This dataset contains supplementary information for a manuscript describing the ESS-DIVE (Environmental Systems Science Data Infrastructure for a Virtual Ecosystem) data repository's community data and metadata reporting formats. The purpose of creating the ESS-DIVE reporting formats was to provide guidelines for formatting some of the diverse data types that can be found in the ESS-DIVE repository. The 6 teams of community partners who developed the reporting formats included scientists and engineers from across the Department of Energy National Lab network. Additionally, during the development process, 247 individuals representing 128 institutions provided input on the formats.The primary files in this dataset are 10 data and metadata crosswalk for ESS-DIVE’s reporting formats (all files ending in _crosswalk.csv). The crosswalks compare elements used in each of the reporting formats to other related standards and data resources (e.g., repositories, datasets, data systems). This dataset also contains additional files recommended by ESS-DIVE’s file-level metadata reporting format. Each data file has an associated dictionary (files ending in _dd.csv) which provide a brief description of each standard or data resource consulted in the data reporting format development process. The flmd.csv file describes each file contained within the dataset.

The ESS-DIVE sample identifiers and metadata reporting format primarily follows the System for Earth Sample Registration (SESAR) Global Sample Number (IGSN) guide and template, with modifications to address Environmental Systems Science (ESS) sample needs and practicalities (IGSN-ESS). IGSNs are associated with standardized metadata to characterize a variety of different sample types (e.g. object type, material) and describe sample collection details (e.g. latitude, longitude, environmental context, date, collection method). Globally unique sample identifiers, particularly IGSNs, facilitate sample discovery, tracking, and reuse; they are especially useful when sample data is shared with collaborators, sent to different laboratories or user facilities for analyses, or distributed in different data files, datasets, and/or publications. To develop recommendations for multidisciplinary ecosystem and environmental sciences, we first conducted research on related sample standards and templates. We provide a comparison of existing sample reporting conventions, which includes mapping metadata elements across existing standards and Environment Ontology (ENVO) terms for sample object types and environmental materials. We worked with eight U.S. Department of Energy (DOE) funded projects, including those from Terrestrial Ecosystem Science and Subsurface Biogeochemical Research Scientific Focus Areas. Project scientists tested the process of registering samples for IGSNs and associated metadata in workflows for multidisciplinary ecosystem sciences.more » We provide modified IGSN metadata guidelines to account for needs of a variety of related biological and environmental samples. While generally following the IGSN core descriptive metadata schema, we provide recommendations for extending sample type terms, and connecting to related templates geared towards biodiversity (Darwin Core) and genomic (Minimum Information about any Sequence, MIxS) samples and specimens. ESS-DIVE recommends registering samples for IGSNs through SESAR, and we include instructions for registration using the IGSN-ESS guidelines. Our resulting sample reporting guidelines, template (IGSN-ESS), and identifier approach can be used by any researcher with sample data for ecosystem sciences.« less

The following dataset is a collection of twelve anonymously gathered responses from scientists and technicians working with Environmental Science Sensor Networks Collecting in-situ time Series data. Specifically, the survey which produced this dataset was distributed to two working groups associated with the organization of Earth Science Information Partners: the Envirosensing Cluster and the Documentation Cluster.This survey was crafted to hopefully provide a picture of what metadata management and creation looks like for professionals working with environmental sensor data.

Our dataset are transcripts and codebooks for a focus group study. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. EPA cannot release CBI, or data protected by copyright, patent, or otherwise subject to trade secret restrictions. Request for access to CBI data may be directed to the dataset owner by an authorized person by contacting the party listed. It can be accessed through the following means: Contact Katie Williams, williams.kathleen@epa.gov. Format: The data are transcripts and protected by IRB approvals. This dataset is associated with the following publication: Eisenhauer, E., K. Williams, K. Margeson, S. Paczuski, K. Mulvaney, and M.C. Hano. Advancing translational research in environmental science: The role and impact of social science. Environmental Science & Policy. Elsevier Science Ltd, New York, NY, USA, 120: 165-172, (2021).

Datafiles in TXT file formats listing PFAS chemicals and a list of all PFAS Chemical Lists publicly available on the CompTox Chemicals Dashboard. This dataset is associated with the following publication: Williams, A., L. Gaines, C. Grulke, C. Lowe, G. Sinclair, V. Samano, I. Thillainadarajah, B. Meyer, G. Patlewicz, and A. Richard. Assembly and Curation of Lists of Per- and Polyfluoroalkyl Substances (PFAS) to Support Environmental Science Research. Frontiers in Environmental Science. Frontiers, Lausanne, SWITZERLAND, 10: 850019, (2022).

