We analyzed the field of expression profiling by high throughput sequencing, or HT-seq, in terms of replicability and reproducibility, using data from the NCBI GEO (Gene Expression Omnibus) repository. Our work puts an upper bound of 62% to field-wide reproducibility, based on the types of files submitted to GEO.

Archived dataset contains following files:

- output/parsed_suppfiles.csv, p-value histograms, histogram classes, estimated number of true null hypotheses (pi0).

- output/document_summaries.csv, document summaries of NCBI GEO series

- output/publications.csv, publication info of NCBI GEO series

- output/scopus_citedbycount.csv, Scopus citation info of NCBI GEO series

- output/single-cell.csv, single cell experiments

- spots.csv, NCBI SRA sequencing run metadata

- suppfilenames.txt, list of all supplementary file names of NCBI GEO submissions. One filename per row.

- suppfilenames_filtered.txt, list of supplementary file names used for downloading files from NCBI GEO. One filename per row.

Gene Expression Omnibus is a public functional genomics data repository supporting MIAME-compliant submissions of array- and sequence-based data. Tools are provided to help users query and download experiments and curated gene expression profiles.

Description

This template is for recording genome data from the NimbleGen platform. This template was taken from the GEO website (http://www.ncbi.nlm.nih.gov/geo/info/spreadsheet.html) and modified to conform to the SysMO-JERM (Just enough Results Model) for transcriptomics. Using these templates will mean easier submission to GEO/ArrayExpress and greater consistency of data in SEEK.

Wetlands in California are protected by several federal and state laws, regulations, and policies. This layer was extracted from the broader vegetation raster from the CA Nature project which was recently enhanced to include a more comprehensive definition of wetland. This wetlands dataset is used as an exclusion as part of the biological planning priorities in the CEC 2023 Land-Use Screens.This layer is featured in the CEC 2023 Land-Use Screens for Electric System Planning data viewer.For more information about this layer and its use in electric system planning, please refer to the Land Use Screens Staff Report in the CEC Energy Planning Library.

The geographic boundaries of Montgomery County's incorporated City, Towns or Villages. In Montgomery County, municipalities are divided by whether a jurisdiction has zoning authority or not. Those with zoning authority include, Barnesville, Brookeville, Gaithersburg, Laytonsville, Poolesville, Rockville and Washington Grove. The rest of the municipalities abide by the Montgomery County Planning Department zoning code.For more information, contact: GIS Manager Information Technology & Innovation (ITI) Montgomery County Planning Department, MNCPPC T: 301-650-5620

This dataset contains major cross country power transmission lines within Montgomery County. This data was captured for use in general mapping at a scale of 1:100. Countywide data updated Spring 2020. For more information, contact: GIS Manager Information Technology & Innovation (ITI) Montgomery County Planning Department, MNCPPC T: 301-650-5620

Hydro 24K - Value Added 2014 MetadataABOUT THE CONTENTS OF THE DATABASE:Attribute Info - a large table that lists all water feature attributes (columns) in the database. Most will use this database to explore different water feature characteristics (e.g. drainage area, upstream land cover composition). This table can also be used to look up whether a specific water feature characteristic is in the database.Hydro 24K VA Schematic Diagram - a database schematic diagram showing the various feature classes and tables in the database, and the various IDs that relate to each other.HOW THE DATABASE WAS CREATED:Hydro 24K VA Documentation - Describes how the database was created from watershed creation to feature attribution.Attribute Reclassification - a large lookup table referred to in Hydro 24K VA Documentation.Data Sources - a table that lists the original data sources that were used to create the value-added attributes in the database.DOCUMENTATION OF SUPPLEMENTAL ATTRIBUTES:Flow Temperature Definitions - A table of column names and associated descriptions for the table: WD_HYDRO_VA_NC_FLOW_TEMP_REF. This table contains a variety of modeled flow and temperature estimates. These flow and temperature estimates were used to estimate each stream natural community, also included in the table.

