Unique values and counts of metadata location fields.

This is a graphic representation of the data stewards based on PLSS Townships in PLSS areas. In non-PLSS areas the metadata at a glance is based on a data steward defined polygons such as a city or county or other units. The identification of the data steward is a general indication of the agency that will be responsible for updates and providing the authoritative data sources. In other implementations this may have been termed the alternate source, meaning alternate to the BLM. But in the shared environment of the NSDI the data steward for an area is the primary coordinator or agency responsible for making updates or causing updates to be made. The data stewardship polygons are defined and provided by the data steward.

Time-based metadata formatted for TimelineJS or other applications.

MetadataGlance: MetadataGlance provides PLSS data steward content for individual PLSS units.This dataset represents the GIS Version of the Public Land Survey System including both rectangular and non-rectangular surveys. The primary source for the data is cadastral survey records housed by the BLM supplemented with local records and geographic control coordinates from states, counties as well as other federal agencies such as the USGS and USFS. The data has been converted from source documents to digital form and transferred into a GIS format that is compliant with FGDC Cadastral Data Content Standards and Guidelines for publication. This data is optimized for data publication and sharing rather than for specific "production" or operation and maintenance. This data set includes the following: PLSS Fully Intersected (all of the PLSS feature at the atomic or smallest polygon level), PLSS Townships, First Divisions and Second Divisions (the hierarchical break down of the PLSS Rectangular surveys) PLSS Special surveys (non rectangular components of the PLSS) Meandered Water, Corners and Conflicted Areas (known areas of gaps or overlaps between Townships or state boundaries). The Entity-Attribute section of this metadata describes these components in greater detail.

Complete metadata export for Idaho Tree Ring Lab Data Hub objects.

Metadata form template for Tempe Open Data.

This data represents the GIS Version of the Public Land Survey System including both rectangular and non-rectangular survey data. The rectangular survey data are a reference system for land tenure based upon meridian, township/range, section, section subdivision and government lots. The non-rectangular survey data represent surveys that were largely performed to protect and/or convey title on specific parcels of land such as mineral surveys and tracts. The data are largely complete in reference to the rectangular survey data at the level of first division. However, the data varies in terms of granularity of its spatial representation as well as its content below the first division. Therefore, depending upon the data source and steward, accurate subdivision of the rectangular data may not be available below the first division and the non-rectangular minerals surveys may not be present. At times, the complexity of surveys rendered the collection of data cost prohibitive such as in areas characterized by numerous, overlapping mineral surveys. In these situations, the data were often not abstracted or were only partially abstracted and incorporated into the data set. These PLSS data were compiled from a broad spectrum or sources including federal, county, and private survey records such as field notes and plats as well as map sources such as USGS 7 ½ minute quadrangles. The metadata in each data set describes the production methods for the data content. This data is optimized for data publication and sharing rather than for specific "production" or operation and maintenance. A complete PLSS data set includes the following: PLSS Townships, First Divisions and Second Divisions (the hierarchical break down of the PLSS Rectangular surveys) PLSS Special surveys (non-rectangular components of the PLSS) Meandered Water, Corners, Metadata at a Glance (which identified last revised date and data steward) and Conflicted Areas (known areas of gaps or overlaps or inconsistencies). The Entity-Attribute section of this metadata describes these components in greater detail. This is a graphic representation of the data stewards based on PLSS Townships in PLSS areas. In non-PLSS areas the metadata at a glance is based on a data steward defined polygons such as a city or county or other units. The identification of the data steward is a general indication of the agency that will be responsible for updates and providing the authoritative data sources. In other implementations this may have been termed the alternate source, meaning alternate to the BLM. But in the shared environment of the NSDI the data steward for an area is the primary coordinator or agency responsible for making updates or causing updates to be made. The data stewardship polygons are defined and provided by the data steward.

PO.DAAC provides several ways to discover and access physical oceanography data, from the PO.DAAC Web Portal to FTP access to front-end user interfaces (see http://podaac.jpl.nasa.gov). That same data can also be discovered and accessed through PO.DAAC Web Services, enabling efficient machine-to-machine communication and data transfers.