This data collection contains Hydrodynamic Model output data produced by the Sydney Harbour Hydrodynamic Model.

The Sydney Harbour (real-time) model collates observations from the Bureau of Meteorology, Macquarie University, Sydney Ports Authority and the Manly Hydraulics Laboratory offshore buoy. The Sydney Harbour Model is contained within the Sydney Harbour Observatory (SHO) system.

The Sydney Harbour Hydrodynamic Model divides the Harbour water into a number of boxes or voxels. Each voxel is less than 60m x 60m x 1m in depth. In narrow parts of the Harbour, or in shallower regions, the voxels are smaller. Layers are numbered - so the sea floor is number 1 and the surface is number 24.

The model is driven by the conditions on the boundaries. It uses rainfall rates at 13 sites in the Sydney catchment, the wind speed, tide height, the solar radiation and astronomical tides. Every hour the display is refreshed.

The model utilizes the following environmental data inputs;

• Dr Serena Lee provide the following: 24 layer grid of the Sydney Harbour Estuary, bathymetry inputs, and the run-off coefficient formula used to convert rainfall readings provided by the Bureau of Meteorology into boundary input data.
• The Bureau of Meteorology provides the following model inputs; rainfall from 13 individual rain gauges, air temperature, humidity, barometric pressure, cloud cover, evaporation, wind speed, wind direction and forecast data
• Sydney Ports Authority provides tidal input data.
• The Office of Environment and Heritage, and the Manly Hydraulics Laboratory provides ocean boundary temperature input data.
• Macquarie University provides solar radiation input data.

The hydrodynamic modeling system models the following environmental variables:

• Salinity
• Temperature
• Depth average salinity
• Horizontal water velocity
• Vertical water velocity
• Depth average north velocity
• Depth average east velocity
• Water elevation

This dataset is available in Network Common Data Form – Climate and Forecast (NetCDF-CF) format.

Acknowledgement: The NEAD format includes NetCDF metadata and is proudly inspired by both SMET and NetCDF formats. NEAD is designed as a long-term data preservation and exchange format. The NEAD specifications were presented at the "WMO Data Conference 2020 - Earth System Data Exchange in the 21st Century" (Virtual Conference). ----------------------- Summary: The Non-Binary Environmental Data Archive (NEAD) format is being developed as a generic and intuitive format that combines the self-documenting features of NetCDF with human readable and writeable features of CSV. It is designed for exchange and preservation of time series data in environmental data repositories. License: The NEAD specifications are released to the public domain under a Creative Commons 4.0 CC0 "No Rights Reserved" international license. You can reuse the information contained herein in any way you want, for any purposes and without restrictions.

