2021 ESIP Winter Meeting

The Physical Samples Curation Cluster is a forum for the community supporting physical samples in the earth, space, and environmental sciences which includes but is not limited to geological and biological samples.  The cluster’s goal is to enhance discoverability, access, and use of sample collections.

At the ESIP 2020 Summer session, we brought together those interested in physical samples to discuss developing a centralized space within ESIP, which resulted in the founding of this cluster. In addition, we created a list of community needs and issues which we might tackle as a community.

The goal of our inaugural session will be to review these potential actives and discuss next steps. The list includes developing a webinar series to highlight existing tools and services, and creating working groups to address topics such as metadata interoperability, resources and infrastructure, and identifiers and citations.

We invite researchers, professionals such as curators, collection managers, and registrars, cyberinfrastructure providers and developers, and the user community to join this session to help shape the future of this cluster.

Agenda

• Introduction (10 minutes)
• Presentation on FAIR (10 minutes)
• Breakout activity to design cluster working group activities:
  • Introduction to breakout activity (5 minutes)
  • Breakout group discussions (25 minutes)
  • Group reports; 3 minutes per group (12 minutes)
  • Community discussion on group recommendations (20 minutes)
• Wrapup (8 minutes)

How to Prepare for this Session: Review the Cluster statement and the meeting notes from the ESIP 2020 Summer Session. These two documents will provide foundation for the discussions during the session.

Session Resources

• View Recording
  
• Meeting notes
• Session slides
• FAIR presentation
• Breakout slides
  • Group 1
  • Group 2
  • Group 3

Adoption and implementation of computational technologies along with the concepts of data science and machine learning have seen a steady acceptance and increase over the past decade in the field of Earth Science. One such technology at the forefront is the Jupyter Notebook.
Jupyter Notebook, an open-source web-based application, allows creation and sharing of documents containing code, results and accompanying documentation. Work in Notebooks is predominantly performed with R and Python, though many other languages are available. Jupyter Notebooks provide an interactive console-based approach making it easier for colleagues to understand the code, results, and goals.

This session encourages submissions of adoption, usage and current benefits, as well as, the use of Jupyter Notebooks as a method for publications and the potential benefits from such an endeavor. This direction aims to explore the usefulness of the reproducibility and replicability of experiments performed in Notebooks. The goal of this session is to highlight the importance and significant impact Jupyter Notebooks has had on projects and research so far and how taking it a step further by incorporating it as a form/format of publications will help in addressing the obstacles faced by scientists and readers alike when attempting to understand the experiments carried out in publications or when re-running an experiment following the methods in publications.

Our Speakers:
1. Dr. Lindsey Heagy:
 Dr. Heagy is currently a Postdoctoral Researcher at the UC Berkeley in the Statistics department, and will soon be an Assistant Professor of Earth, Ocean and Atmospheric Sciences at the University of British Columbia. Dr. Heagy is an active contributor to open source softwares for computational geophysics and open access educational resources to geosciences like SimPEG and GeoSci.xyz. She also leads geophysics component of the Jupyter meets the Earth project, which is in collaboration with Pangeo Project, Jupyter and the geoscience researchers at National Center for Atmospheric Research and UC Berkeley.

2. Dr. Fernando Pérez:
Dr. Pérez is an Associate Professor at the Department of Statistics at UC Berkeley and a found co-investigator of the Berkeley Institute of Data Science. He is also a Faculty Scientist at the Data Science and Technology Division at the Lawrence Berkeley National Laboratory. He created iPython while he was a graduate student in the year 2001 and is the co-founder of its successor, Project Jupyter. His work today focuses on creating tools for modern computational research and data science across domain disciplines with an emphasis on reproducible research.

3. Dr. Lynne Elkins:
Dr. Elkins is an isotope geochemist, petrologist and an Assistant Professor of Geology in the Department of Earth and Atmospheric Sciences at the University of Nebraska- Lincoln. Dr. Elkins' research group focuses on using geochemistry to better understand the Earth's dynamic processes, in particular how magmas are generated in the Earth's mantle layer and how they are emplaced to form new crust. Dr. Elkins has implemented deep Earth complex system modeling in Jupyter Notebooks and also used the tool for a publication of the same project.