This File Geodatabase download, (last updated September 25, 2024), contains all the feature classes within the Transportation Network. The City of Langley has compiled all the Transportation Network feature classes into one file geodatabase. File Geodatabase Feature Classes:Bicycle RoutesBridgesDisaster Response RoutesMediansRailwayRoadsSidewalksStreet Names

Bulk exports, in file-geodatabase format, of data that is shared via the VT EGC (Enterprise GIS Consortium) Geospatial Data Exchange Protocol.

The points in this dataset represent the location of a site or structure in Lee County, FL to which an address has been assigned by Lee County Department of Public Safety/E911 Addressing Division.

This File Geodatabase download, (last updated September 25, 2024), contains all the feature classes within the Storm Sewer Utility System. The City of Langley has compiled all the Storm Sewer feature classes into one file geodatabase for convenience. File Geodatabase Feature Classes:Catch BasinsHeadwallsInvertsLateralsMainsMains AnnotationManholesOffset LinesOffset TextService LinesService Text

Additional file 8: Table S3. RNAseq datasets included in the analysis of this paper and submitted to the GEO database.

One-foot and two-foot contours derived from LiDAR terrain model. The DTM was developed to support the Florida Division of Emergency Management (FDEM) development and maintenance of Regional Evacuation Studies (Study), which include vulnerability assessments and assist disaster response personnel in understanding threats to Florida's citizens and visitors. Breaklines improve the digital elevation model in areas where the point density is insufficient.This data set is one component of a digital terrain model (DTM) for the Florida Division of Emergency Management's (FDEM) Project Management and Technical Services for Mapping within Coastal Florida (Contract 07-HS-34-14-00-22-469), encompassing the entire coastline of Florida. The dataset is comprised of mass points, 2-D and 3-D breakline features, 1-foot and 2-foot contours, ground control, vertical test points, and a footprint of the data set, in the ESRI ArcGIS File Geodatabase format. In accordance with the Baseline Specifications 1.2, the following breakline features are contained within the database: closed water bodies (lakes, reservoirs, etc) as 2-D or 3-D polygons; linear hydrographic features (streams, shorelines, canals, swales, embankments, etc) as 3-D breaklines; coastal shorelines as 2-D or 3-D linear features; edge of pavement road features as 3-D breaklines; soft features (ridges, valleys, etc.) as 3-D breaklines; low confidence areas as 2-D polygons; island features as 2-D or 3-D polygons; overpasses and bridges as 3-D breaklines. Contours were generated from a gridded DEM: 2-foot contours meet National Map Accuracy Standards, with 1-foot contours for visualization purposes. The LiDAR masspoints are delivered in the LAS file format based on the FDEM's 5,000' by 5,000' grid. Breakline features were captured to develop a hydrologically correct DTM. Bare earth LiDAR masspoint data display a vertical accuracy of at least 0.3-feet root mean square error (RMSE) in open unobscured areas.

2' Contour Lines generated from Lee County 1998 Digital Orthophotography project performed by EarthData International. Elevations are in NAVD88, standard vertical error should not exceed 0.6 ft. February-March 1998.

Spot elevations generated from Lee County 1998 Digital Orthophotography project performed by EarthData International Elevations are in NAVD88. February-March 1998

This dataset provides a representation of ground elevation (in NAVD 88 feet). Spot elevations are evenly spaced every 50 feet. Points on a regular grid were derived from LiDAR LAS files (flown in 2007 as part of the Statewide Regional Evacuation Study) using QChoherent's LP360 software. ASCII XYZ coordinates exported from a "Surface " using Triangulation (TIN) and a cell size of 50 feet were used to generate the points in this dataset.

Mineral, Temperature, Gravity, and Fault Density maps in the Coso Geothermal Field in California.

Geoscape G-NAF is the geocoded address database for Australian businesses and governments. It’s the trusted source of geocoded address data for Australia with over 50 million contributed addresses distilled into 15.4 million G-NAF addresses. It is built and maintained by Geoscape Australia using independently examined and validated government data.

