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All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

ECHO Services: Foundational Middleware for a Science Cyberinfrastructure

This viewgraph presentation describes ECHO, an interoperability middleware solution. It uses open, XML-based APIs, and supports net-centric architectures and solutions. ECHO has a set of interoperable registries for both data (metadata) and services, and provides user accounts and a common infrastructure for the registries. It is built upon a layered architecture with extensible infrastructure for supporting community unique protocols. It has been operational since November, 2002 and it available as open source.

Burnett, Michael↗
NASA NTRS2007

Master Metadata Repository and Metadata-Management System

A master metadata repository (MMR) software system manages the storage and searching of metadata pertaining to data from national and international satellite sources of the Global Ocean Data Assimilation Experiment (GODAE) High Resolution Sea Surface Temperature Pilot Project [GHRSSTPP]. These sources produce a total of hundreds of data files daily, each file classified as one of more than ten data products representing global sea-surface temperatures. The MMR is a relational database wherein the metadata are divided into granulelevel records [denoted file records (FRs)] for individual satellite files and collection-level records [denoted data set descriptions (DSDs)] that describe metadata common to all the files from a specific data product. FRs and DSDs adhere to the NASA Directory Interchange Format (DIF). The FRs and DSDs are contained in separate subdatabases linked by a common field. The MMR is configured in MySQL database software with custom Practical Extraction and Reporting Language (PERL) programs to validate and ingest the metadata records. The database contents are converted into the Federal Geographic Data Committee (FGDC) standard format by use of the Extensible Markup Language (XML). A Web interface enables users to search for availability of data from all sources.

Armstrong, Edward↗
NASA NTRS2011

SPASE: The Connection Among Solar and Space Physics Data Centers

The Space Physics Archive Search and Extract (SPASE) project is an international collaboration among Heliophysics (solar and space physics) groups concerned with data acquisition and archiving. Within this community there are a variety of old and new data centers, resident archives, "virtual observatories", etc. acquiring, holding, and distributing data. A researcher interested in finding data of value for his or her study faces a complex data environment. The SPASE group has simplified the search for data through the development of the SPASE Data Model as a common method to describe data sets in the various archives. The data model is an XML-based schema and is now in operational use. There are both positives and negatives to this approach. The advantage is the common metadata language enabling wide-ranging searches across the archives, but it is difficult to inspire the data holders to spend the time necessary to describe their data using the Model. Software tools have helped, but the main motivational factor is wide-ranging use of the standard by the community. The use is expanding, but there are still other groups who could benefit from adopting SPASE. The SPASE Data Model is also being expanded in the sense of providing the means for more detailed description of data sets with the aim of enabling more automated ingestion and use of the data through detailed format descriptions. We will discuss the present state of SPASE usage and how we foresee development in the future. The evolution is based on a number of lessons learned - some unique to Heliophysics, but many common to the various data disciplines.

Thieman, James R.↗
NASA NTRS2005

Towards the Development of a Unified Distributed Date System for L1 Spacecraft

The purpose of this grant, 'Towards the Development of a Unified Distributed Data System for L1 Spacecraft', is to take the initial steps towards the development of a data distribution mechanism for making in-situ measurements more easily accessible to the scientific community. Our obligations as subcontractors to this grant are to add our Faraday Cup plasma data to this initial study and to contribute to the design of a general data distribution system. The year 1 objectives of the overall project as stated in the GSFC proposal are: 1) Both the rsync and Perl based data exchange tools will be fully developed and tested in our mixed, Unix, VMS, Windows and Mac OS X data service environment. Based on the performance comparisons, one will be selected and fully deployed. Continuous data exchange between all L1 solar wind monitors initiated. 2) Data version metadata will be agreed upon, fully documented, and deployed on our data sites. 3) The first version of the data description rules, encoded in a XML Schema, will be finalized. 4) Preliminary set of library routines will be collected, documentation standards and formats agreed on, and desirable routines that have not been implemented identified and assigned. 5) ViSBARD test site implemented to independently validate data mirroring procedures. The specific MIT tasks over the duration of this project are the following: a) implement mirroring service for WIND plasma data b) participate in XML Schema development c) contribute toward routine library.

