2019 ESIP Winter Meeting Session Submission Form (Responses)
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Session TitleSession Short Name Session Description
Does your session relate to any of ESIP's strategic goals?
TypeSession Moderator NameSpeakers
Session Audience: consider your session as a pool of knowledge - will your presentation let folks skim the surface, jump in, or take a deep dive?
Collaboration Area TagsAdd Session Tags
Are you interested in using ESIPhub in your session?
Moderators and SpeakersNotes
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ESIP Lab Funded Project Report OutESIP Lab Hear the outcomes of the 2018 ESIP Lab funded projects.
Promote techniques to articulate and measure the socioeconomic value and benefit of Earth science data, information and applications., Position ESIP to play a major role in Earth science issues (e.g. addressing effects of climate change mitigation, adaptation and supporting sustainable science data infrastructure).
Breakout SessionAnnie BurgessAnnie BurgessSkim the SurfaceCloud Computing, Disaster LifecycleM: Annie Burgess; S: Annie Burgess
3
EDF General Assembly Meeting
EDF General Assembly Meeting
The Council of Data Facilities (CDF) is committed to working with relevant agencies, professional associations, initiatives, and other complementary efforts to enable transformational science, innovative education, and informed public policy through increased coordination, collaboration, and innovation in the acquisition, curation, preservation, and dissemination of geoscience data, tools, models, and services. Existing and emerging geoscience data facilities – through the Council – are committed to serving as an effective foundation for EarthCube. The General Assembly meeting is open to the official representatives from all member data facilities, additional member organization personnel as desired by the members, as well as observers.
Increase the use and value of Earth science data and information.
Breakout SessionDanie KinkadeJump InDiscovery, Sustainable Data ManagementM: Danie Kinkade; S:
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EDF General Assembly Meeting
EDF General Assembly Meeting
The Council of Data Facilities (CDF) is committed to working with relevant agencies, professional associations, initiatives, and other complementary efforts to enable transformational science, innovative education, and informed public policy through increased coordination, collaboration, and innovation in the acquisition, curation, preservation, and dissemination of geoscience data, tools, models, and services. Existing and emerging geoscience data facilities – through the Council – are committed to serving as an effective foundation for EarthCube. The General Assembly meeting is open to the official representatives from all member data facilities, additional member organization personnel as desired by the members, as well as observers.
Increase the use and value of Earth science data and information.
Breakout SessionDanie KinkadeJump InDiscovery, Sustainable Data ManagementM: Danie Kinkade; S:
5
Applications of Semantic Technologies Across Earth Sciences
Applications of Semantic Technologies Across Earth Sciences
This session encourages use of semantic technologies which further the use and value of earth science data through linkage, interoperability and standardization.
Increase the use and value of Earth science data and information.
Breakout SessionLewis John McGibbneyLewis McGibbney, Dalia VarankaJump InData to Decisions, Discovery, Data Analytics, Science Software, Semantic TechnologiesM: Lewis John McGibbney; S: Lewis McGibbney, Dalia Varanka
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Community Curated Metadata Extractors
Community Curated Metadata Extractors
How can science communities come together to create tools that automatically derive data from files?
Increase the use and value of Earth science data and information., Strengthen the ties between observations and user communities (e.g. technologies, research, education and applications).
Working SessionBen GalewskyBen Galewsky, Kunxuan Wang, Bob Dattore
Skim the Surface, Jump In
Data to Decisions, Data Analytics, Information Quality, Machine Learning, Research Data Management, Sustainable Data Managementmetadata, curationM: Ben Galewsky; S: Ben Galewsky, Kunxuan Wang, Bob Dattore
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Provenance for connecting climate adaptation decisions to data
Data to decisions provenance
Our ESIP Lab funded project asked the question: how effectively can we capture the provenance between data products and decisions? We still do not have all the answers, but we hope you’ll find this session thought provoking, regardless of whether you’re a provenance expert asking the same question, or a member of a climate resilience project looking for ways to find and adapt existing data-driven solutions, or a policy analyst estimating the socio-economic value of data by tracing decisions back to data.

Among the topics covered will be: ontologies for capturing decision making, machine parsing of human readable documents to extract concepts, capturing decisions using process frameworks like the US Climate Resilience Toolkit planning guidelines and the National Park Service’s climate change scenario planning guidelines, text mining legally mandated public records for resilience infrastructure, and others. Audience feedback to our findings will be used to guide follow-on activities.
Increase the use and value of Earth science data and information., Strengthen the ties between observations and user communities (e.g. technologies, research, education and applications)., Promote techniques to articulate and measure the socioeconomic value and benefit of Earth science data, information and applications., Position ESIP to play a major role in Earth science issues (e.g. addressing effects of climate change mitigation, adaptation and supporting sustainable science data infrastructure).