Following our speakers' talks we will open the floor for a discussion among all the attendees. 

How to prepare for our session:
We are going to have a quick walkthrough that helps you understand the basics of Jupyter Notebook. So, rest assured that you will be able to follow along if you are new to the application.

View Recording
View Notes

Description: The challenges confronting the Earth and Space Sciences (ESS) are increasingly complex, avoiding categorization or solution within neatly defined disciplinary boxes. Transdisciplinary, or "antidisciplinary," approaches are required to address threats in ESS like climate change and space weather.  However, existing approaches to integrating data and knowledge remain crippling to progress and collaboration. Thus, now is the critical time to bring together the antidisciplinary communities to create a new paradigm of knowledge integration using knowledge graphs/networks and semantic technologies. We will collect contributions that utilize these approaches to better structure knowledge across projects. This session will emerge the success stories and best practices for knowledge graphs across ESS.

Format: We propose to highlight the 'home run stories' in the Earth and Space Sciences to create knowledge graphs/networks that have improved information flows between individuals, projects, groups, and data systems. We will first feature these use cases, then hold a discussion period to emerge new articulation, methods, and research vistas for KGs across the Earth and Space Sciences. We hope that the discussion will emerge data models that can be generally used and processes for tailoring them to new applications.
Conveners:

• Ryan McGranaghan - Principal Data Scientist and Aerospace Engineering Scientist at ASTRA LLC
• Barbara Thompson - NASA Goddard Space Flight Center
• Emily Law - NASA Jet Propulsion Laboratory
• Lewis McGibbney - NASA Jet Propulsion Laboratory

Agenda

• (4 - 4:10 PM) Presentation - opening remarks    
  • Speaker: Ryan McGranaghan
• (4:10 - 4:20 PM) Introduction to panel speakers    
  • All; Ryan McGranaghan to moderate
• (4:20 - 4:45 PM) Panel Discussion    
  • General topics (panel member):
    • Different approaches to building a KG (Deborah L. McGuinness)
    • The socio-technical perspective of KGs (Juan Sequeda)
    • Role of KGs in AI/ML (Leilani Gilpin)
    • Using KGs to link domains (Krzysztof Janowicz)
• (4:45 - 5:10 PM) Breakout sensemaking groups    
• (5:10 - 5:25 PM) ‘What, so what, now what?' Exercise to get feedback from breakouts 
  • Moderator: Ryan McGranaghan and session conveners
• (5:25 - 5:30 PM) Concluding chat   

Panelists

• Juan Sequeda - Principal Scientist at data.world
• Krzysztof Janowicz - Professor of Geographic Information Science and Geoinformatics at the Geography Department of the University of California, Santa Barbara (UCSB)
• Leilani H. Gilpin - Research Scientist at Sony AI; PhD MIT CSAIL
• Deborah L. McGuinness - Tetherless World Senior Constellation Chair and Professor of Computer and Cognitive Science at Rensselaer Polytechnic Institute (RPI); Founding director of the Web Science Research Center at RPI

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View Notes

Interest in the subject and implementation of Analysis Ready Data (ARD), especially for remote sensing products, continues to build in the domain of science data producers and private industry, and their user communities.

In this session we will explore and hear about the landscape of ARD activities from science data producers, private industry stakeholders, and international coordination activities like the Committee on Earth Observation Satellites (CEOS) and others. We will solicit presentations on ARD definitions and assessment, implementation, and practical examples of ARD datasets and their applications highlighting both the successes and challenges.

One of the potential outcomes of this session is to build momentum toward more harmonization of diverse ARD activities and definitions.