This feature layer depicts land use within northeastern Illinois broken out into 57 categories. This dataset is an update of the 2018 parcel-based Land Use Inventory and the primary focus was on parcels whose assessment records or geometry had changed between 2018 and 2020, suggesting a change in land use. Parcels were dissolved on common land use types, and polygons were generated for non-parcel areas (e.g. road rights-of-way) and assigned a generic “non-parcel” category.Download the data from the CMAP Data Hub.Supporting metadata and documentation for the 2020 Land Use Inventory for Northeastern Illinois:

2020 Land Use Inventory Classification Schema provides a full description of all land use categories. 2020 Land Use Inventory Geodatabase Schema provides a description of LUI attributes and domains. 2020 Land Use Inventory Metadata LANDUSE lookup .csv table to support shapefile downloads.

More information can be found on CMAP's Land Use Inventory webpage.

Metropolitan Statistical Areas are CBSAs associated with at least one urbanized area that has a population of at least 50,000. The metropolitan statistical area comprises the central county or counties or equivalent entities containing the core, plus adjacent outlying counties having a high degree of social and economic integration with the central county or counties as measured through commuting.Download: https://www2.census.gov/geo/tiger/TGRGDB24/tlgdb_2024_a_us_nationgeo.gdb.zip Layer: Core_Based_Statistical_Area where [MEMI] = "1"Metadata: https://meta.geo.census.gov/data/existing/decennial/GEO/GPMB/TIGERline/Current_19115/series_tl_2023_cbsa.shp.iso.xml

Abstract: This dataset contains bacterial production, primary production, chlorophyll biomass, and photosynthetic parameters for samples archived in NCBI SRA as SUB4579142.

Textural class (defined according to USDA system) at 6 depth intervals derived from sand, silt and clay contents predicted using the Africa Soil Profiles Database (AfSP) v1.2. For details see published paper here below (Hengl T., G.B.M. Heuvelink, B. Kempen, J.G.B. Leenaars, M.G. Walsh, K.D. Shepherd, A. Sila, R.A. MacMillan, J. Mendes de Jesus, L.T. Desta, J.E. Tondoh, 2015. Mapping Soil Properties of Africa at 250 m Resolution: Random Forests Significantly Improve Current Predictions. PLoS ONE 10(6)

Texture classes of the USDA system / triangle used in this map: code, name 1 clay 2 silty clay 3 sandy clay 4 clay loam 5 silty clayloam 6 sandy clay loam 7 loam 8 silty loam 9 sandy loam 10 silt
11 loamy sand 12 sand

The MAREL (Mesures Automatisées en Réseau pour l’Environnement Littoral) Carnot system developed and implemented by Ifremer (French Research Institute for Exploitation of the sea) in 2004 is a moored buoy equipped with physico-chemical and biological measuring devices working in continuous and autonomous conditions. The system is located in the Boulogne-sur-Mer harbor (eastern English Channel) influenced both by marine coastal and fresh waters. The measuring station is equipped with high performance systems for seawater analysis and near real time data transmission.

A Shoreline Management Plan (SMP) is a large-scale assessment of the risks associated with coastal processes and helps reduce these risks to people and the developed, historic and natural environments. Coastal processes include tidal patterns, wave height, wave direction and the movement of beach and seabed materials.

The SMPs set the strategic policy direction for coastal management and identify the most sustainable approaches to managing the risks to the coast in the short term (Epoch 1 0-20 years), medium term (Epoch 2 20-50 years) and long term (Epoch 3 50-100 years).

A set of preferred policies are identified which are assigned to 'policy units' for each SMP epoch. A 'policy unit' (PU) is a length of shoreline where a separate shoreline management policy applies. PU's are defined by coastal areas that have similar characteristics in terms of coastal processes and assets at risk, that can be managed efficiently.

Four policy options are available for SMPs: - Hold the Line (HTL): an aspiration to build or maintain artificial defences so that the current position of the shoreline remains. This can involve maintaining or changing the standard of protection.
- Advance the Line (ATL): by building new defences on the seaward side of the original defences. This is rarely used and is limited to policy units where there is significant land reclamation is considered. There are no policy units in Wales assigned ATL. - Managed Realignment (MR): by allowing the shoreline to move backwards or forwards naturally but managing the process to direct it in certain areas. - No Active Intervention (NAI): where there is no planned investment in coastal defences or operations, regardless of whether or not an artificial defence has existed previously.

