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Enabling FAIR data in Earth and environmental science with community-centric (meta)data reporting formats

Abstract Research can be more transparent and collaborative by using Findable, Accessible, Interoperable, and Reusable (FAIR) principles to publish Earth and environmental science data. Reporting formats—instructions, templates, and tools for consistently formatting data within a discipline—can help make data more accessible and reusable. However, the immense diversity of data types across Earth science disciplines makes development and adoption challenging. Here, we describe 11 community reporting formats for a diverse set of Earth science (meta)data including cross-domain metadata (dataset metadata, location metadata, sample metadata), file-formatting guidelines (file-level metadata, CSV files, terrestrial model data archiving), and domain-specific reporting formats for some biological, geochemical, and hydrological data (amplicon abundance tables, leaf-level gas exchange, soil respiration, water and sediment chemistry, sensor-based hydrologic measurements). More broadly, we provide guidelines that communities can use to create new (meta)data formats that integrate with their scientific workflows. Such reporting formats have the potential to accelerate scientific discovery and predictions by making it easier for data contributors to provide (meta)data that are more interoperable and reusable.

54 ENVIRONMENTAL SCIENCES↗

Data from: “Enabling FAIR data in Earth and environmental science with community-centric (meta)data reporting formats”

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.

54 ENVIRONMENTAL SCIENCES↗

Data from: "A guide to using GitHub for developing and versioning data standards and reporting formats"

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.

54 ENVIRONMENTAL SCIENCES↗

A Guide to Using GitHub for Developing and Versioning Data Standards and Reporting Formats

Abstract Data standardization combined with descriptive metadata facilitate data reuse, which is the ultimate goal of the Findable, Accessible, Interoperable, and Reusable (FAIR) principles. Community data or metadata standards are increasingly created through an approach that emphasizes collaboration between various stakeholders. Such an approach requires platforms for collaboration on the development process that centers on sharing information and receiving feedback. Our objective in this study was to conduct a systematic review to identify data standards and reporting formats that use version control for developing data standards and to summarize common practices, particularly in earth and environmental sciences. Out of 108 data standards and reporting formats identified in our review, 32 used GitHub as the version control platform, and no other platforms were used. We found no universally accepted methodology for developing and publishing data standards. Many GitHub repositories did not use key features that could help developers to gather user feedback, or to create and revise standards that build on previous work. We provide guidance for community‐driven standard development and associated documentation on GitHub based on a systematic review of existing practices.

54 ENVIRONMENTAL SCIENCES↗

Templates for developing and versioning data standards and reporting formats using GitHub

This data package contains three templates that can be used for creating README files and Issue Templates, written in the markdown language, that support community-led data reporting formats. We created these templates based on the results of a systematic review (see related references) that explored how groups developing data standard documentation use the Version Control platform GitHub, to collaborate on supporting documents. Based on our review of 32 GitHub repositories, we make recommendations for the content of README Files (e.g., provide a user license, indicate how users can contribute) and so 'README_template.md' includes headings for each section. The two issue templates we include ('issue_template_for_all_other_changes.md' and 'issue_template_for_documentation_change.md') can be used in a GitHub repository to help structure user-submitted issues, or can be modified to suit the needs of data standard developers. We used these templates when establishing ESS-DIVE's community space on GitHub (https://github.com/ess-dive-community) that includes documentation for community-led data reporting formats. We also include file-level metadata 'flmd.csv' that describes the contents of each file within this data package. Lastly, the temporal range that we indicate in our metadata is the time range during which we searched for data standards documented on GitHub.