Lazarus, Alan J.↗
DOE OSTI2026

WHONDRS 2016 Sediment Organic Matter Characterization Data from Streams across HJ Andrews Experimental Forest, Oregon

This dataset supports a broader synoptic effort to map morphological, hydrological, chemical, and biological conditions across a fifth-order mountain stream network. Samples were generated through a collaborative synoptic sampling effort in 2016. The dataset provides sediment Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FTICR-MS) from 60 sites across the HJ Andrews Experimental Forest, Oregon (https://andrewsforest.oregonstate.edu). Related data were collected as part of the event and were published separately in collaboration with other team members. The data are available at http://www.hydroshare.org/resource/ea6c0832885a46c3939e7bb22e48e754 and are described within https://doi.org/10.5194/essd-11-1567-2019 (Ward et al., 2019). The hydroshare data package contains processed FTICR-MS data from the samples included in this data package. The data were processed via Formultitude (previously called Formularity; https://github.com/PNNL-Comp-Mass-Spec/Formultitude). However, we have re-processed the data using Core-MS and included it in this data package. Additional related data collected in 2025 from a similar effort can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/3023310 and http://www.hydroshare.org/resource/b274c4a234bf4b12b7cb8a54a696c629. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of (1) a folder of sample data; (2) data dictionary; (3) file-level metadata; (4); (5) coordinates; and (6) readme. The sample data subfolder contains 12 Tesla (12T) FTICR-MS data. This folder contains the processed data and three subfolders, one containing the .xml files, one containing the CoreMS output files, and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). All files are .csv, .pdf, .R, .xml, .Rmd, .py, .cal, or .json.

Biogeochemistry↗
DOE OSTI2025

mzPeak: Designing a Scalable, Interoperable, and Future-Ready Mass Spectrometry Data Format

Advances in mass spectrometry (MS) instrumentation, such as higher resolution, faster scan speeds, and improved sensitivity, have significantly increased the volume and complexity of data. The growing adoption of imaging and ion mobility further amplifies these challenges across MS-based omics fields, including proteomics, metabolomics, and lipidomics. While these technologies unlock new possibilities, they also present significant challenges in data management, storage, and accessibility. Existing open formats, such as the XML-based community standards mzML and imzML, struggle to meet the demands of modern MS workflows due to their large file sizes, slow data access, and limited metadata support. Vendor-specific formats, while optimized for proprietary instruments, lack interoperability, comprehensive metadata support and long-term archival reliability. This white paper lays the groundwork for mzPeak, a next-generation community data format designed to address these challenges and support high-throughput, multi-dimensional MS workflows. By adopting a hybrid model that combines efficient binary storage for numerical data and both human and machine-readable metadata storage, mzPeak will reduce file sizes, accelerate data access, and offer a scalable, adaptable solution for evolving MS technologies. For researchers, mzPeak will enable enhanced interoperability across platforms, seamless support for complex workflows including ion mobility and MS imaging, and faster data access compared to existing community formats such as mzML. Its design will ensure data is managed in compliance with regulatory standards, essential for applications such as precision medicine and chemical safety, where long-term data integrity and accessibility are critical. For vendors, mzPeak provides a streamlined, open alternative to proprietary formats, reducing the burden of regulatory compliance while aligning with the industry's push for transparency and standardization. By offering a high-performance, interoperable solution, mzPeak positions vendors to meet customer demands for sustainable data management tools which will be able to handle emerging and future data types and workflows. mzPeak aspires to become the cornerstone of MS data management, empowering researchers, vendors, and developers to innovate and collaborate more effectively.

data formats↗
NASA NTRS2008

XTCE and XML Database Evolution and Lessons from JWST, LandSat, and Constellation

