ESS-DIVE Webinar

Monday, February 27 | 10:00-11:00 PT / 13:00-14:00 ET

View Webinar Recording / Link to Webinar Slides

ESS-DIVE is excited to welcome Urban Integrated Field Laboratory (Urban IFL) projects to DOE ESS. We invite all who are part of an Urban IFL project and broader ESS researchers to an introductory webinar about the ESS-DIVE data repository for Earth and environmental system science data, and associated resources for project data management. We will also have a discussion on data management needs for Urban IFL projects.  

We will cover the following topics:

• Overview of ESS-DIVE and our data;
• ESS-DIVE project data management features; 
• Resources to organize and curate high-quality datasets; and
• Discussion on Urban IFL data management needs.

Please encourage anyone from your project who may be interested to attend. 

The webinar will be presented by Joan Damerow and Emily Robles.

Joan Damerow, Lead Scientist

Joan is an environmental scientist with a background in geoscience sampling, freshwater ecology, and biodiversity informatics. She runs activities for ESS-DIVE, including ESS-DIVE webinars, our annual data workshop, and is active in relevant conferences and data working groups (e.g. ESIP, RDA, AGU). Joan is interested in interdisciplinary data management and tracking, and works with DOE ESS data contributors to identify, develop, and implement practical data standards in ESS-DIVE that support FAIR principles.

Emily Robles, Data Management Research Associate

Emily is a research associate and a member of ESS-DIVE’s team. Her work with ESS-DIVE focuses on utilizing research and feedback to implement a comprehensive data package review workflow for data publication. She has experience with data package organization and quality management as a member of the NGEE Tropics data team and received her BS in Environmental Science from the University of California, Berkeley.

ESS-DIVE Webinar

Monday, January 30 | 10:00-11:00 PT / 13:00-14:00 ET

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Are you interested in publishing or using data from small Unoccupied Aerials Systems (UAS)? With rapid development of platform and sensor technologies, the use of UASs, also known as UAVs or drones, in Earth sciences is becoming increasingly common. This webinar will review the new UAS data and metadata reporting format that is in development, and provide you an opportunity to give feedback.

We will cover the following topics:

• Benefits of using reporting formats,
• Types of data that this format will cover and associated challenges,
• Metadata variables to describe flight details and equipment, 
• Categorizing data by processing level, and
• Discussion and feedback. 

You can review the draft UAS data and metadata reporting format before the webinar, although this is not required to attend.  This webinar will be presented by Kim Ely and Shawn Serbin from Brookhaven National Laboratory (BNL).

Please encourage anyone from your project who may be interested to attend.

The ESS-DIVE Team is looking forward to participating in the 2022 AGU Fall Meeting. Below are several abstracts that we will be presenting at the meeting!

BASIN-3D: Data Synthesis Software for Earth Science Researchers (H12P-0874)

Presenter: Danielle Christianson
Presentation Type: Poster
Session Date and Time: Monday, 12 December 2022; 9:00 AM – 12:30 PM CST / 7:00 AM – 10:30 AM PST
Session Number and Title: H12P: Hydroinformatics and Data Science: Pathways to Support Reproducible Watershed Modeling II Poster
Session URL: https://agu.confex.com/agu/fm22/webprogrampreliminary/Paper1153073.html

Abstract

Danielle S Christianson, Valerie C Hendrix, Catherine Wong, Charuleka Varadharajan, and Deb Agarwal, Lawrence Berkeley National Laboratory, Berkeley, CA, United States

 

Developed (meta)data reporting formats to enable data reuse in environmental repositories (IN41A-06)

Presenter: Charuleka Varadharajan
Presentation Type: Online Poster Discussion
Session Date and Time: Thursday, 15 December 2022; 8:40 AM – 8:48 AM CST / 6:40 AM – 6:48 AM PST
Session Number and Title: IN41A: Adopting Trustworthy Data Repository Stewardship to Enable Reuse of Data Across Disciplines I Online Poster Discussion
Session URL: https://agu.confex.com/agu/fm22/webprogrampreliminary/Paper1163669.html