This CD-ROM (Compact Disk - Read Only Memory) contains sidescan sonar, high-resolution seismic-reflection, bathymetric, textural, and bibliographic data and interpretations collected, compiled, and produced through the U.S. Geological Survey/State of Connecticut Cooperative and the Long Island Sound Environmental Studies Project of the Coastal and Marine Geology Program, U.S. Geological Survey during October 1991 to August 1998. Cooperative research with the State of Connecticut was initiated in 1982. During the initial phase of this cooperative program, geologic framework studies in Long Island Sound were completed. The second and current phase of the program, which is the focus of this CD-ROM, emphasizes studies of sediment distribution, processes that control sediment distribution, near-shore environmental concerns, and the relationship of benthic communities to sea-floor geology. The study area covers all of Long Island Sound, which is bordered on the north by the rocky shoreline of Connecticut, on the east by Block Island Sound, on the south by the eroding sandy bluffs of Long Island, and on the west by the East River and the New York metropolitan area. Sidescan sonar data were variously collected with 100 kHz Klein, Datasonics, and Edgetech systems under two survey schemes. In the first scheme, the data were collected along closely-spaced grids where the ship tracks were spaced 150 m apart and the sonar system was set to sweep 100 m to either side of the ship's track. This scheme produced the continuous-coverage acoustic images that are stored on the CD-ROM as TIF files. In the second scheme, the sidescan sonar data collected along reconnaissance lines spaced about 2,400 m apart. Only selected portions of this data, when used for geologic interpretation, are stored on this CD-ROM. Under both survey schemes, the sidescan sonar data were processed according to procedures summarized by Danforth and others (1991) and Paskevich (1992a, 1992b, 1992c). The seismic reflection data were variously collected with an Ocean Research Equipment 3.5-kHz profiler transmitting at a 0.25-s repetition rate and a Datasonics CHIRP system set to sweep between 2-7 kHz. Only selected seismic-reflection data, which are used as examples in geologic interpretations, are stored as GIF-formatted images on this CD-ROM. Navigation during this project was determined with a differential Global Positioning System (GPS); position data were logged at 10-second intervals. The bathymetric data were collected by means of a 200-kHz echo sounder and logged digitally. Surficial sediment (0-2 cm below the sediment-water interface) sampling completed as part of this project was conducted using a Van Veen grab sampler equipped with an Osprey video and still camera system. The photographic system was used to appraise bottom variability around stations, faunal communities, and sedimentary processes. It also documented bedrock outcrops and boulder fields where samples could not be collected. The fine fraction (less than 62 microns) was analyzed by Coulter Counter (Shideler, 1976); the coarse fraction was analyzed by sieving (gravel) and by rapid sediment analyzer (sand; Schlee, 1966). The data were corrected for the salt content of interstitial water. Size classifications are based on the method proposed by Wentworth (1929) and were calculated using the inclusive graphics statistical method (Folk, 1974), using the nomenclature proposed by Shepard (1954). A detailed discussion of the sedimentological methods employed are given in Poppe and others (1985); a detailed description of the methods used to perform the CHN analyses are given in Poppe and others (1996) . The database presented here contains over 14,000 records and 83 fields (see the Data Dictionary below). The specific fields and parameters have been chosen based on the data produced by the sedimentation laboratory of the Coastal and Marine Geology Program of the U.S. Geological Survey in Woods Hole, Mass., and the format of information typically found in the literature. Because the data have come from numerous sources, there are differing amounts and types of information. Most of the samples or sets of samples do not have data in all of the given fields. However, additional fields, qualifiers, and data can be added in virtually unlimited fashion to accommodate specific needs. The database itself is provided in four formats: Microsoft EXCEL, ver. 5, Quattro Pro for Windows, Dbase IV, and Tab-delimited ASCII text. Four bathymetric data sets are presented and include:1) Interpretations of the bathymetry within the continuous-coverage sidescan sonar study areas; 2} The NOS database modified to remove extraneous data (i.e. bouys); 3) Contoured National Ocean Service (NOS) bathymetry digitized by Applied Geographics Inc., Boston, Massachusetts; and 4) a fly-by based on the modified NOS database. Data files are present in ASCII format with navigation and depth in meters. The bathymetric interpretations within the sidescan sonar study areas are based on mean sea level and stored as TIF images; the NOS data are based on mean low sea level; and the fly-by is configured to run in QuickTime or MPEG, which can be downloaded from this CD-ROM. The bibliographic database, which contains over 2,000 references, is stored as an ASCII text, Microsoft Word, Corel WordPerfect, HTML, and Microsoft EXCEL files. This bibliography is largely a compilation of references from Lewis and Coffin (1985) and the GENCAT bibliographic database at the Long Island Sound Resource Center, Connecticut Department of Environmental Protection, Groton, Connecticut. These sources have been supplemented by citations from the BIOSIS, GEOREF, and FISH AND FISHERIES WORLDWIDE bibliographic databases.

The manuscript and accompanying talk for the International Congress on Environmental Modeling and Software on building informatics infrastructure to support the integration of models and data. Please cite as: "Hart, E.M., Fox, A., Berukoff, S., Hoar, T., 2014 Integrating NEON data with existing models: An example with the Community Land Model In: Ames, D.P., Quinn, N.W.T., Rizzoli, A.E. (Eds.), Proceedings of the 7th International Congress on Environmental Modelling and Software, June 15-19, San Diego, California, USA. http://www.iemss.org/society/index.php/iemss-2014-proceedings"

The ESS-DIVE reporting format for file-level metadata (FLMD) provides granular information at the data file level to describe the contents, scope, and structure of the data file to enable comparison of data files within a data package. The FLMD are fully consistent with and augment the metadata collected at the data package level. We developed the FLMD template based on a review of a small number of existing FLMD in use at other agencies and repositories with valuable input from the Environmental Systems Science (ESS) Community. Also included is a template for a CSV Data Dictionary where users can provide file-level information about the contents of a CSV data file (e.g., define column names, provide units). Files are in .csv, .xlsx, and .md. Templates are in both .csv and .xlsx (open with e.g. Microsoft Excel, LibreOffice, or Google Sheets). Open the .md files by downloading and using a text editor (e.g. Notepad or TextEdit). Though we provide Excel templates for the file-level metadata reporting format, our instructions encourage users to 'Save the FLMD template as a CSV following the CSV Reporting Format guidance'. In addition, we developed the ESS-DIVE File Level Metadata Extractor which is a lightweight python script that can extract some FLMD fields following the recommended FLMD format and structure.