54 ENVIRONMENTAL SCIENCES↗

ESS-DIVE Reporting Format for Hydrologic Monitoring Data and Metadata

The ESS-DIVE Reporting Format (RF) for Hydrologic Monitoring Data and Metadata was designed for water level, temperature, electrical conductivity, specific conductance, dissolved oxygen, and pH measured in situ using sensors deployed in water bodies. It can also be applied to a broader suite of variables beyond its original scope. The RF is intended to provide clear and easy guidance to data generators aiming to upload consistent findable, accessible, interoperable, and reusable (FAIR) datasets. The RF includes instructions (pdf), a term guide (csv), templates (csv and xlsx), and a list of recommended vocabulary (csv) to equip the data generator with all of the tools needed to successfully apply the RF. There is also a crosswalk to some key data resources and standards (csv). Users should cite this dataset when using the RF but are encouraged to access the RF files on GitHub (https://github.com/ess-dive-community/essdive-hydrologic-monitoring) where the RF documentation is maintained and updated on the ESS-DIVE Community Space GitHub. Questions and suggestions for improvement can be submitted as GitHub issues.

54 ENVIRONMENTAL SCIENCES↗

Strawman Philosophical Guide for Developing International Network of GPM GV Sites

The creation of an international network of ground validation (GV) sites that will support the Global Precipitation Measurement (GPM) Mission's international science programme will require detailed planning of mechanisms for exchanging technical information, GV data products, and scientific results. An important component of the planning will be the philosophical guide under which the network will grow and emerge as a successful element of the GPM Mission. This philosophical guide should be able to serve the mission in developing scientific pathways for ground validation research which will ensure the highest possible quality measurement record of global precipitation products. The philosophical issues, in this regard, partly stem from the financial architecture under which the GV network will be developed, i.e., each participating country will provide its own financial support through committed institutions -- regardless of whether a national or international space agency is involved.At the 1st International GPM Ground Validation Workshop held in Abingdon, UK in November-2003, most of the basic tenants behind the development of the international GV network were identified and discussed. Therefore, with this progress in mind, this presentation is intended to put forth a strawman philosophical guide supporting the development of the international network of GPM GV sites, noting that the initial progress has been reported in the Proceedings of the 1st International GPM GV Workshop -- available online. The central philosophical issues themselves, all flow from the fact that each participating institution can only bring to the table, GV facilities and scientific personnel that are affordable to the sanctioning (funding) national agency (be that a research, research-support, or operational agency). This situation imposes on the network, heterogeneity in the measuring sensors, data collection periods, data collection procedures, data latencies, and data reporting capabilities. Therefore, in order for the network to be effective in supporting the central scientific goals of the GPM mission, there must be a basic agreed upon doctrine under which the network participants function vis-a-vis: (1) an overriding set of general scientific requirements, (2) a minimal set of policies governing the free flow of GV data between the scientific participants, (3) a few basic definitions concerning the prioritization of measurements and their respective value to the mission, (4) a few basic procedures concerning data formats, data reporting procedures, data access, and data archiving, and (5) a simple means to differentiate GV sites according to their level of effort and ability to perform near real-time data acquisition - data reporting tasks. Most important, in case they choose to operate as a near real-time data collection-data distribution site, they would be expected to operate under a fairly narrowly defined protocol needed to ensure smooth GV support operations. This presentation will suggest measures responsive to items (1) - (5) from which to proceed,. In addition, this presentation will seek to stimulate discussion and debate concerning how much heterogeneity is tolerable within the eventual GV site network, given that the any individual GV site can only be considered scientifically useful if it supports the achievement of the central GPM Mission goals. Only ground validation research that has a direct connection to the space mission should be considered justifiable given the overarching scientific goals of the mission. Therefore each site will have to seek some level of accommodation to what the GPM Mission requires in the way of retrieval error characterization, retrieval error detection and reporting, and generation of GV data products that support assessment and improvement of the mission's standard precipitation retrieval algorithms. These are all important scientific issues that will be best resolved in open scientific debate.

Smith, Eric A.↗

Stream discharge and temperature data collected within the East and Taylor Watershed, Colorado for the Lawrence Berkeley National Laboratory Watershed Function Science Focus Area (water years 2019 to 2025)