The database organizations within three different NASA projects have advanced current practices by creating database synergy between the various spacecraft life cycle stakeholders and educating users in the benefits of the Consultative Committee for Space Data Systems (CCSDS) XML Telemetry and Command Exchange (XTCE) format. The combination of XML for managing program data and CCSDS XTCE for exchange is a robust approach that will meet all user requirements using Standards and Non proprietary tools. COTS tools for XTCEKML are very wide and varied. To combine together various low cost and free tools can be more expensive in the long run than choosing a more expensive COTS tool that meets all the needs. This was especially important when deploying in 32 remote sites with no need for licenses. A common mission XTCEKML format between dissimilar systems is possible and is not difficult. Command XMLKTCE is more complex than telemetry and the use of XTCEKML metadata to describe pages and scripts is needed due to the proprietary nature of most current ground systems. Other mission and science products such as spacecraft loads, science image catalogs, and mission operation procedures can all be described with XML as well to increase there flexibility as systems evolve and change. Figure 10 is an example of a spacecraft table load. The word is out and the XTCE community is growing, The f ~ sXt TCE user group was held in October and in addition to ESAESOC, SC02000, and CNES identified several systems based on XTCE. The second XTCE user group is scheduled for March 10, 2008 with LDMC and others joining. As the experience with XTCE grows and the user community receives the promised benefits of using XTCE and XML the interest is growing fast.

Gal-Edd, Jonathan↗
NASA NTRS2011

SPASE: Current Uses, Tools, and Plans

The Space Physics Archive Search and Extract (SPASE) project is an international collaboration among Heliophysics (solar and space physics) groups concerned with data acquisition and archiving. Within this community there are a variety of old and new data centers, resident archives, "virtual observatories", etc. acquiring, holding, and distributing data. The main product of the SPASE group is an XML-based SPASE Data Model now in operational use to enable searches for and ultimate acquisition of data of interest to a researcher. The SPASE Data Model defines the content of resource descriptions (metadata). The intent is to describe all SCientifically usable Heliophysics data sets using the Data Model. Another product of the SPASE group, in collaboration with NASA's Virtual Observatories, is a set of tools and services which work with SPASE meta data. This includes Registry Services which can retrieve and render metadata using resource identifiers and facilitate the downloading of the data referenced by the meta data. The SPASE Data Model has also been used as a vocabulary in specialized data models. One example is the Heliophysics Event List Manager (HELM) model. The SPASE Data Model is also being expanded to provide the means for more detailed description of data sets with the aim of enabling more automated ingestion and use of the data through detailed format descriptions. The evolution is based on a number of lessons learned and feedback from our community. Some of the lessons learned are unique to Heliophysics, and some are common to the various data diSCiplines. We will discuss the present state of SPASE usage, the role the SPASE Data Model can play in speCialized data models and how we foresee the development direction in the future.

Thieman, J. R.↗
NASA NTRS2010

Common Data Format (CDF) and Coordinated Data Analysis Web (CDAWeb)

The Coordinated Data Analysis Web (CDAWeb) data browsing system provides plotting, listing and open access v ia FTP, HTTP, and web services (REST, SOAP, OPeNDAP) for data from mo st NASA Heliophysics missions and is heavily used by the community. C ombining data from many instruments and missions enables broad resear ch analysis and correlation and coordination with other experiments a nd missions. Crucial to its effectiveness is the use of a standard se lf-describing data format, in this case, the Common Data Format (CDF) , also developed at the Space Physics Data facility , and the use of metadata standa rds (easily edited with SKTeditor ). CDAweb is based on a set of IDL routines, CDAWlib . . The CDF project also maintains soft ware and services for translating between many standard formats (CDF. netCDF, HDF, FITS, XML) <! .

