Data (Supplemental or in Repository) Required? and Recommended data repositories, as provided in the online author guidelines for each the top 50 journals.
We ran a series of searches on all resulting general subject databases with the designated search terms. From the results, we noted the total number of datasets in the repository, type of resource searched (datasets, data, images, components, etc.), percentage of the total database that each term comprised, any dataset with a search term that comprised at least 1% and 5% of the total collection, and any search term that returned greater than 100 and greater than 500 results.
We compared domain-specific databases and repositories based on parent organization, type of institution, and whether data submissions were dependent on conditions such as funding or affiliation of some kind.
A summary of the major findings from our data review:
See included README file for descriptions of each individual data file in this dataset.
Resources in this dataset:
File Name: Journals.csv
File Name: Repos_from_journals.csv
File Name: TDWG_Presentation.pptx
File Name: domain_specific_ag_databases.csv
File Name: Ag_Data_Repo_DD.csv
File Name: general_repos_1.csv
File Name: README_InventoryPublicDBandREepAgData.txt
Organization: Department of Agriculture
Last updated: 2024-03-30T11:34:15.254791
Tags: agricultural-data, ars, data-access, data-gov, data-publication, data-repositories, data-sharing, database, datasets, nal-ksd, open-data, scholarly-research
CREATE TABLE ag_data_repo_dd_2 (
"sheet" VARCHAR,
"column_heading" VARCHAR,
"description" VARCHAR,
"data_type" VARCHAR,
"accepted_values" VARCHAR,
"required" VARCHAR -- Required?,
"accepts_null_value" VARCHAR -- Accepts Null Value?
);CREATE TABLE domain_specific_ag_databases_1 (
"database_or_data_repository_name" VARCHAR,
"url" VARCHAR,
"organization" VARCHAR,
"type" VARCHAR,
"notes" VARCHAR,
"open_submission" VARCHAR,
"submission_notes" VARCHAR,
"conditions_associated_with_submission" VARCHAR,
"funding_notes" VARCHAR
);CREATE TABLE general_repos_1_0 (
"institution_repository" VARCHAR -- Institution / Repository,
"url" VARCHAR,
"type" VARCHAR,
"total_datasets_in_repository_as_of_6_26_2017" VARCHAR,
"resource_type_searched" VARCHAR,
"agriculture" VARCHAR,
"agriculture_percent" VARCHAR,
"agricultural_research_service" VARCHAR,
"agricultural_research_service_percent" VARCHAR,
"natural_resources_conservation_service" VARCHAR,
"nrcs_percent" VARCHAR,
"forestry" VARCHAR,
"forestry_percent" VARCHAR,
"aquaculture" VARCHAR,
"aquaculture_percent" VARCHAR,
"agronomy" VARCHAR,
"agronomy_percent" VARCHAR,
"soil_science" VARCHAR,
"soil_science_percent" VARCHAR,
"notes" VARCHAR,
"significant_source_of_ag_data" VARCHAR,
"search_term_greater_than_1_percent_of_collection" VARCHAR,
"over_100_data_search_returns" VARCHAR,
"both_1_percent_of_collection_and_over_100_returns" VARCHAR,
"search_term_greater_than_5_percent_of_collection" VARCHAR,
"over_500_data_search_returns" VARCHAR,
"both_5_percent_of_collection_and_over_500_returns" VARCHAR
);CREATE TABLE repos_from_journals_0 (
"data_repository" VARCHAR,
"recommending_journal_publisher" VARCHAR -- Recommending Journal / Publisher,
"category_ies" VARCHAR -- Category(-ies)
);Anyone who has the link will be able to view this.