This dataset contains stream discharge and temperature data for water years 2019 to 2025 from the East and Taylor Watersheds in Colorado, United States. This data was collected to understand hydrological processes occurring in the East River and Taylor River Watersheds, Colorado, which is part of the Lawrence Berkeley National Laboratory Watershed Function Scientific Focus Area. Data includes instantaneous observed discharge using salt dilution and acoustic doppler velocimeter techniques, raw pressure transducer downloaded data, sub-hourly temperature as well as corrected water level and associated stream discharge and mean daily values. Notes on water level corrections, rating curve development and metadata provided. A rating curve is the translation of depth to streamflow. The rating curve can be used as a quantitative measure of the “quality of the data.” Data within this dataset is formatted using ESS-DIVE’s Hydrological Monitoring Reporting Format. This data package contains (1) a zip file (Stream_Discharge_Data_WY19-WY25.zip) containing stream discharge and temperature data organized by location; (2) an InstallationMethods file (InstallationMethods.csv) describing metadata about the installation; (3) a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata; (4) a data dictionary (dd.csv) file that contains terms/column_headers used throughout the files along with a definition, units, and data type; (5) a locations metadata file (locations.csv); (6) and a sensor metadata file (sensors.csv). All data files are in non-proprietary formats (csv, png, or pdf formats). Please contact Rosemary Carroll, Curtis Beutler, or Austin Shirley for any support in accessing the files. Update on 2023-05-12: Additional data from WYs 2021 and 2022 were added. Additionally, the dataset was converted using ESS-DIVE’s Hydrological Monitoring Reporting Format. Data files were reformatted to match reporting format guidance, new metadata files were added, and files were converted from excel to CSV. Update on 2025-05-16: Additional data from WYs 2022 (for locations not previously included), 2023, and 2024 were added. An additional descriptive PDF (WFSFA_Streamflow_Hydrograph_Disclaimer.pdf) was added. Metadata files were updated to reflect the addition of new data and locations. Update on 2026-05-18: Additional data from WY 2025 were added, including a new location Upper Trail Creek (TR-TCG2). Metadata files were updated to reflect the addition of new data.

54 ENVIRONMENTAL SCIENCES↗

ESS-DIVE reporting format for leaf-level gas exchange data and metadata

Here we present documentation of the ESS-DIVE reporting format for leaf-level gas exchange data and metadata. This reporting format provides guidance to data contributors on how to store data to maximize their discoverability, facilitate their efficient reuse, and add value to individual datasets. For data users, the reporting format will better allow data repositories to optimize data search and extraction, and more readily integrate similar data into harmonized synthesis products. The reporting format specifies data table variable naming and unit conventions, as well as metadata characterizing experimental conditions and protocols. For common data types that were the focus of this initial version of the reporting format, i.e., survey measurements, dark respiration, carbon dioxide and light response curves, and parameters derived from those measurements, we took a further step of defining required additional data that would maximize the potential reuse of those data types. To aid data contributors and the development of data ingest tools by data repositories we provided a translation table comparing the outputs of common gas exchange instruments. The reporting format presented here is intended to form a foundation for future development that will incorporate additional data types and variables as gas exchange systems and measurement approaches advance in the future. The reporting format documentation is maintained and updated on the ESS-DIVE Community Space GitHub. This data package is the first published version of this reporting format, and comprises a zip file of the complete content of https://github.com/ess-dive-community/essdive-leaf-gas-exchange v1.0. The zip contains the reporting format description, guidelines, variable tables and instructions in GitHub markdown language (*.md) and 2 metadata templates as spreadsheets with drop down options (*.xlsx files, also function in GoogleSheets).