Candey, Robert M.↗
DOE OSTI2025

Organic Matter Composition in June 2023 and September 2023 Across the McKenzie Sub-Basin Impacted by the 2020 Holiday Farm Fire

This dataset represents results from a field study aiming to understand the variability in post-fire responses of dissolved organic matter and determine drivers of post-fire responses. Samples were collected at 58 sites within the McKenzie River Watershed (Oregon, USA) that were upstream, within, and downstream of the Holiday Farm Fire burn perimeter. The samples were collected in June 2023 and September 2023 during storm events, approximately 3 years post-fire. Samples were characterized for benezenepolycarboxylic acids (BPCA) and ultra-high resolution mass spectrometry. Dissolved organic carbon and optics (absorbance and fluorescence) data can be found in a separate data packages (https://ir.library.oregonstate.edu/concern/datasets/zc77sz60m, https://ir.library.oregonstate.edu/concern/datasets/mc87q034m). Related data from a subset of sites from 2020-2022 can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1869708 and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2478546. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset contains (1) file-level metadata; (2) data dictionary; (3) data package readme; (4) metadata; (5) methods information; (6) benzene polycarboxylic acid (BPCA) concentration data; (7) Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) methods; (8) folder of high resolution characterization of organic matter via 12 Tesla FTICR-MS data generated through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). This package contains the following file types: csv, xml, pdf.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2006

Ground Processing of Data From the Mars Exploration Rovers

A computer program implements the Earth side of the protocol that governs the transfer of data files generated by the Mars Exploration Rovers. It also provides tools for viewing data in these files and integrating data-product files into automated and manual processes. It reconstitutes files from telemetry data packets. Even if only one packet is received, metadata provide enough information to enable this program to identify and use partial data products. This software can generate commands to acknowledge received files and retransmit missed parts of files, or it can feed a manual process to make decisions about retransmission. The software uses an Extensible Markup Language (XML) data dictionary to provide a generic capability for displaying files of basic types, and uses external "plug-in" application programs to provide more sophisticated displays. This program makes data products available with very low latency, and can trigger automated actions when complete or partial products are received. The software is easy to install and use. The only system requirement for installing the software is a Java J2SE 1.4 platform. Several instances of the software can be executed simultaneously on the same machine.

Wright, Jesse↗
DOE OSTI2024

Organic Matter Concentration and Composition in November 2021 and April 2022 from 12 Streams Impacted by the 2020 Holiday Farm Fire (v2)

This dataset represents results from a field study aiming to understand storm induced transport of pyrogenic materials to streams impacted by varying degrees of burn severity. Time series samples were collected at 5 sites within the McKenzie River Watershed (Oregon, USA) whose catchment were each completely engulfed by the 2020 Holiday Farm Fire. An additional 7 sites were sampled once during the storm. The samples were collected during storm events in November 2020, January 2021, November 2021, and April 2022. Samples were characterized for benezenepolycarboxylic acids (BPCA), ultra-high resolution mass spectrometry, dissolved organic carbon and optics (absorbance and fluorescence). Fourier-transform ion cyclotron resonance mass spectrometry (FTICR) and dissolved organic carbon data from the November 2020 (referred to as “EWEB_2020”) sampling can be found in a separate data package (doi: 10.15485/1869708). NOTE: The 2020 samples were run on FTICR-MS in two unique instances. The first run can be found in the previous data package (EWEB_2020). The second run is included in this data package. These samples were run for a second time so that the data were more directly interoperable with the other samples in this data package. We have not done any investigation into the differences/similarities between these datasets and the previously ran/published data in the other data package. This data package was originally published in November 2024. It was updated in April 2025 (v2; new and modified files). See the change history section below for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset contains (1) file-level metadata; (2) data dictionary; (3) data package readme; (4) metadata; (5) methods information; (6) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data; (7) excitation emission matrix (EEM) methods; and (8) a sub-folder with processed EEM data (9) benzene polycarboxylic acid (BPCA) concentration data; (10) Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) methods; and (11) folder of high-resolution characterization of organic matter via 12 Tesla FTICR-MS generated through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). The EEMs sub-folder contains two additional folders; the Absorbance and Fluorescence folders which contain the processed EEMs absorbance and fluorescence data respectively. This package contains the following file types: csv, xml, pdf.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

