The Tethys database houses the metadata associated with the acoustic data collection efforts by the Passive Acoustic Group. These metadata include dates, locations and sampling rate, among other things.

The database platform itself was developed by colleagues at San Diego State University, and is freely available and open source. See citation details for website link.

This dataset is part of the database compiled as an outcome of Work Area 1 in project OrganicYieldsUP. This Excel file describes the content of the OYUP relational database for each table and column.

The main sheet "table_schema_oyup" contains:

The additional sheet "quality_indicator_description" contains:

Stores physical and logical information about relational databases and record structures to assist in data identification and management.

Metadata for the 16,012 microbial samples included in this database. Metadata was collated from the originally published studies, available supplementary information, and from online databases

The full metadata database for all other items in this collection. Created in Microsoft Excel and exported here as an XML spreadsheet. This database is a working catalog of material in this collection. The earliest version of the database are the 01 files. Subsequent versions have increasingly higher numbers in the file names.. Language as given:

Compiled spatial database for pondscapes obtained from PONDERFUL partner countries containing spatial data and attributes of the ponds. The spatial distribution of the pondscapes in Europe were obtained from global and local databases. Database consists of spatial information such as latitude and longitude of the ponds in geographic coordinates, name, code, land cover, intensity, hydro period, surface area, perimeter, maximum depth, mean depth, altitude, measurement year, created year, information about work packages and installed sensor information. A web application has been developed to display spatial distribution and available information of ponds from the individual countries. The application allows users to dynamically visualize the ponds and download pond’s available data, hydro period information and pond database spatially. Web application can be accessed from the following link: https://ponderful.hidrosaf.com/

This fileset provides supporting data and corpora for the empirical study described in:Rafael S. Gonçalves and Mark A. Musen. The variable quality of metadata about biological samples used in biomedical experiments. Scientific Data, in press (2019).Description of filesAnalysis spreadsheet files:- ncbi-biosample-metadata-study.xlsx contains data to support the analysis of the quality of metadata in the NCBI BioSample.- ebi-biosamples-metadata-study.xlsx contains data to support the analysis of the quality of metadata in the EBI BioSamples.Validation data files:- ncbi-biosample-validation-data.tar.gz is an archive containing the validation data for the analysis of the entire NCBI BioSample dataset.- ncbi-biosample-packaged-validation-data.tar.gz is an archive containing the validation data for the analysis of the subset of metadata records in the NCBI BioSample that use a BioSample package definition.- ebi-ncbi-shared-records-validation-data.tar.gz is an archive containing the validation data for the analysis of the set of metadata records that exist both in EBI BioSamples and NCBI BioSample.Corpus files:- ebi-biosamples-corpus.xml.gz corresponds to the EBI BioSamples corpus.- ncbi-biosample-corpus.xml.gz corresponds to the NCBI BioSample corpus.- ncbi-biosample-packaged-records-corpus.tar.gz corresponds to the NCBI BioSample metadata records that declare a package definition.- ebi-ncbi-shared-records-corpus.tar.gz corresponds to the corpus of metadata records that exist both in NCBI BioSample and EBI BioSamples.

The SEABORNE (Sustainable UsE And Benefits fOR mariNE) has consolidated and synthesised existing information about who is using the Reef, how it is being used and what the benefits are from this use. SEABORNE began in November 2021, and initially, we were provided with a list of potential datasets relevant to our project in a spreadsheet. To this, we continued to search various data portals online and find additional datasets relevant to our project, particularly focusing on the Great Barrier Reef. We recorded these initially in an Excel spreadsheet. We then transferred this to an MS Access database and developed a more user-friendly entry form. Within the MS Access database, there is one table that stores all the metadata records entered. And another table that stores the static preview images. There are 58 fields (which have been described in a data dictionary) – some of these are mandatory. At the moment there are 3 metadata records entered and we expect this to grow to 50-100 records by the completion of the project. Lineage: Data was produced by examining each of the datasets metadata and documenting various features of each of the individual datasets and how useful they were for examining ecosystem services. Data was initially entered in excel, then migrated to MS Access database, and then imported or read in by SHiny R app.