54 ENVIRONMENTAL SCIENCES↗

ESS-DIVE Unoccupied Aerial Systems (UAS) Reporting Format v1

Here we present documentation of the ESS-DIVE reporting format for Unoccupied Aerial System (UAS) data and metadata. This reporting format provides guidance to data contributors on how to store data to maximize their discoverability, facilitate their efficient reuse, and add value to individual datasets. For data users, the reporting format will better allow data repositories to optimize data search and extraction, and more readily integrate similar data into harmonized synthesis products. The reporting format provides templates and guidance for the reporting of metadata for UAS experimental campaigns, individual flights, platform and sensor description. To improve data access and discoverability, the reporting format proposes a data description scheme of Levels based on the degree of processing, where Level 0 includes raw data, through to Level 3 being derived data end products. A range of examples of data types for each Level are given, with suggested file naming schemes. The reporting format presented here is intended to form a foundation for future development that will accommodate new UAS technologies and approaches to data access and use in the future. The reporting format documentation is maintained and updated on the ESS-DIVE Community Space GitHub at https://github.com/ess-dive-community/essdive-uas. This data package is the first published version of this reporting format, and comprises a zip file of the complete content of https://github.com/ess-dive-community/essdive-uas v1.0. The zip contains the reporting format description, instructions and variable definitions in GitHub markdown language (*.md) and metadata templates in csv format. The reporting format is designed to be compatible with other ESS-DIVE formats, and it is specifically recommended that this reporting format be used in conjunction with the File-level metadata (FLMD) and comma separated values (csv) reporting formats for submission to the ESS-DIVE repository.

54 ENVIRONMENTAL SCIENCES↗

ESS-DIVE reporting format for field measurements of soil respiration

This is a new data and metadata reporting format for soil respiration data, based on engagement with a wide range of researchers in the earth and ecological sciences as well as expert advisory panels. Reporting formats are intended to be ‘bottom-up’, community-developed documents and templates that can enable consistent, findable, accessible, interoperable, and reproducible (FAIR) data; our goal was a reporting format that would be relevant and useful for synthesis activities, optimizing data discoverability and usability while not placing an undue burden on data contributors. The format is split into two levels of information—metadata about chambers (used to measure soil respiration in the field), and the measured data themselves. The file data_reportingformat_template.xlsx contains information on how the data table should be structured, including field names, field descriptions, and units; the chammetadata_reportingformat_template.xlsx file contains similar information for the chamber-level metadata. Fundamentally, this format aims to enable FAIR data through an easy-to-use guide for data providers interested in formatting their data in a common way, and provide ‘future-proofing’ capabilities to support reanalyses of soil respiration data, a globally-important component of the carbon cycle.

54 ENVIRONMENTAL SCIENCES↗

Electric Vehicle Charging Analytics and Reporting Tool (EV-ChART): Data Format and Preparation Guidance (V.5.0)

The Joint Office of Energy and Transportation maintains the Electric Vehicle Charging Analytics and Reporting Tool (EV-ChART), which provides a centralized hub for submitting electric vehicle (EV) charging infrastructure data directed by the Federal Highway Administration (23 CFR 680.112(a)-(c)). EV-ChART provides a streamlined data submission process and an integrated set of analytic tools, connects to other data sources, and empowers data sharing and access across stakeholders, including the public. Any data shared publicly will be aggregated and anonymized to stay in accordance with 23 CFR 680. This EV-ChART Data Format and Preparation Guidance provides a comprehensive overview of the data reporting requirements as authorized under 23 CFR 680.112(a)-(c)). The guidance is intended to be used alongside the EV-ChART Data Input Template, which defines the tabular data structure that these data submissions must follow. Per 23 CFR 680.112(a)-(c), the annual and quarterly data submissions are required of all National Electric Vehicle Infrastructure (NEVI) Formula Program projects, as well as projects for the construction of publicly accessible EV chargers that are funded with funds made available under Title 23, United States Code, including any EV charging infrastructure project funded with federal funds that is treated as a project on a federal-aid highway. One-time data submissions are required of both the NEVI Formula Program projects and grants awarded under 23 U.S.C. 151(f) for projects that are for EV charging stations located along and designed to serve the users of designated Alternative Fuel Corridors (AFCs). Other information and data required in 23 CFR 680, such as 23 CFR 680.112(d), 23 CFR 680.116(c), and 23 CFR 680.106(a), are not discussed in this guidance.

