January Community Webinar

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

View Webinar Video / Link to Webinar Slides

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

Integration of diverse data required for earth science research remains a time-consuming task. While approaches such as data warehousing and federation (brokering) have reduced effort, the difficult work of harmonizing formats, units, and semantics remains for the individual researcher. Often the resulting one-off data synthesis products become outdated as data change. In addition, the researcher does not have flexibility to tailor synthesis to specific data needed.

In this presentation, we describe BASIN-3D (Broker for Assimilation, Synthesis and Integration of eNvironmental Diverse, Distributed Datasets), a tool we developed to address this gap. BASIN-3D synthesizes diverse data from a variety of remote and/or local data sources in real-time without the need for additional storage. The software can be deployed as a python package in python-based applications like Jupyter notebooks or as a web service application. Data sources can be configured using a plugin approach that maps their data model and vocabularies to BASIN-3D’s. These mappings enable BASIN-3D to handle translation of query parameters and results into a standardized data model. BASIN-3D then outputs the synthesized results in common data formats (e.g., hdf5, Pandas dataframe, json) specified by the researcher.

We describe the unique features of BASIN-3D using two prototype U.S. Department of Energy use cases. The first is a python-based application that combines USGS National Water Information Systems NWIS and DayMet time series data to support study of disturbances on river water quality with ML techniques. The second is a Django web-based application that integrates time series data from NWIS and project-based databases for access via an online data portal. Finally, we discuss future work and ongoing challenges such as optimization for large data volumes, adding new data sources, and tradeoffs between generalization and customizability.

 

Community-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 and Climate 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

Findable, Accessible, Interoperable, and Reusable (FAIR) principles are intended to enable the reuse of Earth and environmental science data beyond the purpose for which the data were originally collected. One pathway to making data more reusable is for repositories to encourage contributors to organize and publish data that follow established standards and guidelines. However, Earth science data are diverse and multidisciplinary making it difficult for researchers to determine and use the appropriate standards or formats that apply to their data.

Here, we present 11 reporting formats: instructions, templates, and tools for consistently formatting data, for a diverse set of Earth science (meta)data. These formats were developed through a partnership between the U.S. Department of Energy’s Environmental Systems Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) repository and researchers from its science community. They cover a broad range of Earth science (meta)data that includes cross-domain metadata (dataset metadata, location metadata, sample metadata), file-formatting guidelines (file-level metadata, CSV files, terrestrial model data), and domain-specific formats for biological, geochemical, and hydrological data types (amplicon abundance tables, leaf-level gas exchange, soil respiration, water and sediment chemistry, sensor-based hydrologic measurements). We adopted a community consensus process to develop these formats by obtaining extensive input from 247 researchers across 128 institutions. This resulted in a pragmatic set of reporting formats that are based on scientific use cases. We also describe lessons learned from this process and guidelines that communities can use to create new reporting formats that are tailored to their scientific workflows. Such community-developed reporting formats lend themselves to easy adoption, enabling scientific data synthesis and knowledge discovery by making it easier for data contributors to provide (meta)data that are more FAIR.

 

A FAIR Guided and Community-Oriented 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

The Environmental System Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) data repository stores diverse Earth and environmental science data generated by projects funded by the U.S. Department of Energy (DOE). ESS-DIVE strives to publish datasets that adhere to the FAIR principles, which state that data should be findable, accessible, interoperable, and reusable, and to develop practices that enable data providers to improve the quality of data submissions. However, these strategies must also be able to scale with the growth of the repository, apply to a wide range of data types, and be valuable to both data providers and users.

To address these challenges, we have developed metadata requirements for the ESS-DIVE repository through research into dataset best practices, review of journal metadata requirements, and with community feedback to ensure that they are useful and applicable across data types. We then developed a two-part, semi-automated dataset review workflow that programmatically verifies whether datasets meet metadata quality requirements before publication. The automated component includes FAIR metadata checks developed by the National Center for Ecological Analysis and Synthesis (NCEAS) that were customized to fit ESS-DIVE’s publishing requirements. Results from the automated checks are compiled into a Metadata Assessment Report, providing instant feedback to data providers that identifies where and how their metadata can be improved. ESS-DIVE reviewers then carry out a manual, content-focused metadata review based on FAIR principles. Finally, revision requests are sent by reviewers, who then collaborate 1:1 with data providers until their dataset is eligible for publication.

Since implementation, 401 datasets have been reviewed using the semi-automated dataset review workflow. We have found that incorporating automated metadata validation has reduced review time, allowing the publication workflow to scale as the repository grows and freeing up time for reviewers to interact 1:1 with data providers to improve their publication practices. Finally, by tracking all review results, we are able to make transparent, data based recommendations to our community and continue to improve automation where possible.