How to prepare for this session: https://www.youtube.com/watch?v=YU3ZXOsH7DE&feature=youtu.be


Speakers 

• Ignacio Zuleta (ARD Zone): Virtual constellations, ARD and sensor fusion: the future of earth observation
• Steven Labahn (USGS, CEOS Land Surface Imaging Virtual Constellation (LSI-VC) Co-Lead ): CEOS Analysis Ready Data (ARD)
• Chris Lynnes (NASA): Analysis Ready Satellite Data in NASA’s EOSDIS

Agenda (Condensed)

• Introduction, logistics and audience poll
• 3 speakers and Q&A
• Breakout rooms and discussion
• Summary reports

Other Relevant Sessions:

• Best Practices and Fundamental Challenges of AI in Earth and Space Sciences (01/28 1:30 pm - 3:00 pm)
• Accelerating Artificial Intelligence Applications at Scale with AI-ready Data (01/29 • 11:00am - 12:30pm)
  
  

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View Notes

A major goal of the ESIP Semantic Harmonization Cluster is to promote common understanding and encourage discussion with other ESIP clusters that are developing vocabularies, thesauri, metadata schemas, or ontologies to increase the FAIRness of Earth Science data in potentially specialized domains (e.g. Marine, Soil, or Biological data). By adopting shared approaches among these efforts whenever possible — such as re-using terms, implementing common design patterns, and standardized tooling for vocabulary harmonization — semantic harmonization should vastly increase the capability of researchers to more effectively pursue their science. Thus, we are seeking to build new collaborations with domain experts from various disciplines to harmonize and further develop semantic resources relevant to their respective fields.

This session will continue ongoing discussion of the benefits, goals, and progress in semantically harmonizing Earth Science terminologies, data models and ontologies. Using actual examples integrating vocabularies from the Cryospheric domain, and with a focus on the SWEET and Environment (ENVO) Ontologies, we will present lessons learned for “good enough”/“working practices” learned during our efforts to harmonize the glacial and crosphere terminology between SWEET and ENVO. We hope that our efforts to date can inspire new collaborations and set novel harmonization activities in motion.

How to prepare for this session: For more Information see our ESIP page: https://wiki.esipfed.org/SemanticHarmonization, as well as our running meeting notes: https://www.google.com/url?q=https://docs.google.com/document/d/1IFA6AsCdxESh9mZB5W1bZ_vARFkF3OvnL-KgdGNcp60/edit&sa=D&ust=1604399963101000&usg=AOvVaw0-fqz1-MEOZYXx5PsongvZ, and our ESIP summer 2020 session: https://2020esipsummermeeting.sched.com/event/cIuW/semantic-harmonization-see-it-in-action-bridging-metagenomics-and-earth-science-data.

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View Notes

Thanks to funding from the Institute of Museum & Library Services (IMLS) National Leadership Grant, the ESIP-hosted Data Management Training Clearinghouse (DMTC) is getting ready to unveil its new user interface (UI) design and search capabilities! The home, search and submit pages are the three areas that are receiving the enhancements. Before finalizing the design, navigation and functionality of the Search page that is closest to being ready, however, the DMTC team and Advisory Board members would like to test the usability of the Search page. During this working session, ESIP Community members are invited to try out the Search page using structured usability testing procedures.  Session attendees will have options for providing feedback using different methods such as performing moderated search tasks, documenting the paths taken to fulfill specific needs, and commenting upon the results, utility, look and feel of the page.  The feedback offered by the session attendees will significantly inform final tweaks to the design of the DMTC searching functionality (and be GREATLY appreciated) before we finish our IMLS funded enhancement project in June 2021.

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What should we do next on Usage-based Discovery? Who should we collaborate with over the coming semester?  

We will start with some lightning talks by ESIP members whose work intersects or could intersect with Usage-based Discovery in some way:

1. Chris Lynnes: Discovery Cluster
2. Cyndi Hall: NASA Earth Science Data Pathfinders
3. Mark Parsons: Citations Cluster (PDF)
4. Mike Little / Beth Huffer: Air Quality Cluster
5. Rupu Gupta / Jonathan Blythe: Community Resilience Cluster
6. Dave Jones / Karen Moe:  Disasters Lifecycle Cluster
7. Brian Wee: Agriculture / Climate Cluster

We will follow the lightning talks with a card-sorting exercise and then a discussion about possible modes of collaboration.