33 ADVANCED PROPULSION SYSTEMS↗

Electric Vehicle Charging Analytics and Reporting Tool (EV-ChART): Data Format and Preparation Guidance, Version 2.0

The Joint Office of Energy and Transportation maintains the Electric Vehicle Charging Analytics and Reporting Tool (EV-ChART), which provides a centralized hub for submitting electric vehicle (EV) charging infrastructure data directed by the Federal Highway Administration (23 CFR 680.112) EV-ChART will provide a streamlined data submission process and an integrated set of analytic tools, connect to other data sources, and empower data sharing and access across stakeholders, including the public. Any data shared publicly will be aggregated and anonymized to stay in accordance with 23 CFR 680. This EV-ChART Data Format and Preparation Guidance provides a comprehensive overview of the data reporting requirements as authorized under 23 CFR 680.112. The guidance is intended to be used alongside the EV-ChART Data Input Template, which defines the tabular data structure that these data submissions must follow.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗

ESS-DIVE Reporting Format for Sample-based Water and Soil Chemistry Measurements

The ESS-DIVE (Environmental Systems Science Data Infrastructure for a Virtual Ecosystem) reporting format for sample-based water and soil chemistry measurements are written guidelines and spreadsheet templates, that facilitate archiving water/soil/sediment chemistry data. The templates and terminology lists provided as part of the reporting format can help organize data and potentially enable data reuse.The reporting format consists of a general instructions file (instructions.md) as well as more detailed instructions files for each template (files beginning “Detailed_Instructions_*.md). The “examples” folder includes an example of each data template with just the limited set of required fields filled out as well as other examples with both required and optional fields complete.The 'templates' folder contains CSV templates for data, methods, and terminology file templates. Similar to the examples folder, the blank templates are provided with versions for required fields only as well as required and optional fields. Lastly, the term list folder provides common terminology used in each of the templates as well as a definition and any constraints for the fields.

54 ENVIRONMENTAL SCIENCES↗

Cation Data for the East River Watershed, Colorado (2014-2025)