Abstract

This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied.

The Database of Communities of National Environmental Significance stores maps, taxonomic, ecological, and management information about Communities of National Environmental Significance listed in the Environment Protection and Biodiversity Conservation (EPBC) Act 1999 as threatened ecological communities.

Credit:

State and Commonwealth Herbaria, Museums and Conservation Agencies Centre for Plant Biodiversity Research Australian Government Department of the Environment, Environmental Resources Information Network

External accuracy:

The positional accuracy of spatial data is a statistical estimate of the degree to which planimetric coordinates and elevations of features agree with their real world values. The planimetric accuracy attainable in the vector data will be composed of errors from three sources:

1. The positional accuracy of the source material

2. Errors due to the conversion processes.

3. Errors due to the manipulation processes.

This specification cannot prescribe a figure for the planimetric accuracy of the existing source material used for capture of community distributions as it has already been produced. The errors due to the digitising process depend on the accuracy of the digitising table set-up or the scanner resolution, systematic errors in the equipment, errors due to software and errors specific to the operator. An accepted standard for digitising is that the line accuracy should be within half a line width.

Non Quantitative accuracy:

Tests are undertaken to ensure that there are no errors in attributes:

• The spatial resolution of the data is reflected in the Presence Categories

• Presence categories are one of:

* Community known to occur within area

* Community likely to occur within area

* Community may occur within area (general indication only)

Conceptual consistency:

Tests undertaken for logical consistency:

• Names of export files and data quality table are correct

• Table names are valid

• Item names in coverages are valid

• Item names are present in coverage attribute files

• Label points and entity point features have only one coordinate pair

• The Arc/Info coverages can be generated, have attributes attached and be 'built'

• In polygon coverages there are no label errors i.e. every polygon has one and only one polygon label point

• Data format, projection and data type are correct

• There are no overshoots, i.e. arc overhangs at intersections (1% error acceptable)

• There are no undershoots, i.e. arcs failing to meet at intersections (0.5% error acceptable)

• There are no new polygons smaller than the minimum specified area (5% error acceptable)

• There are no new linear features shorter than the minimum length (5% error acceptable)

• There are no artefacts such as spikes or deviations visible at 1:125 000 (5% error acceptable)

• Separate covers have exactly coincident lines where intended (5% error acceptable)

Completeness omission:

The database is continually being updated as the lists of threatened ecological communities on schedules of the EPBC Act are amended.

The Species of National Environmental Significance database is available at

https://www.environment.gov.au/science/erin/databases-maps/snes

Dataset History

This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied.

The Spatial information is stored in a geographic information system and links to the Species Profile tables through the community identifier.

Source data were provided from a range of government, industry and non-government organisations.

Testing is carried out using a combination of expert opinion and on-screen checks.

Dataset Citation

Department of the Environment (2015) Communities of National Environmental Significance Database - RESTRICTED - Metadata only. Bioregional Assessment Source Dataset. Viewed 13 March 2019, http://data.bioregionalassessments.gov.au/dataset/c01c4693-0a51-4dbc-bbbd-7a07952aa5f6.

A manually curated registry of standards, split into three types - Terminology Artifacts (ontologies, e.g. Gene Ontology), Models and Formats (conceptual schema, formats, data models, e.g. FASTA), and Reporting Guidelines (e.g. the ARRIVE guidelines for in vivo animal testing). These are linked to the databases that implement them and the funder and journal publisher data policies that recommend or endorse their use.

In most democracies, the public record of legislative votes in national and local parliaments is an important basis for holding elected officials accountable. In political science, that record is also an important source of data on legislator and party behavior. In practice, many legislatures create a public record of the votes cast by individual legislators for only a fraction of the issues on which votes occur. These recorded votes often are not a representative sample of all votes cast and may exhibit systematic biases that have implications for political accountability and for the science of political behavior. Therefore, understanding the characteristics of the issues that receive a publicly recorded vote (a roll-call vote) is essential to our understanding of democratic processes and evaluating the limits of scientific inferences that can be drawn from roll-call data. This data set advances our understanding of the voting record through examination of national parliamentary bodies around the world.