Breakout SessionBrian Wee, Bill TengBrian Wee, Nancy Hoebelheinrich, Tom Narock, Arif Albayrak
Skim the Surface, Jump In
Agriculture and Climate, Community Resilience, Data to Decisions, Disaster Lifecycle, Semantic Technologies
climate resilience, provenance, decision making
M: Brian Wee, Bill Teng; S: Brian Wee, Nancy Hoebelheinrich, Tom Narock, Arif Albayrak
8
Increasing the use and value of Earth science data and information through standards
Standards for Earth Observation
This session presents the latest results from the OGC innovation program Testbed-14, which addressed several topics that are directly inline with this year's ESIP theme of "increasing the use and value of Earth science data and information". The OGC innovation program is the experimentation lab of OGC, where new technologies are explored that enhance earth observation research and science. Testbed-14 addressed among others topics new standardized approaches to access and exploit satellite swath data (level 1 and 2); explored enhanced, resource-oriented, discovery and access mechanisms for geospatial data and information that reduces the burden on clients, as data can be browsed in addition to being queried; developed an architecture to execute any type of application physically close to Big data; explored quoting and billing mechanisms for geospatial products; developed an architecture to integrate machine learning and artificial intelligence into earth science workflows.
Increase the use and value of Earth science data and information., Strengthen the ties between observations and user communities (e.g. technologies, research, education and applications).
Breakout SessionIngo SimonisIngo Simonis, Luis Bermudez, George PercivallJump InAgriculture and Climate, Cloud Computing, Data Models, Data to Decisions, Discovery, Data Analytics, Information Quality, Machine Learning, Web Services
standards, OGC, Big data, cloud, machine learning
M: Ingo Simonis; S: Ingo Simonis, Luis Bermudez, George Percivall
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Machine Learning Cluster Breakout
Machine Learning Cluster Breakout
We'll introduce the cluster and Rob and Hook will ecah present some current work involving machine learning. A better title and abstract will be forthcoming.
Increase the use and value of Earth science data and information., Strengthen the ties between observations and user communities (e.g. technologies, research, education and applications)., Position ESIP to play a major role in Earth science issues (e.g. addressing effects of climate change mitigation, adaptation and supporting sustainable science data infrastructure).
Breakout SessionBill Teng, Hook Hua, Beth Huffer, Svetla Hristova-Veleva, Arif AlbayrakRob Emanuelle, Hook HuaSkim the SurfaceCloud Computing, Data to Decisions, Data Analytics, Education, Machine Learning, Science SoftwareScience TechnologiesM: Bill Teng, Hook Hua, Beth Huffer, Svetla Hristova-Veleva, Arif Albayrak; S: Rob Emanuelle, Hook Hua
Combine with other ML session??
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Test-drive earthdata.nasa.gov: Is this ride good for you?
Test-drive earthdata.nasa.gov
The NASA Earth Science Data System program, which hosts all of NASA’s Earth science data collections, is currently working to improve access to those data holdings and information. In this working session, we want to get to know you, the driver, but then want to task you with test-driving the process of accessing data through the earthdata.nasa.gov site. You can provide feedback and suggestions on site intuitiveness, data access, and data manipulation, noting any pain points or needs that you have. Your valuable input will be used to build an effective site, that not only increases the use of but also the value of Earth science data through NASA.
Increase the use and value of Earth science data and information., Strengthen the ties between observations and user communities (e.g. technologies, research, education and applications).
Working SessionCynthia HallCynthia Hall, Paula Land, Teodoro Gelabert, Kevin Ward
Skim the Surface, Jump In
Discovery, UsabilityM: Cynthia Hall; S: Cynthia Hall, Paula Land, Teodoro Gelabert, Kevin Ward
Combine with Usability Session?
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GCMD Keyword Management Process and LifecycleShow the process for GCMD keywords - fast track and yearly reviews through the ESDIS Standards Office, and how Earth science users can influence keyword additions and modifications. Highlight how keywords facilitate the discovery of EOSDIS data and services. Upcoming keyword reviews.
Increase the use and value of Earth science data and information.
Breakout SessionTyler B. StevensTyler B. StevensJump InDiscovery, DocumentationKeywords, ProcessM: Tyler B. Stevens; S: Tyler B. Stevens
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NASA Metadata Models and Standards Round-Table
NASA Metadata Models and Standards
Round-table discussion about the UMM models, answer metadata questions from users, and gather any feedback for future improvements to the models based on user needs. Briefly discuss what's new with the models.
Increase the use and value of Earth science data and information.
