GSA Enterprise Data Inventory (EDI)

Tracking systems for timeliness and completion for business processes

Interne database met diverse data

The dataset contains locations and attributes of GSA owned or leased buildings, created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies. A database provided by GSA identified Federal locations and DC GIS staff geo-processed the data.

GSA eLibrary (formerly Schedules e-Library) is the online source for the latest contract award information for: GSA Schedules; Department of Veterans Affairs (VA) Schedules; and Technology Contracts, including Governmentwide Acquisition Contracts (GWACs), Network Services and Telecommunications Contracts, and Information Technology (IT) Schedule 70. This data contains all the current contracts under those contract vehicles and their respective schedule, special item number information.

The General Service Administration's data.json harvest source. This file contains the metadata for the GSA's public data listing shown on data.gov as defined by the Project Open Data

Comprehensive dataset containing 33 verified GSA locations in United States with complete contact information, ratings, reviews, and location data.

Traffic analytics, rankings, and competitive metrics for gsa.gov as of September 2025

Comprehensive dataset containing 1 verified GSA locations in Mississippi, United States with complete contact information, ratings, reviews, and location data.

Gene-set-based analysis (GSA), which uses the relative importance of functional gene-sets, or molecular signatures, as units for analysis of genome-wide gene expression data, has exhibited major advantages with respect to greater accuracy, robustness, and biological relevance, over individual gene analysis (IGA), which uses log-ratios of individual genes for analysis. Yet IGA remains the dominant mode of analysis of gene expression data. The Connectivity Map (CMap), an extensive database on genomic profiles of effects of drugs and small molecules and widely used for studies related to repurposed drug discovery, has been mostly employed in IGA mode. Here, we constructed a GSA-based version of CMap, Gene-Set Connectivity Map (GSCMap), in which all the genomic profiles in CMap are converted, using gene-sets from the Molecular Signatures Database, to functional profiles. We showed that GSCMap essentially eliminated cell-type dependence, a weakness of CMap in IGA mode, and yielded significantly better performance on sample clustering and drug-target association. As a first application of GSCMap we constructed the platform Gene-Set Local Hierarchical Clustering (GSLHC) for discovering insights on coordinated actions of biological functions and facilitating classification of heterogeneous subtypes on drug-driven responses. GSLHC was shown to tightly clustered drugs of known similar properties. We used GSLHC to identify the therapeutic properties and putative targets of 18 compounds of previously unknown characteristics listed in CMap, eight of which suggest anti-cancer activities. The GSLHC website http://cloudr.ncu.edu.tw/gslhc/ contains 1,857 local hierarchical clusters accessible by querying 555 of the 1,309 drugs and small molecules listed in CMap. We expect GSCMap and GSLHC to be widely useful in providing new insights in the biological effect of bioactive compounds, in drug repurposing, and in function-based classification of complex diseases.

Inventory description

The Harmonized IACS inventory of Europe-LAND is a harmonised collection of data from the Geospatial Aid (GSA) system of the Integrated Control and Administration System (IACS), which manages and controls agricultural subsidies in the European Union (EU). The GSA data are a unique data source with field-levels of land use information that are annually generated. The data carry information on crops grown per field, a unique identifier of the subsidy applicants that allows to aggregate fields to farms, and information on organic cultivation.

The inventory contains all data that can be shared following the General Data Protection Regulations (GDPR) of the data providers. It covers 19 EU member states with time series up to 17 years. For most members states, only the crop information can be shared. However, for six member states also the farm identifier (Czechia, Denmark, Estonia, Ireland, Portugal and Spain) and for five also the organic management information (Austria, Flanders in Belgium, Denmark, Ireland, and Bulgaria) can be shared.

Due to General Data Protection Regulations (GDPR), we are not allowed to share all data that we collected and harmonised. We hold GSA data for six additional member states (Italy, Greece, Poland, Hungary, Romania, and Cyprus) as well as supplementary information on farm-level indicators for 17 additional member states, federal states, or regions (Austria, Cyprus, Greece, Latvia, Netherlands, Romania, Sweden, Slovenia, Slovakia, Wallonia in Belgium, Brandenburg, Lower Saxony, Saxony-Anhalt, and Thuringia in Germany, and Emilia-Romagna, Marche, and Toscana in Italy,) and organic farming information for seven more member states, federal states, or regions (Greece, Netherlands, Sweden, Slovenia, Slovakia, Wallonia in Belgium, and Brandenburg, Lower Saxony, Saarland, Saxony-Anhalt, and Thuringia in Germany). For Luxembourg and Malta, only LPIS data were available. As these datasets contain only reference parcels without detailed land-use information at the parcel level, they were not included in the inventory.

If you use the data, please also cite the original sources of the data. You can find the references in the documentation provided in the "_Documentation.zip".

The crop information were harmonised using the Hierarchical Crop and Agriculture Taxonomy (HCAT) of the EuroCrops project (Schneider et al., 2023). To allow for interoperability with EuroCrops, the harmonised Europe-LAND data come with the same column names that relate to the crop information. All crop mapping tables can be found in our GitHub repository.