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The National Geological and Geophysical Data Preservation Program (NGGDPP) works with state geological surveys and U.S. Department of the Interior (DOI) bureaus to support and foster the archival of geological, geophysical, and engineering data, maps, photographs, samples, and other physical specimens. Metadata records describing these assets are managed in the National Digital Catalog (NDC). The NDC is being re-architected to provide end-to-end improvements in capabilities and services to data providers and users. The goal is to evolve an existing system in the context of many identification systems (ORCID, USGS, ROR, DOI, IGSN, …), existing tools (GeoLog Locator, ScienceBase, mdTools), metadata models (ours, ISO, mdJSON, ScienceBase, SESAR, Science on Schema.org), vocabularies (GCMD, mdTools, many others), representations, and the FAIR principles. This session will encourage representatives of many of these group to discuss how we build a thriving collaborative documentation ecosystem larger than the sum of its parts.

How to prepare for this session: Think about information you need to discover, access, use, understand and trust specimens and other items in scientific collections. Bring examples of well-documented collections that you have created or used.

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ESIP Information Quality Cluster (IQC) has been collaborating with national and international domain experts on a number of fronts that are associated with representing data quality information in a consistent way, ranging from capturing data uncertainty information in NetCDF file-level metadata, providing IQC perspectives on citizen science data, and developing community guidelines for curating FAIR dataset quality information. Doing so will not only improve the maturity of underlying data, but also help enable the sharing of both data and quality information. Community adoption of practices for improving data quality information also will offer new opportunities for users to determine whether data products and services can be used for particular purposes and foster the use of such data.

In this session, we will share with the ESIP community on the current status of those efforts and obtain feedback from the community.

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This session offers a hands-on working agenda for SWEET community members.

Audience
In order to focus on work items, this session targets people who are already familiar with the SWEET ontology. This session will NOT provide an introduction to ontology engineering or the semantic technologies ecosystem.
 

 Preparation
Prior to the session we will have prioritized a handful of Github issues we want to work through. Issues should be labeled with #esipwinter2021To align with the ESIP Meeting theme 'Leading Innovation in Earth Science Data Frontiers', issues focusing on INTEROPERABILITY will be prioritized. Please feel free to create issues and label them appropriately.

Agenda Introduce the session structure Est. time: 5
Landform introduction (Gary Berg-Cross) Est. time: 5
Part 1 - Prioritizing SWEET work

Slido poll #1 Which open Github issue is most important to you? Est. time: 5 min
BREAKOUT #1 Vote with your feet. Join the breakout of interest. Est. time: ~10 min
FEEDBACK #1 - Breakout representative briefs larger group on breakout outcomes; allow time for comments from broader group Est. time: 15-20 min
Part 2 - SWEET Community and Project Governance

Slido poll #2 Which community and/or project governance issues are of concern to you? Est. time: 5 min
BREAKOUT #2 VOTE with your feet. Join breakout of interest. Est. time: ~10 min
FEEDBACK #2 - Breakout representative briefs larger group on breakout outcomes; allow time for comments from broader group Est. time: 15-20 min
SURVEY FEEDBACK/CONCLUSION – Brandon provides commentary of the SWEET survey responses so far. Est time: ~5-10 min

Outcomes

1. We will have identied community governance issues and built consensus on how to address them. Decisions will be recorded in the Github issue - [GOVERNANCE] Project and Community Governance Issues.
2. We will have strategized solutions for current development activities. These will be documented in Github. Maybe even grouped and prioritized as a Github project.

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ESIP has published guidelines for citing data and for citing software and services. These have been important and influential ESIP products. Now, the Research Artifact Citation Cluster is working to address the issues of “research artifact” citation writ large. The cluster has been working to identify additional types of research artifacts that could or should be cited such as samples, taxonomies, annotations, and other artifacts. We have also been examining the various concerns that may be addressed in citing the objects such as access, credit or attribution, and scientific reproducibility.

Currently, we are focusing on the credit aspect of citation for five different artifact types: data, software, samples, semantic resources, and learning resources. At the previous ESIP meeting, we began to explore whether and how the Contribution Roles Taxonomy (CRediT) might apply to different artifacts. In this session we will explore what roles are missing and whether we can begin to generalize credit mechanisms for multiple artifacts or classes of artifacts.