WHONDRS Surface Water and Sediment Geochemistry and Organic Matter Characterization Data from Streams across HJ Andrews Experimental Forest, Oregon (v2)

This dataset supports a broader study developing conceptual models for river corridor critical zone processes across spatial scales and was generated in collaboration with the HJ Andrews River Corridor Critical Zone Workshop in 2025. The dataset provides surface water geochemistry (dissolved organic carbon, total dissolved nitrogen) from 48 sites across the HJ Andrews Experimental Forest, Oregon (https://andrewsforest.oregonstate.edu). Some of the sites have been impacted by the Holiday Farm Fire and the Lookout Fire in 2020 and 2023, respectively. Related data were collected as part of the workshop and will be published separately in collaboration with other workshop attendees and available at http://www.hydroshare.org/resource/b274c4a234bf4b12b7cb8a54a696c629. Related genomic data can be found on the National Center for Biotechnology Information (NCBI) under BioProject PRJNA1503030 (see critical details section below for more information). Additional related data collected in 2016 from a similar effort can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/3377027 and http://www.hydroshare.org/resource/ea6c0832885a46c3939e7bb22e48e754 and are described within https://doi.org/10.5194/essd-11-1-2019 (Ward et al., 2019). This data package was originally published in March 2026. It was updated in August 2026 (v2; new and modified files). See the change history section in the readme for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of (1) a folder of field photos, (2) a folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data, (3) a data checks report, (4) a folder of sample data, (5) file-level metadata, (6) data dictionary, (7) field metadata, (8) readme, (9) international generic sample number (IGSN) mapping file; and (10) field protocol. The sample data subfolder contains surface water and sediment (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages, (2) total dissolved nitrogen data and averages, (3) methods codes, (4) FTICR-MS methods; and (5) a subfolder of 9.4 Tesla (9.4T) FTICR-MS data. This folder contains the CoreMS processed data and seven subfolders, thee containing .xml files for each sample type (sediment, surface water and blank samples), three containing the sediment CoreMS output files for each sample type (sediment, surface water and blank samples), and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). All files are .csv, .pdf, .R, .xml, .Rmd, .py, .cal, .json, .jpg, or .jpeg.

Biogeochemistry↗
DOE OSTI2026

Post-fire time series of sensor and geochemistry sample data from surface water, groundwater, precipitation, soil, and vegetation across Oak Creek watershed, Washington

This dataset supports a broader study examining wildfire impacts on hydrologic connectivity across 5 sites within the Oak Creek watershed and the resulting biogeochemical impacts. Stream sites were selected using the Advanced Terrestrial Simulator (ATS) hydrologic model to identify locations with varying groundwater contributions and hydrologic responses across different burn severity scenarios. The Retreat Fire burned from July 23 to August 2 in 2024, affecting the five study sites at varying burn severities. Each site is equipped with YSI EXO2 sondes logging sub-hourly throughout the year, and grab samples are collected approximately every six weeks. YSI sondes are used to measure temporally resolved proxies for groundwater inputs (specific conductivity) and organic matter (fluorescent dissolved organic matter; fDOM) along with basic water quality and depth. Grab samples of surface water, groundwater, and precipitation are analyzed for water stable isotopes and conductivity to understand endmembers for hydrologic mixing Grab samples of surface water, groundwater, soil water, and litter/vegetation/soil leachates are analyzed for organic matter composition measured by Fourier-Transform Ion Cyclotron Resonance Mass Spectrometry (FTICR-MS) to understand organic matter dynamics. Game camera photos are provided in a separate data package available at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/3018598. Future versions of this dataset will include time series data from YSI EXO2 sondes (fDOM, dissolved oxygen, temperature, depth, specific conductance, turbidity, pH), BaroTROLL sensors (air temperature and barometric pressure), rain gauges (precipitation), and data from the soil and vegetation samples. Because this study is ongoing, this data package will be updated regularly to include newly collected data and the additional data types. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of (1) a folder of field photos; (2) a folder of surface water sample data; (3) a folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data; (4) a data checks report; (5) file-level metadata; (6) data dictionary; (7) field metadata; (8) readme; (9) international generic sample number (IGSN) mapping file; and (10) field protocols. The sample data subfolder contains (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (2) total dissolved nitrogen data and averages; (3) stable water isotopes and averages; (4) methods codes; (5) FTICR-MS methods; and (15) a subfolder of 9.4 Tesla (9.4T) FTICR-MS data. This folder contains the processed data and three subfolders, one containing the .xml files, one containing the water CoreMS output files, and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). All files are .csv, .pdf, .R, .xml, .d, .html, .Rmd, .py, .cal, .json, .jpg, .jpeg, .png, .mov, or .mp4.