The coastal management approach for a certain section of coast may change from the status quo where a policy may no longer be practical or acceptable over 100 years. Therefore, a combination of policies may be proposed over the length of the SMP.

The dataset identifies which of the second-generation Shoreline Management Plans are applicable to a particular stretch of the Welsh coastline and the policies assigned to policy units related to that particular area. This dataset is a polyline, spatial data layer for the Welsh coast only.

This map layer contains the shallowest principal aquifers of the conterminous United States, Hawaii, Puerto Rico, and the U.S. Virgin Islands, portrayed as polygons. The map layer was developed as part of the effort to produce the maps published at 1:2,500,000 in the printed series "Ground Water Atlas of the United States". The published maps contain base and cultural features not included in these data. This is a replacement for the July 1998 map layer called Principal Aquifers of the 48 Conterminous United States.

The data for this project include fields that are output from the numerous CMAQ simulations used to build the RSM. This dataset is not publicly accessible because: The data is too large to be included on ScienceHub. It can be accessed through the following means: This data can be accessed by contacting the corresponding authors as will be noted by the peer-reviewed journal. Format: This data is generated by OAQPS and colleagues at Tsinghua university in China. The output data are stored and, if requested, provided in the format of NetCDF. It is stored and preserved on the Atmos high performance computing (HPC) system located at the National Computing Center (NCC).

The folder location for raw model data and post-processed data is: /asm1/ROMO. The input data is located in the folder titled: /work/ROMO

Data will be copied to the backup automatic storage management (ASM) system after completion of the project to make room for working space on Atmos. This backup system is also located at the National Computing Center, fully accessible form EPA computers at all times and backed up daily or more frequently.

In order to facilitate transparency, reproducibility, and credibility throughout the project, the model code will be appropriately commented to indicate the algorithmic functioning in a manner suitable for the general computer programmer. CMAQ source code will be stored on Github at www.github.com/USEPA/CMAQ on the branch labeled ‘5.3.2’. All substantive evolution of the model code will be documented by comments within the code, and the date of the change will be recorded in the standard logs created by Git version control.

Project documentation is available via https://www.epa.gov/scram

The Africa Soil Profiles Database, Version 1.1, is compiled by ISRIC - World Soil Information (World Data Center for Soils) as a project activity for the Globally integrated- Africa Soil Information Service (AfSIS) project (www.africasoils.net/data/legacyprofile). It replaces version 1.0. The Africa Soil Profiles Database is a compilation of georeferenced and standardised legacy soil profile data for Sub-Saharan Africa. Version 1.1 (March 2013) identifies 16,711 unique soil profiles inventoried from a wide variety of data sources and includes profile site and layer attribute data. Soil analytical data are available for 13,835 profiles of which 12,683 are georeferenced, including the attributes as specified by GlobalSoilMap.net. Soil attribute values are standardized according to SOTER conventions and are validated according to routine rules. Odd values are flagged. The degree of validation, and associated reliability of the data, varies because reference soil profile data, that are previously and thoroughly validated, are compiled together with non-reference soil profile data of lesser inherent representativeness.

This is a polygonal dataset representing the U.S. Coast Guard Captain of the Port Zones throughout the United States. This data was developed by USCG - OSC Enterprise GIS based on Title 33, Code of Federal Regulations Part 3.

VAMC-level statistics on the prevalence, mental health utilization, non-mental health utilization, mental health workload, and psychological testing of Veterans with a confirmed diagnosis of posttraumatic stress disorder (PTSD). Information prepared by the VA Northeast Program Evaluation Center (NEPEC) for fiscal year 2015. This dataset is no longer supported and is provided as-is. Any historical knowledge regarding meta data or it's creation is no longer available. All known information is proved as part of this data set.

description:

Web site for the Center for Women Veterans. Web site includes resources and events for women Veterans.

Web site for the Center for Women Veterans. Web site includes resources and events for women Veterans.