 

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 Climate 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 climate and 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 Community 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, Climate and Ecosystem Sciences Division, 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

Did you know that ESS-DIVE can help promote your Environmental System Science datasets and related publications on our website and twitter (@ESSDIVE)? We have already done this with other ESS projects and scientists – see this example tweet on WHONDRS data portal, and this one for a dataset about the impact of freeze-thaw history on soil carbon response. We can promote any research related to datasets that have been published with ESS-DIVE at any time, and especially new ones! 

If you would like us to share your dataset and related publication, let us know by emailing Dylan O’Ryan at ess-dive-outreach@lbl.gov. We will then work with you to get the scoop on your research (aiming for a 200 character tweet), as well as any relevant Twitter handles and hashtags. 

Don’t have your ESS dataset published yet? No problem! Contact us now for help getting started, and visit our website (https://ess-dive.lbl.gov/) for useful resources. If you are ready, submit your dataset today.

September Community Webinar

Tuesday, September 13 | 10:00-11:00 PT / 13:00-14:00 ET

View Webinar Video / Link to Webinar Slides

Did you know that ESS-DIVE’s upgraded Package Service API can help you efficiently search ESS-DIVE data, and get info you need to help prepare your project’s Annual Report? Join our September webinar to learn how to use the API’s new data search capabilities to quickly download dataset files and metadata in bulk, or get a list of the datasets published by your project.  

This webinar is designed for Principal Investigators (PIs), Data Managers, and Software Developers. We will cover the following topics: 

• Brief overview of the ESS-DIVE Package Service API and recent upgrades
• How to use the API for bulk data search and download
• How to use the API to generate csv reports of relevant metadata for published datasets*
• Q&A**

*If you would like to follow along during the webinar, make sure you use your ORCiD to login to ESS-DIVE before we begin (login instructions are available in our documentation)

**This webinar will focus on recent upgrades to the Package Service API, but we can review other API capabilities at the end as needed.

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

 

Webinar will be presented by Madison Burrus Computer Systems Engineer

Madison is a computer systems engineer at Lawrence Berkeley National Lab. She supports ESS-DIVE metadata publication, data pipeline workflows, and feature development. Additionally, she is lead support staff and handles community inquiries. She holds a B.S. in Environmental Science from Stony Brook University.

The Earth Science Information Partners (ESIP) community gathered both virtually and in-person in Pittsburg, PA for the Summer 2022 meeting. The 2022 meeting theme was “Data for All People: From Generation to Use & Understanding.”

Joan Damerow and Dylan O’Ryan from ESS-DIVE attended the meeting virtually, and recap a few takeaway points and resources from the meeting that may be useful for the ESS-DIVE community.

• The Building a Thriving Open Science Community session focused on addressing open science goals, barriers encountered in moving towards Open Science, and trends around the advancement of Open Science practices. A few key themes emerged from the discussion, including the importance of community trust and transparency, and open standards. Mark Parsons shared a graphic that conveyed the importance of both social and technological trust through agreements and standards.
• The Human atlas of Earth science information: a use case for Federated Knowledge Graphs session outlined the potential of federated knowledge graphs to identify and connect related data and information online. The session provided some introductory resources to learn about knowledge graphs (e.g. Intro to Knowledge Graphs Video), and discussed some recent relevant projects in usage based discovery (e.g. NASA EOSDIS Dataset to publication linkages). See graph from Vincent Inverso from NASA depicting connections for research articles. 
• The Towards A Community Guide for FAIR Digital Earth Science Data and Quality Information – Approaches and Practices Promoting Trustworthy FAIR Data and Repositories Session discussed dataset quality and promoting FAIR practices for datasets and repositories. Lightning talks represented relevant projects working towards promoting FAIR data and repository practices – such as NASA’s ECODIS (Earth Observing System Data and Information System) and the USGS State of the Data Project. One referenced journal publication provides guidelines for datasets: FAIR-DQI Guidelines (Findable, Accessible, Interoperable, Reusable) (Dataset Quality Information).
• The How to Use Schema.org on your Dataset Web Pages session provided a great tutorial on using Schema.org, which you can explore here: https://bit.ly/soso-tutorial. ESS-DIVE plans to participate in the Schema.org ESIP cluster towards expanding Science on Schema.org to better connect related data across online data systems for interdisciplinary research.
• During the Defining 5 star data for researchers session, members of the Sustainable Data Management Cluster proposed a star-rating system for data and data repositories, and facilitated feedback on the merits of this approach and potential alternatives. Most agreed that a rating system may not be the best approach, but that simple guidelines may assist researchers in choosing better data repositories for their data publications. The cluster will use feedback from the session to revise simplified guidelines for researchers.
• In the Cite your samples! Drafting guidelines for sample and specimen citation in the earth sciences session, the Physical Samples Curation Cluster reviewed drafted guidelines for sharing sample data in journal publications. Participants also provided updates relevant for sample data curation, such as the AGU session on making samples, specimens and sampled features FAIR.