We will present the current work of the cluster on defining the roles and their importance for the different artifacts and then facilitate a group brainstorming exercise on relevant roles and their importance in different use cases.

How to prepare for this session: Participants should be familiar with ESIP Data Citation Guidelines and the ESIP Software & Services Citation Guidelines and ideally the cluster's last session at the 2020 ESIP Summer Meeting.

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California experienced its largest wildfire season on record in 2020 with a single wildfire burning more than 1 million acres. Data has been crucial to inform decision makers and innovation is being applied. This session will dive into the public-private benefits of putting trusted data to work as we tie into the ESIP theme of ‘Leading Innovation in Earth Science Frontiers’. The California Wildfires of 2020 demonstrated that disasters can be on-going and multi-dimensional with COVID-19, evacuations, and destroyed towns. We will discuss key trusted data needs and identify additional opportunities for data applications in support of life saving operations. How can coordination and data sharing accelerate public-private situational awareness and decision making? Are there steps that agencies could take to successfully share their data with decision makers and the public? Your participation can guide us in the Disaster Lifecycle Cluster for the next 6 months. Come join us!

Presentations have been uploaded and are available. If the PPT was larger than 50MB it has been converted to a PDF document.

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Session Description: Artificial intelligence (AI) is a leading technology that may transform the research and applications of Earth and space science and amplify the benefits to society. One of the key bottlenecks limiting exploring/applying AI in Earth and space sciences at scale is the lack of analysis-ready data for AI applications. It's often cited that researchers can spend 80% of their project time wrangling with the large heterogeneous volumes of data that are needed for the application. To accelerate the application of AI in Earth and space sciences, it is essential to minimize users’ burden of data wrangling by providing AI-ready data with machine-readable metadata that is not only compliant with FAIR principles but also tuned for AI applications (e.g., data biases). In this session, we will convene a panel of stakeholders from data providers, users, and data engineers to discuss the path of defining the requirements and creating inter-organization matrices to assess and describe data “AI-readiness”. The outcome of this session will be summarized in a short report, and the document will be used as a guiding document to pursue further collaboration across Earth and space science data communities on this topic.

Session Agenda:

1. Session Scope (5 min)
2. Establish A Baseline (5 min)
3. Invited Presentations (Gregory Dusek, Kirstine Dale, Sophie Hou) (25 min)
4. Breakout Discussion (35 min)
5. Setting Community-Driven Priority (15 min)
6. Close & Depart (5 min)

Slides & Relevant Documents:

• Data AI-readiness matrix (presented during 2nd NOAA AI Workshop).
• Session slide deck
• All slides from speakers can be found at the bottom of this page.

Relevant Sessions:

• Analysis Ready Data in Science and Industry (01/27 11:00 am -12:30 pm)
• Best Practices and Fundamental Challenges of AI in Earth and Space Sciences (01/28 1:30 pm - 3:00 pm)
• Research Showcase (01/27 6:00 pm - 7:30 pm)

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SLIDES: Google Slides

The science-on-schema.org guidelines have been a useful resource for guiding data repositories on how to publish metadata embedded in web pages for describing scientific datasets on the web. Following these guidelines helps repositories ensure they are correctly publishing common, shared metadata information in ways that are known to major search engines and metadata aggregators. The Schema.org Cluster is seeking to have guidelines for simple data discovery endorsed by the ESIP Assembly, and this session will address/cover:
1. Brief introduction to the Science-on-Schema.org guidelines & the Schema.org ESIP Cluster
2. Review/announce the latest version of the guidelines (v1.2)
3. Why obtaining an ESIP Assembly endorsement is a worthwhile/meaningful activity;
4. Review the ESIP Assembly submission guidelines
5. Develop a roadmap for the Science-on-Schema.org guidelines for ESIP Assembly review

How to prepare for this session:

1. Review the Science-on-Schema.org guidelines at https://science-on-schema.org. 
2. Review the ESIP Endorsement Policy
   https://github.com/ESIPFed/Governance/blob/master/ESIP%20Policies%20and%20Procedures/1.0%20Corporate/ESIP%20P%26P%201.7%20Endorsements.md.
   

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