Biogeochemistry↗
NASA NTRSDate not supplied

High Performance Access to Archival Data Stored in HDF4 and HDF5 on Cloud Object Stores Without Reformatting the Files

Cloud computing offers numerous advantages for users of extensive Earth science data collections. These benefits encompass direct online access to data files and granules from any location, scalable access supporting parallel computing workflows, and flexible computing tools enabling innovative experimentation with processing techniques. However, older archival file formats designed for distinct computing systems hinder efficient access to decade-long time-series data when compared to data stored in modern cloud-optimized formats like Web Object Stores (WOS), exemplified by Amazon Web Services’ Simple Storage Service (S3). We describe DMR++ (Dataset Metadata Response plus plus), a technology facilitating efficient access to HDF5 (Hierarchical Data Format, version 5) and HDF4 files stored on WOS systems without requiring data reformatting. DMR++ achieves performance comparable to technologies like Zarr while preserving the original file structure, a substantial benefit considering the vast quantity of archival files held by organizations such as NASA. Moreover, DMR++ typically outperforms cloud-optimized versions of HDF5. Essentially an XML (Extensible Markup Language) document usually stored alongside the described data, DMR++ can also be generated on-the-fly but is generally created during data staging to the WOS. Archival files that use HDF4/5 often store large arrays of numerical data. The data in these files is often compressed, typically reducing their size by a factor of four or more. To achieve efficient access to portions of those arrays, they are 'chunked' into smaller sub-arrays, each individually compressed. The chunk size is a compromise, where spinning disks can efficiently access data in smaller chunks while S3 favors larger chunks. A simple optimization of aggregating smaller chunks that are stored adjacently, transferring them in a single access and then individually decompressing them will improve performance. NASA data pose an additional challenge: special Application Programmer Interface (API) libraries are often needed to compute some variables. These libraries are incompatible with WOS environments. Our solution involves storing computed values in the DMR++ document or a companion file, making them accessible like other variables and eliminating the need for specialized APIs. We outline specific optimizations for both satellite grid and swath data stored in HDF4-EOS2 (Earth Observing System).

James Gallagher↗
DOE OSTI2026

WHONDRS Surface Water Geochemistry and Organic Matter Characterization Data from Streams Distributed across Latin America

This dataset supports a broader study examining global transferability of stream biogeochemistry and was generated in collaboration with the MicroSudAqua (µSudAqua) network (https://microsudaqua.netlify.app/en/). The dataset provides surface water geochemistry (dissolved organic carbon, total dissolved nitrogen, cations) and organic matter characterization (FTICR-MS) from streams in Argentina, Brazil, Chile, and Colombia. Samples were collected across stream orders (1st to 6th order) within five basins. Related data were collected and will be published separately in collaboration with the µSudAqua network. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to this readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of (1) a folder of field photos; (2) a folder of surface water sample data, (3) a folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data; (4) file-level metadata; (5) data dictionary; (6) field metadata; (7) readme; (8) international generic sample number (IGSN) mapping file; and (9) field protocol. The sample data subfolder contains (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (2) total dissolved nitrogen data and averages; (3) anions and averages; (4) methods codes; (5) FTICR-MS methods; and (15) a subfolder of 9.4 Tesla (9.4T) FTICR-MS data. This folder contains the processed data and three subfolders, one containing the .xml files, one containing the water CoreMS output files, and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). All files are .csv, .pdf, .R, .xml, .d, .html, .Rmd, .py, .cal, .json, .jpg, .jpeg, .png, .mov, or .mp4.