The file provides information about available data sources for forest managers. It covers intentory, lidar, remote sensing, and other useful data for forest management. It is identified the extent of the data, and include links to the general web site and specific databases in some cases.

A description of biological and ecological data of the Danube delta lakes and channels is presented. The biological indicators refer to aquatic macrophytes, fish, zoo-plankton, and macro-invertebrates. Environmental data include physio-chemical data as well as hydrological parameters. More information on this dataset can be found in the Freshwater Metadatabase - MARS_12 (http://www.freshwatermetadata.eu/metadb/bf_mdb_view.php?entryID=MARS_12

Gms-index-mediator is a standalone index for spatio-temporal data acting as a mediator between an application and a database. Even modern databases need several minutes to execute a spatio-temporal query to huge tables containing several million entries. Our index-mediator speeds the execution of such queries up by several magnitues, resulting in response times around 100ms. This version is tailored towards the GeoMultiSens database, but can be adapted to work with custom table layouts with reasonable effort.

Each year the Council publishes an annual report on the implementation of regulation 1049/2001 on access to documents. The annual report contains statistical information on the requests for public access received by the Council. With the exception of personal data, information on such requests is public. This dataset contains the following information on the requests for public access to documents received by the Council: 1. General information on the applicant (anonymous): professional activity of applicant; geographic origin 2. General Information on the request: request number; type of request (initial request, confirmatory application); date of request; deadline to reply; extended deadline to reply; date of reply; effort spent; follow-up; policy area(s). 3. Information on the requested documents: publication status (public or not); type of reply; document category; document number

This data describe the abundance of individual lichen species across the U.S. as recorded in the Forest Health and Monitoring dataset of the Forest Inventory and Analysis program (i.e. Phase 3 plots). This dataset is not publicly accessible because: These data are already housed on the USFS Forest Inventory and Analysis site (see below). It can be accessed through the following means: The lichen data for this product are from the USDA Forest Services (USFS) Forest Inventory and Analysis (FIA) Phase 3 (P3) dataset - Forest Health and Monitoring. The metadata and database description for the FIA-P3 is here (https://res1wwwd-o-tfiad-o-tfsd-o-tfedd-o-tus.vcapture.xyz/library/database-documentation/). The data itself is located at the USFS Data Mart here (https://res1appsd-o-tfsd-o-tusdad-o-tgov.vcapture.xyz/fia/datamart/CSV/datamart_csv.html) in two files: “LICHEN_PLOT_SUMMARY.zip,” and “LICHEN_VISIT.zip.” Point of contact: Linda Geiser, lgeiser@fs.fed.us. Format: The data are in .csv format.

Ocean Data View software (ODV, http://odv.awi.de/), has to be used for visualization. Follow the instructions to install the software and in menu File>open choose the file IBAMar_metadata.odv. You will observe a map with the station distribution and a box indicating the metadata variables. […]

Usefulness of metadata in the automatic version of ACMANTv5 was tested.
A benchmark database has been developed, which consists of 41 datasets
of 20,500 networks of 170,000 synthetic monthly temperature time series
and the relating metadata dates. The research was supported by the
Catalan Meteorological Service. The research results will be published
in the open access MDPI journal Atmosphere.

See more in the "Readme.txt" file of the dataset.

File1: Contains information about Multidrug resistance result

This database (2004) is the only harmonized soil database for Europe, extending also to Eurasia. It contains a soil geographical database SGDBE (polygons) to which a number of essential soil attributes are attached, and an associate database PTRDB, with attributes which values have been derived through pedotransfer rules. Also part of the database is the Soil Profile Analytical Database, that contains measured and estimated soil profiles for Europe.