This dataset contains Ocean Color (OC) Science Quality Environmental Data Records (EDR) Level-3 products from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi-National Polar-orbiting Partnership (SNPP) satellite. Level-3 EDR data are produced by NOAA CoastWatch/OceanWatch (CW) from Level-2 products. The Level-2 OC EDR are produced by NESDIS Center for Satellite Applications and Research (STAR) OC team using the Multi-Sensor Level-1 to Level-2 (MSL12) ocean color data processing system. Science quality OC EDR are produced using the significantly improved VIIRS Sensor Data Records (SDR or Level-1B data), which are generated by the OC team (named OC-SDR) using both the solar and lunar approaches, and assimilated ancillary input data (as opposed to model predicted data used in near-real time data production). MSL12 and the OC-SDR calibration improvements were developed by the STAR OC team [Wang et al., 2013; Sun and Wang, 2015; Wang et al., 2016; Wang et al., 2017]. The Science Quality Level-2 VIIRS OC EDR are produced daily on a delayed mode (present day minus 15 days) with global spatial coverage. In addition to this forward stream processing, a consistent, full-mission dataset was generated with the same processing covering the time period from the first post-launch useable data in January 2012 to present day minus 15 days and also with global spatial coverage. The CW Level-3 processing uses MSL12 version 1.2 Level-2 (the swath or granule data) as input to produce global mapped 4 km spatial resolution, daily, weekly and monthly time binned (averaged) output data product files in NetCDF format. These CW Level-3 products include the following parameters: normalized water-leaving radiances for 6 VIIRS visible bands (i.e., bands M1-M5 at 410 nm, 443 nm; 486 nm; 551 nm; 671 nm respectively and band I1 at 638 nm), chlorophyll-a concentration (Chl-a), the diffuse attenuation coefficient at 490 nm (Kd(490)), and the diffuse attenuation coefficient for photosynthetically available radiation (Kd(PAR)). Note that the MSL12 is the NOAA enterprise processing system for all OC data (from multiple sensors and/or satellite missions) which has replaced the Integrated Data Processing Segment (IDPS) from the Joint Polar Satellite System (JPSS) program for VIIRS data. These Level-3 records are a primary source of information for numerous regional and global marine resource stewardship efforts and are used in applications in support of the NOAA mission and other applications such as fish stock assessments, local habitat characterization, phytoplankton pigment concentration and whale distribution, weather predictions and forecasting, as well as basic physical and biological oceanographic studies of our changing ocean environments. For additional information about OC data, other data formats and a variety of search tools, visit CoastWatch.NOAA.gov.

Code and data for 'Forest types for afforestation: benefits for Carbon sequestration and food systems under stringent climate mitigation'

These data are the results of a systematic review that investigated how data standards and reporting formats are documented on the version control platform GitHub. Our systematic review identified 32 data standards in earth science, environmental science, and ecology that use GitHub for version control of data standard documents. In our analysis, we characterized the documents and content within each of the 32 GitHub repositories to identify common practices for groups that version control their documents on GitHub.In this data package, there are 8 CSV files that contain data that we characterized from each repository, according to the location within the repository. For example, in 'readme_pages.csv' we characterize the content that appears across the 32 GitHub repositories included in our systematic review. Each of the 8 CSV files has an associated data dictionary file (names appended with '_dd.csv' and here we describe each content category within CSV files.There is one file-level metadata file (flmd.csv) that provides a description of each file within the data package.