Anions↗
DOE OSTI2026

WHONDRS River Corridor Surface Water Metabolites and Geochemistry from Global Sites

This dataset supports a broader study examining the character of organic matter that may be delivered to subsurface sediments via hydrologic exchange. To implement the global survey, free stream sampling kits were provided to interested volunteers throughout the world. Samples were collected with minimal constraints in terms of location, but following strict protocols, and shipped for metabolomic analysis via Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). In addition, basic geochemistry analyses (e.g., dissolved organic matter concentration) were conducted, standardized photos of each field system were taken, and extensive metadata were captured. Sampling began in 2018 and is ongoing as of 2025. This dataset is comprised of one folders of field photos, one folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data, and one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) readme; (5) international generic sample number (IGSN) mapping file; (6) field protocol; and (7) a subfolder with sample data. The sample data subfolder contains (1) surface water dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (2) methods codes; (3) surface water FTICR methods; and (4) a subfolder of 12 Tesla (12T) FTICR-MS data. This folder contains three subfolders, one containing the.xml files, one containing the CoreMS output files, and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). All files are .csv, .pdf, .R, .xml, .html, .Rmd, .py, .cal, .json, .jpg, .jpeg, or .png. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About.

Biogeochemistry↗
DOE OSTI2024

Laboratory time series moisture manipulative experiment from sediment across the contiguous US: time series aerobic respiration and geochemistry (v2)

This dataset supports a broader study examining the effects of wetting and drying on hyporheic zone respiration across the contiguous United States (CONUS). The dataset provides data generated from a laboratory moisture manipulation experiment. The contents include time series aerobic respiration and moisture; dissolved oxygen; sediment geochemistry data; and field metadata (including qualitative information on instream and river corridor characteristics). Samples were collected as part of the WHONDRS CONUS-Scale Model-Sample Study (CM). This study was designed following ICON (integrated, coordinated, open, and networked) principles to facilitate a model-experiment (ModEx) iteration approach, leveraging crowdsourced sampling across the CONUS. The data package associated with the CM study is available at https://data.ess-dive.lbl.gov/view/doi:10.15485/1923689. CM sampling began in April 2022 and ended in October 2023. This study uses subsamples from a subset of CM samples collected between June 2022 and June 2023. The original field samples were labeled as CM_###. Subsequent subsamples for this study were labeled as EC_###. The labels from the field samples and the EC subsamples can be mapped directly based on the digits following the prefix and underscore (i.e., EC_001 is a subsample from CM_001). See the critical details section below for more details on sample naming. This data package was originally published in August 2024. It was updated in February 2026 (v2; new and modified files). See the change history section in the readme for more details. For details on how to navigate this data package, see this infographic from the River Corridor SFA https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of one folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data and one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) readme; (5) field protocol; and a (6) a subfolder with sediment sample data from the incubation experiment. The sample data subfolder contains (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC); (2) total nitrogen (TN); (3) adenosine triphosphate (ATP); (4) percent carbon and nitrogen; (5) effect size; (6) iron (II); (7) gravimetric moisture; (8) respiration rates and raw dissolved oxygen values; (9) specific conductance; (10) pH; (11) temperature; (12) a summary containing median values of each data type for each treatment (wet and dry); (13) methods codes; (14) FTICR-MS methods; and (15) a subfolder of 9.4 Tesla FTICR-MS data. This folder contains three subfolders, one containing the sediment .xml data files, one containing the sediment CoreMS output files, the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). All files are .csv, .pdf, .R, .ref, or .xml.

54 ENVIRONMENTAL SCIENCES↗