This data package contains mean values for cation concentration for water samples taken from the East River Watershed in Colorado. Inductively coupled plasma mass spectrometry (ICP-MS) has been used to measure the concentrations of elements of interest simultaneously for the East River Watershed, Colorado groundwater and surface water samples to inform insights on the biogeochemistry processes within the watershed. The East River is part of the Watershed Function Scientific Focus Area (WFSFA) located in the Upper Colorado River Basin, United States. For samples collected prior to 06-16-2021, the instrumentation, Elan DRC II, PerkinElmer SCIEX, automatically switches among the three models necessary to analyze all 37 elements. These 37 elements include: (1) Lithium (Li), Beryllium (Be), Boron (B), Sodium (Na), Magnesium (Mg), Aluminium (Al), Silicon (Si), Phosphorus (P), Titanium (Ti), Cobalt (Co), Nickel (Ni), Copper (Cu), Zinc (Zn), Germanium (Ge), Arsenic (As), Rubidium (Rb), Strontium (Sr), Zirconium (Zr), Molybdenum (Mo), Silver (Ag), Cadmium (Cd), Tin (Sn), Antimony (Sb), Caesium (Cs), Barium (Ba), Europium (Eu), Lead (Pb), Thorium (Th), Uranium (U) using standard model, argon Ar as reaction gas, (2) Potassium (K), Calcium (Ca), Vanadium (V), Chromium (Cr), Manganese (Mn), Iron (Fe) using dynamic reaction cell (DRC) model, ammonia NH3 as reaction gas, and (3) Phosphorus (P) and Selenium (Se) using DRC model, oxygen O2 as reaction gas. Note for the samples with higher concentrations of chloride (Cl-), asenic (As) concentrations were analysed with DRC model (oxygen O2 as reaction gas) to avoid the interference of chloride. For samples collected on and after 06-16-2021, an advanced Agilent 8900 triple quadrupole inductively coupled plasma mass spectrometry system (Agilent 8900 QQQ ICP-MS, Agilent Technologies) has been used to measure the concentrations of interested 36 elements simultaneously for environmental samples, including (1) Lithium (Li), Beryllium (Be) and Boron (B) using standard no gas mode, (2) Sodium (Na), Magnesium (Mg), Aluminium (Al) Phosphorus (P), Potassium (K), Chromium (Cr), Manganese (Mn), Iron (Fe), Cobalt (Co), Nickel (Ni), Copper (Cu), Zinc (Zn), Germanium (Ge), Arsenic (As), Rubidium (Rb), Strontium (Sr), Zirconium (Zr), Molybdenum (Mo), Silver (Ag), Cadmium (Cd), Tin (Sn), Antimony (Sb), Cesium (Cs), Barium (Ba), Europium (Eu), Lead (Pb), Thorium (Th) and Uranium (U) using standard helium (He) collision mode, (3) Titanium (Ti) and Vanadium (V) using high Energy (HEHe) helium (He) collision mode, and (4) Silicon (Si), Calcium (Ca) and Selenium (Se) using standard H2 reaction mode. All samples were prepared/diluted with 2% (v/v) ultrapure nitric acid in Milli-Q water (18.2 mega ohm-cm), and analyzed under a rigorous quality assurance and quality control (QA/QC) process. This data package contains (1) a zip file (cation_data_2014_2025.zip) containing a total of 5,849 files: 5.848 data files of cation data from across the Lawrence Berkeley National Laboratory (LBNL) Watershed Function Scientific Focus Area (SFA) which is reported in .csv files per location and a locations.csv (1 file) with latitude and longitude for each location; (2) a file-level metadata (v6_20260901_flmd.csv) file that lists each file contained in the dataset with associated metadata; (3) a data dictionary (v6_20260901_dd.csv) file that contains terms/column_headers used throughout the files along with a definition, units, and data type; (4) PDF and docx files for the detemination of Method Detection Limits (MDLs) for ICP-MS PerkinElmer DRC II instrumentation (Detemination_of_Method_Detection_Limits__MDLs__for_ICP_MS__PerkinElmer_Elan_DRC_II__LBL_Bldg74_Lab214D) for samples before November 2021; (5) PDF and docx files for the determination of MDLs for ICP-MS Agilent 8900 QQQ instrumentation (ICP_MS_Analysis_detection_limits_and_QA_QC_WenmingDong_updated_2026-08-06) for samples November 2021 and onward. Missing values within the anion data files are noted as either "-9999" or "0.0" for not detectable (N.D.) data. There are a total of 113 locations containing cation data. Update on 2021-04-11: Added Detemination of Method Detection Limits (MDLs) for ICP-MS document, which can be accessed as a PDF or with Microsoft Word. Update on 2022-06-10: versioned updates to this dataset was made along with these changes: (1) updated cation data for all locations up to 2021-12-31, (2) removal of units from column headers in datafiles, (3) added row underneath headers to contain units of variables, (4) removed suffix and prefix on two variables (“aqberylliumion_asberyllium” and “aqlithiumion_aslithium”), (5) added -9999 for empty numerical cells, and (6) the addition of the file-level metadata (flmd.csv) and data dictionary (dd.csv) were added to comply with the File-Level Metadata Reporting Format. Update on 2022-09-09: Updates were made to reporting format specific files (file-level metadata and data dictionary) to correct swapped file names, add additional details on metadata descriptions on both files, add a header_row column to enable parsing, and add version number and date to file names (v2_20220909_flmd.csv and v2_20220909_dd.csv). Update on 2023-08-08: Updates were made to both the data files and reporting format specific files. New available anion data was added, up until 2023-01-05. The file level metadata and data dictionary files were updated to reflect the additional data added. Update on 2024-03-11: Updates were made to both the data files and reporting format specific files. New available anion data was added, up until 2023-10-16. Further, revisions to the data files were made to remove incorrect data points (from 1970 and 2001). The reporting format specific files were updated to reflect the additional data added. Updated versions of the PDF and docx files for determination of MDLs for ICP-MS data were added to this dataset for samples starting in November 2021. Update on 2025-05-15: Updates were made to both the data files and reporting format specific files. New available cation data was added, up until the end of WY2024 (September 30, 2024). International Generic Sample Numbers (IGSNs), when registered, were added to the data files. The reporting format specific files were updated to reflect the additional data added. Update on 2026-09-01: Updates were made to both the data files and reporting format specific files. New available cation data was added, up until the end of WY2025 (September 30, 2025). Updated versions, as of 2026-08-06, of the PDF and docx files for determination of MDLs for ICP-MS data were added to this dataset for samples starting in November 2021.

54 ENVIRONMENTAL SCIENCES↗