This dataset contains Ocean Color (OC) Science Quality Environmental Data Records (EDR) Level-2 products from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi-National Polar-orbiting Partnership (SNPP) satellite. The Level-2 OC EDR are produced by NESDIS Center for Satellite Applications and Research (STAR) OC team using the Multi-Sensor Level-1 to Level-2 (MSL12) ocean color data processing system. Science quality OC EDR are produced using the significantly improved VIIRS Sensor Data Records (SDR or Level-1B data), which are generated by the OC team (named OC-SDR) using both the solar and lunar approaches, and assimilated ancillary input data (as opposed to model predicted data used in near-real time data production). MSL12 and the OC-SDR calibration improvements were developed by the STAR OC team [Wang et al., 2013; Sun and Wang, 2015; Wang et al., 2016; Wang et al., 2017]. The Science Quality Level-2 VIIRS OC EDR are produced daily on a delayed mode (present day minus 15 days) with global spatial coverage at 750 m spatial resolution at nadir. In addition to this forward stream processing, a consistent, full-mission dataset was generated with the same processing covering the time period from the first post-launch useable data in January 2012 to present day minus 15 days, also with global spatial coverage. The Level-2 (swath or granule data) processing uses MSL12 version 1.2 and generates the following standard products at the nominal 750 m resolution in NetCDF format: normalized water-leaving radiances for 6 VIIRS visible bands (i.e., bands M1-M5 at 410 nm, 443 nm, 486 nm, 551 nm, and 671 nm, respectively, and band I1 at 638 nm), chlorophyll-a concentration (Chl-a), the diffuse attenuation coefficient at 490 nm wavelength (Kd(490)), the diffuse attenuation coefficient for photosynthetically available radiation (Kd(PAR)), and a quality score product (QA Score). Note that the MSL12 is the NOAA enterprise processing system for all OC data (from multiple sensors and/or satellite missions) which has replaced the Integrated Data Processing Segment (IDPS) from the Joint Polar Satellite System (JPSS) program for VIIRS data. These Level-2 records are a primary source of information for numerous regional and global marine resource stewardship efforts and are used in applications in support of the NOAA mission and other applications such as fish stock assessments, local habitat characterization, phytoplankton pigment concentration and whale distribution, weather predictions and forecasting, as well as basic physical and biological oceanographic studies of our changing ocean environments. For additional information about OC data, other data formats and a variety of search tools, visit CoastWatch.NOAA.gov.

This dataset contains key characteristics about the data described in the Data Descriptor A harmonised, high-coverage, open dataset of solar photovoltaic installations in the UK. Contents: 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format

Acoustic Doppler current profiler (ADCP) surveys for submerged portions of cross-section 3 (XS3) on Mission River at Fennessey Ranch. Cross-section surveys were conducted using a SonTek M9 RiverSurveyor. Six channel transects with the ADCP are used to represent the submerged topography at XS3. Seven types of data formats (csv, mat, riv, snr, sum, vel, wsp) are included in this data set. csv is a comma separated tabular file that contains summary and measurement information for each transect in ascii file format. mat is a tabular file that contains summary and measurement information for each transect in the proprietary MATLAB file format. riv is a tabular file that contains real-time measurement information for each transect in the proprietary SonTek file format. snr is a tabular file that contains information on the signal-to-noise ratios associated with the measurements for each transect in the ascii file format. sum is a tabular file that contains summary information for the measurements of each transect in the ascii file format. vel is a tabular file of the flow velocities measured along each in the ascii file format. wsp is file used in the post-processing of files from a transect measurement in the proprietary SonTek file format.

This dataset contains key characteristics about the data described in the Data Descriptor Domestic waste emissions to European waters in the 2010s. Contents: 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format Versioning Note:Version 2 was generated when the metadata format was updated from JSON to JSON-LD. This was an automatic process that changed only the format, not the contents, of the metadata.

ESS-DIVE’s (Environmental Systems Science Data Infrastructure for a Virtual Ecosystem) dataset metadata reporting format is intended to compile information about a dataset (e.g., title, description, funding sources) that can enable reuse of data submitted to the ESS-DIVE data repository. The files contained in this dataset include instructions (dataset_metadata_guide.md and README.md) that can be used to understand the types of metadata ESS-DIVE collects. The data dictionary (dd.csv) follows ESS-DIVE’s file-level metadata reporting format and includes brief descriptions about each element of the dataset metadata reporting format. This dataset also includes a terminology crosswalk (dataset_metadata_crosswalk.csv) that shows how ESS-DIVE’s metadata reporting format maps onto other existing metadata standards and reporting formats.Data contributors to ESS-DIVE can provide this metadata by manual entry using a web form or programmatically via ESS-DIVE’s API (Application Programming Interface). A metadata template (dataset_metadata_template.docx or dataset_metadata_template.pdf) can be used to collaboratively compile metadata before providing it to ESS-DIVE.Since being incorporated into ESS-DIVE’s data submission user interface, ESS-DIVE’s dataset metadata reporting format, has enabled features like automated metadata quality checks, and dissemination of ESS-DIVE datasets onto other data platforms including Google Dataset Search and DataCite.

Data and code for "Spatial and temporal expansion of global wildland fire activity in response to climate change" by Martin Senande-Rivera, Damian Insua-Costa and Gonzalo Miguez-Macho Data formats: netcdf and csv Codes: Python v3.8

The Environmental Research Division's Data Access Program (ERDDAP) is a data server that provides a simple, consistent way to download subsets of scientific datasets in common file formats and make graphs and maps. This particular ERDDAP installation has oceanographic data (for example, data from satellites and buoys). It acts as a middleman between users and various remote data servers by unifying the different types of data servers to provide a consistent way to get desired data in the desired format.