Column names:

• field_id (mandatory): Unique identifier for each parcel per member state, state, or region
• farm_id (optional): Unique identifier for each farm per member state, state, or region
• crop_code (mandatory): Original, member state-specific crop code
• crop_name (mandatory): Original, member state-specific crop name
• EC_trans_n (mandatory): Original crop name translated into English
• EC_hcat_n (mandatory): Machine-readable HCAT name of the crop
• EC_hcat_c (mandatory): The 10-digit HCAT code indicating the hierarchy of the crop
• organic (optional): Whether a parcel was conventional (0), organic (1), or is in the conversion process to organic cultivation (2)
• field_size (mandatory): Size of parcel/reference parcel in hectares
• crop_area (optional): Area in hectares of the main crop reported in crop column. The crop_area column only occurs if multiple crops are reported per reference parcel.

More detailed information for all members states in our harmonised inventory can also be found in the documentation.

Information on data provision

All files come as .geoparquets to stay within the space limitations of Zenodo. Geoparquets can simply be opened in QGIS via drag and drop. Additionally, various libraries from different porgramming languages are able to handle geoparquets, e.g. geoarrow and sgarrwo in R, GDAL/OGR in C++, GeoParquet.jl in Julia or Fiona in Python.

• ES_Bundle1 (Northeast): BAL, BAR, CAS, GIR, HEC, LLE, NAV, TAR, TER, ZAR
• ES_Bundel2 (Northwest): ACO, ALA, AST, BUR, CAN, GUI, LEO, LRI, LUG, OUR, PAL, PON, VIZ, VLD, ZAM
• ES_Bundle3 (West): ALB, AVI, CAC, CIU, CUE, GUA, MAD, SAL, SEG, SOR, TOL
• ES_Bundle4 (Southwest): ALI, ALM, BAD, CAD, CDB, GRA, HEV, JAE, LAP, MAL, MUR, SAN, SEV, VLC

Changelog

Version 1.2: In this version, we have corrected the inventory description and documentation to only refer to data that we share publicly. Additionally, we corrected an error in the Spanish data, where the crop_code column got mixed up during pre-processing. This did not affect the other columns, which were correct. Moreover, we have uploaded new data for Bulgaria to the inventory.

Version 1.1: In this version, we corrected some data errors that occured in v1 due to a failure of our quality checks. First, not all fields got classified in v1, and secondly, there were two different datatypes in the EC_hcat_c in many files. Both errors are now corrected.

Data includes total 10 genome-wide genotyped ( autosomal SNP genotyping) samples of the Assam population

HHS Data Inventory: Version 1.0, published in July 2025, is a comprehensive metadata catalog designed to provide public visibility into both public and non-public data assets across all HHS Divisions. Developed in alignment with the OPEN Government Data Act (Evidence Act, Title II), the HHS Data Inventory will continue to expand and improve over time, serving as a critical resource for discovering and understanding the breadth of data assets managed by HHS.

Version 1.1 is published on Sep. 22, 2025

Gsa Government Services Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

Gsa Data Center Company Limited Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

The Federal Activities Inventory Reform (FAIR) Act Inventory contains GSA's information related to the determination of whether a position is commercial or inherently governmental in nature. Total Full-time Equivalent (FTE) are listed by activity, city and state and a designation of commercial (C) or inherently governmental (I).

The Groundwater Sustainability Plan (GSP) Annual Report (AR) datasets contain the following data submitted by Groundwater Sustainability Agencies (GSA) and Alternative Agencies as part of their GSP AR or Alternative to GSP AR: groundwater extraction, surface water supply, total water use, and change in storage volumes for a given water year. All data was originally submitted to the Department of Water Resources (DWR) through the Sustainable Groundwater Management Act (SGMA) Portal’s AR Modules (https://sgma.water.ca.gov/portal/gspar/submitted and https://sgma.water.ca.gov/portal/alternative/annualreport/submitted). Data records within each dataset correspond to either an entire basin or one of multiple GSP areas which collectively correspond to an entire basin.

The GSP Regulations established the AR data requirements (23 CCR § 356.2) and tasked DWR with developing an online reporting system for GSAs and Alternative Agencies to electronically submit these data (23 CCR § 353.2). The data fields associated with these datasets were created by DWR to ensure GSAs and Alternative Agencies electronically submitted the required AR data to DWR’s online reporting system, the SGMA Portal (https://sgma.water.ca.gov/portal/). For additional information regarding the AR Modules and the AR submittal process, please view the DWR’s AR resources (https://sgma.water.ca.gov/portal/resources).

The Federal Advisory Committee Act (FACA) database is used by Federal agencies to continuously manage an average of 1,000 advisory committees government-wide. This database is also used by the Congress to perform oversight of related Executive Branch programs and by the public, the media, and others, to stay abreast of important developments resulting from advisory committee activities. Although centrally supported by the General Services Administration's (GSA) Committee Management Secretariat, the database represents a true shared system wherein each participating agency and individual committee manager has responsibility for providing accurate and timely information that may be used to assure that the system's wide array of users has access to data required by FACA.

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