Abstract

Charuleka Varadharajan¹, Robert Crystal-Ornelas¹, Dylan O’Ryan², Bond-Lamberty Benjamin³, Kathleen Beilsmith⁴, Kristin Boye⁵, Madison Burrus¹, Shreyas Cholia¹, Danielle S Christianson¹, Michael Cameron Crow⁶, Joan E Damerow¹, Kim S Ely⁷, Amy E Goldman⁸, Susan L Heinz⁹, Valerie C Hendrix¹, Zarine Kakalia¹, Kayla Cerise Mathes¹⁰, Fianna O’Brien¹, Stephanie C Pennington^11,12, Emily Robles¹, Alistair Rogers⁷, Maegen Simmonds^1,13, Terri Velliquette⁶, Pamela Weisenhorn¹⁴, Jessica Nicole Welch⁶, Karen Whitenack¹ and Deb Agarwal¹, (1)Lawrence Berkeley National Laboratory, Berkeley, CA, United States, (2)Lawrence Berkeley National Lab, Berkeley, CA, United States, (3)Pacific Northwest National Laboratory, College Park, MD, United States, (4)Argonne National Laboratory, Chicago, United States, (5)SLAC National Acceleratory Laboratory, Stanford Synchrotron Radiation Lightsource, Menlo Park, CA, United States, (6)Oak Ridge National Laboratory, Oak Ridge, TN, United States, (7)Brookhaven National Laboratory, Environmental Sciences Department, Upton, NY, United States, (8)Pacific Northwest National Laboratory, Biological Sciences, Richland, WA, United States, (9)Oak Ridge National Laboratory, Oak Ridge, United States, (10)Virginia Commonwealth University, Integrative Life Sciences, Richmond, VA, United States, (11)Pacific Northwest National Laboratory, College Park, United States, (12)Joint Global Change Research Institute, College Park, United States, (13)Pivot Bio, Berkeley, United States, (14)Argonne National Laboratory, Argonne, IL, United States

 

A FAIR Guided Approach to Improving Metadata Quality in a Large Scale Data Repository (IN41A-03)

Presenter: Emily Robles
Presentation Type: Online Poster Discussion
Session Date and Time: Thursday, 15 December 2022; 8:16 AM – 8:24 AM CST / 6:16 AM – 6:24 AM PST
Session Number and Title: IN41A: Adopting Trustworthy Data Repository Stewardship to Enable Reuse of Data Across Disciplines I Online Poster Discussion
Session Link: https://agu.confex.com/agu/fm22/webprogrampreliminary/Paper1199893.html

Abstract

Emily Robles¹, Charuleka Varadharajan¹, Madison Burrus¹, Shreyas Cholia¹, Robert Crystal-Ornelas¹, Joan E Damerow¹, Hesham Elbashandy¹, Valerie C Hendrix¹, Christopher S. Jones², Matthew B. Jones³, Zarine Kakalia¹, Mario Melara¹, Fianna O’Brien¹, Peter Slaughter², Karen Whitenack¹ and Deb Agarwal¹, (1) Lawrence Berkeley National Laboratory, Berkeley, CA, United States, (2) National Center for Ecological Analysis and Synthesis, Santa Barbara, CA, United States, (3) National Center for Ecological Analysis and Synthesis, DataONE, Santa Barbara, CA, United States

 

Enabling proper Citation of Individual Objects Across Large Collections of Datasets (IN42B-0338)

Presenter: Deb Agarwal
Presentation Type: Poster
Session Date and Time: Thursday, 15 December 2022; 9:00 AM – 12:30 PM CST / 7:00 AM – 10:30 AM PST
Session Number and Title: IN42B: Adopting Trustworthy Data Repository Stewardship to Enable Reuse of Data Across Disciplines II Poster
Session Link: https://agu.confex.com/agu/fm22/webprogrampreliminary/Paper1188622.html

Abstract

Deb Agarwal¹, Martina Stockhause², Lesley A Wyborn³, Justin James Henry Buck⁴, James Ayliffe⁴ and Shelley Stall⁵, (1) Lawrence Berkeley National Laboratory, Berkeley, CA, United States, (2) German Computing Centre (DKRZ), Hamburg, Germany, (3) Australian National University, Canberra, ACT, Australia, (4) National Oceanography Center, BODC, Liverpool, United Kingdom, (5) American Geophysical Union, Data Leadership, Washington, DC, United States

 

Sample tracking and synthesis needs for exploring ecosystem response to environmental disturbance (IN55A-03)

Presenter: Joan Damerow
Presentation Type: Oral
Session Date and Time: Friday, 16 December 2022; 3:06 PM – 3:14 PM CST / 1:06 PM – 1:14 PM PST
Session Number and Title: IN55A: Global Efforts to Make Samples, Specimens, and Sampling Features (As Well Digital Information About Them) Comply with the FAIR and CARE Principles III Oral
Session Link: https://agu.confex.com/agu/fm22/webprogrampreliminary/Paper1121127.html