From 22 August 2022, Geoscape Australia is making G-NAF available in an additional simplified table format. G-NAF Core makes accessing geocoded addresses easier by utilising less technical effort.

G-NAF Core will be updated on a quarterly basis along with G-NAF.

Further information about contributors to G-NAF is available here.

With more than 15 million Australian physical address record, G-NAF is one of the most ubiquitous and powerful spatial datasets. The records include geocodes, which are latitude and longitude map coordinates. G-NAF does not contain personal information or details relating to individuals.

Updated versions of G-NAF are published on a quarterly basis. Previous versions are available here

Users have the option to download datasets with feature coordinates referencing either GDA94 or GDA2020 datums.

Changes in the August 2025 release

• Nationally, the August 2025 update of G-NAF shows an overall increase of 40,716 addresses (0.30%). The total number of addresses in G-NAF now stands at 15,794,643 of which 14,950,491 or 94.66% are principal.

• In the ACT, there have been minor updates to the address parsing of flat-numbered addresses aimed at: improving the address representation of flat-numbered addresses; improving address coverage; and improving address alignment between contributors. This change affects approximately 4,000 addresses.

• A small number of additional address sites have implemented the use of the BUILDING_NAME attribute as part of the merge criteria to improve address coverage for flat-numbered addresses in NSW and QLD. These changes have resulted in the creation of approximately 400 addresses in NSW and 120 in QLD.

• A focus has been applied to Tasmanian street-locality addresses to reduce the number of these addresses. For the August 2025 release, there is a reduction of some 900 street-locality addresses in Tasmania.

• Geoscape has moved product descriptions, guides and reports online to https://docs.geoscape.com.au.

Further information on G-NAF, including FAQs on the data, is available here or through Geoscape Australia’s network of partners. They provide a range of commercial products based on G-NAF, including software solutions, consultancy and support.

Additional information: On 1 October 2020, PSMA Australia Limited began trading as Geoscape Australia.

License Information

Use of the G-NAF downloaded from data.gov.au is subject to the End User Licence Agreement (EULA)

The EULA terms are based on the Creative Commons Attribution 4.0 International license (CC BY 4.0). However, an important restriction relating to the use of the open G-NAF for the sending of mail has been added.

The open G-NAF data must not be used for the generation of an address or the compilation of an address for the sending of mail unless the user has verified that each address to be used for the sending of mail is capable of receiving mail by reference to a secondary source of information. Further information on this use restriction is available here.

End users must only use the data in ways that are consistent with the Australian Privacy Principles issued under the Privacy Act 1988 (Cth).

Users must also note the following attribution requirements:

Preferred attribution for the Licensed Material:

_G-NAF © Geoscape Australia licensed by the Commonwealth of Australia under the _Open Geo-coded National Address File (G-NAF) End User Licence Agreement.

Preferred attribution for Adapted Material:

Incorporates or developed using G-NAF © Geoscape Australia licensed by the Commonwealth of Australia under the Open Geo-coded National Address File (G-NAF) End User Licence Agreement.

What to Expect When You Download G-NAF

G-NAF is a complex and large dataset (approximately 5GB unpacked), consisting of multiple tables that will need to be joined prior to use. The dataset is primarily designed for application developers and large-scale spatial integration. Users are advised to read the technical documentation, including product change notices and the individual product descriptions before downloading and using the product. A quick reference guide on unpacking the G-NAF is also available.

These files contain the geodatabases related to the Desert Peak Geothermal Field. It includes all input and output files used in the project. The files include data categories of raw data, pre-processed data, and analysis (post-processed data). In each of these categories there are six additional types of raster catalogs including Radar, SWIR, Thermal, Geophysics, Geology, and Wells. The files for the Desert Peak Geothermal Site are used with the Geothermal Exploration Artificial Intelligence to identify indicators of blind geothermal systems. The included zip file is a geodatabase to be used with ArcGIS and the tar file is an inclusive database that encompasses the inputs and outputs for the Desert Peak Geothermal Field.