Abstract

Joan E Damerow¹, Elisha M Wood-Charlson¹, Charuleka Varadharajan¹, Mikayla Borton², Eoin Brodie³, Richard S. Canon⁴, Shreyas Cholia¹, Paramvir Dehal⁵, Zachary Crockett⁶, Emiley Eloe-Fadrosh⁷, Ricardo J Eloy Alves⁸, Kjiersten Fagnan⁷, Amy E Goldman⁹, David Hays¹⁰, Valerie C Hendrix¹, Lee Ann McCue¹¹, Nancy Shiao-Lynn Merino¹², Marka Miller⁴, Chris Mungall¹³, Supratim Mukherjee¹⁰, T.B.K. Reddy¹⁰, Patrick Sorensen³, Montana L Smith¹⁴, James Stegen¹⁵, Pajau Vangay⁴, Pamela Weisenhorn¹⁶, Steven Wilson¹⁷ and Deb Agarwal¹, (1) Lawrence Berkeley National Laboratory, Berkeley, CA, United States, (2) Colorado State University, Soil and Crop Sciences, Fort Collins, United States, (3) Lawrence Berkeley National Laboratory, Earth and Environmental Sciences Area, Berkeley, CA, United States, (4) Lawrence Berkeley National Laboratory, Berkeley, United States, (5) Lawrence Berkeley National Lab, Berkeley, United States, (6) Oak Ridge National Laboratory, Oak Ridge, United States, (7) Joint Genome Institute, Walnut Creek, CA, United States, (8) Lawrence Berkeley National Laboratory, CESD, Berkeley, CA, United States, (9) Pacific Northwest National Laboratory, Biological Sciences, Richland, WA, United States, (10) Joint Genome Institute, Berkeley, United States, (11) Pacific Northwest National Lab, Richland, United States, (12) Lawrence Livermore National Laboratory, Livermore, United States, (13) Lawrence Berkeley National Laboratory, Environmental Genomics and Systems Biology, Berkeley, United States, (14) Pacific Northwest National Laboratory, Environmental Molecular Sciences Laboratory, Richland, United States, (15) Pacific Northwest National Laboratory, Richland, United States, (16) Argonne National Laboratory, Argonne, IL, United States, (17)Joint Genome Institute, Berkeley, CA, United States

Earth and environmental systems science (ESS) research is evidence-based and relies on the analysis and modeling of heterogeneous and multi-scale datasets. The volume of ESS data has risen sharply in recent years, with more data gathered by the minute. This may come as positive news—however, much of this data remains unarchived, difficult to access, and even unusable. Among other challenges, many scientists lack the resources and ability to archive and share their data using consistent methods. Earth science has moved toward adopting Findable, Accessible, Interoperable, and Reusable (FAIR) data principles to solve this problem.

A new paper authored by the Earth and Environmental Systems Science for a Virtual Ecosystem (ESS-DIVE) team seeks to address these issues and presents 11 novel reporting formats for organizing and describing various types of Earth science data in public databases. Published in Scientific Data, the ready-to-use formats are available in the ESS-DIVE data repository, as well as on ESS-DIVE’s Workspace GitHub. ESS-DIVE provides a centralized location to store and share open and standardized datasets to enhance scientific collaboration and data reuse.

“This publication is the result of a dedicated and collaborative effort across six U.S. DOE national labs, and a testament to the value of computational and Earth science researchers partnering for positive impact,” said Charuleka Varadharajan, a Scientist in the Earth and Environmental Sciences Area at Berkeley Lab, and lead of its Earth AI and Data program. “These reporting formats come at a time when they are urgently needed to enable our ability to extract insights from complex environmental systems data.”

A DOE ESS effort for a FAIRer future 

Supported by the U.S. Department of Energy (DOE) Office of Science Biological and Environmental Program, ESS-DIVE brought together teams of scientists across the DOE National Lab Network with the aim of helping researchers within DOE ESS provide more standardized and well-described data. Together, they identified and created instructions and templates for formatting heterogeneous environmental data types. The DOE ESS-centered process involved reviewing over 100 existing data standards, conventions, or other reporting formats—and receiving input from 247 scientists representing 100+ institutions.

“A highlight of the reporting format development process was monthly meetings that convened many of the scientists leading the reporting format development process,” says Robert Crystal-Ornelas. “During these working sessions, we could harmonize on key terminology relevant across reporting formats, and share successes and challenges with the broader reporting format group.”

Covering data types commonly used by DOE, some of the reporting formats are intended to standardize commonly used descriptions about the data, referred to as “metadata,” such as information about the dataset locations and samples from where the data were generated. Others provide instructions for formatting and describing data files such as the comma-separated value (CSV) format or guidelines for organizing model data.  The other reporting formats are more domain-specific and focused on data types of importance to ESS research such as leaf-level gas exchange, soil respiration, water and sediment chemistry, hydrologic monitoring, and microbial amplicon abundances.

Crystal-Ornelas also stated that the scale of the outreach and input received on the reporting formats underscores how big a need there was for this type of standardization within Earth and environmental sciences. He’s excited to see the formats used by researchers around the world, including inputs from across and outside of the National Lab Network.

Shreyas Cholia, Group Leader for the Integrated Data Systems Group (Scientific Data Division) at Berkeley Lab, said: “ESS-DIVE is designed as a scalable framework that allows data providers to contribute standardized, structured, and high-quality data. The reporting formats are a vitally important contribution that supports long-term data stewardship. reproducible research, and data standardization across DOE ESS.”

This collaborative approach paves the way for future innovation around FAIRer data and may serve as a model for other organizations that would like to develop (meta)data reporting formats for other types of data.