Working SessionTyler B. Stevens, Erich Reiter, Joe RincioneTyler B. Stevens, Erich Reiter, Joe RincioneJump InData Models, Documentation
Metadata, Models, Earth Science
M: Tyler B. Stevens, Erich Reiter, Joe Rincione; S: Tyler B. Stevens, Erich Reiter, Joe Rincione
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Triage in the Data ward: A collaborative working session for developing a data rescue decision framework
Developing a common data risk decision framework
Data rescue requires resources that are often scarce, and can also hinge of the timeliness of rescue efforts. Efforts by ESIP, RDA, EarthCube, and the IMLS-funded Data Rescue Toolkit have all focused on the development of elements to help focus and motivate data rescue efforts and improve the efficiency of efforts in the future. A clear need from within the community is to help synthesize findings from each of these groups, and to obtain input from the broader geosciences community, those actively involved in ad hoc data rescue efforts, and other issues around data rescue that may be particular to that community.

This session will begin with a brief overview of the work accomplished by the various groups mentioned above, and provide an introduction to the goals of the newly-approved CODATA Task Group, Improving Data Access and Reusability (IDAR-TG). The IDAR-TG highlights the importance and timeliness of not only data rescue, but also the need to collect and/or develop tools and frameworks to assist with assessing what data is in most need of rescuing.

The majority of the session will be a working session where we will discuss what characteristics of the data and its environment (repository, funding stream, etc.) increase data’s risk level, what considerations need to be made when deciding whether the data needs to be rescued, what resources are already available for this task, and how the Data Nomination Tool and other activities in the Data Rescue Toolkit project might be able to help.
Increase the use and value of Earth science data and information., Strengthen the ties between observations and user communities (e.g. technologies, research, education and applications)., Promote techniques to articulate and measure the socioeconomic value and benefit of Earth science data, information and applications., Position ESIP to play a major role in Earth science issues (e.g. addressing effects of climate change mitigation, adaptation and supporting sustainable science data infrastructure).
Working SessionDenise Hills, Ruth DuerrDenise Hills, Steve Diggs, Sophie Hou, Matt Mayernick, Ruth Duerr, Reid Boehm, Simon GoringJump InCommunity Resilience, Data to Decisions, Research Data Management, Sustainable Data Management, Usability, Data Stewardship
data rescue, data risk, data access, risk management
M: Denise Hills, Ruth Duerr; S: Denise Hills, Steve Diggs, Sophie Hou, Matt Mayernick, Ruth Duerr, Reid Boehm, Simon Goring
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Working Session: Exploring Jupyter Technologies for EducatorsJupyter for EducatorsMembers of ESIP's Education Committee invite attendees who have a working knowledge of Jupyter technologies to share information and examples that can be used in an introductory workshop for educators.
Increase the use and value of Earth science data and information., Strengthen the ties between observations and user communities (e.g. technologies, research, education and applications).
Working SessionLuAnn Dahlman, Shelley Olds, Becky ReidLuAnn Dahlman, Shelley Olds, Becky Reid, Sean Gordon
Skim the Surface, Jump In
EducationJupyter notebooks, MaybeM: LuAnn Dahlman, Shelley Olds, Becky Reid; S: LuAnn Dahlman, Shelley Olds, Becky Reid, Sean Gordon
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Semantics: Working to harmonize SWEET and ENVO: Part 1
SWEET & ENVO Harmonization 1
The ESIP Semantic Technologies committee has been working to harmonize ontologies in the Earth sciences with ontologies in other fields (environmental science, biology, chemistry, etc.). In these two back-to-back sessions we will be working on harmonizing SWEET with ENVO, with particular concentration on cryospheric terminology.
Increase the use and value of Earth science data and information., Position ESIP to play a major role in Earth science issues (e.g. addressing effects of climate change mitigation, adaptation and supporting sustainable science data infrastructure).
Working SessionRuth Duerr, Pier Luigi Buttigieg, Gary Berg-CrossDeep DiveData Models, Data to Decisions, Discovery, Documentation, Research Data Management, Semantic Technologies
sematics, SWEET, ENVO, ontologies
NoM: Ruth Duerr, Pier Luigi Buttigieg, Gary Berg-Cross; S:
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Harmonizing SWEET and ENVO: Part 2
Harmonizing SWEET and ENVO: Part 2
Harmonizing SWEEt
Increase the use and value of Earth science data and information., Position ESIP to play a major role in Earth science issues (e.g. addressing effects of climate change mitigation, adaptation and supporting sustainable science data infrastructure).
Working SessionRuth Duerr, Pier Luigi Buttigieg, Gary Berg-CrossDeep DiveData Models, Discovery, Documentation, Semantic Technologies
Semantics, Ontologies, SWEET, ENVO
MaybeM: Ruth Duerr, Pier Luigi Buttigieg, Gary Berg-Cross; S:
17
Exercising Deep Learning Technique on Earth Datasets for Agriculture
Deep learning on Agricultural Data
Deep learning (DL) is the hottest method to realize artificial intelligence in many applied science domains. Our ESIPLab project Geoweaver has started to use Deep Learning method in producing crop maps with higher resolution and accuracy than conventional crop map production methods.
The success of DL relies on massive training datasets and powerful compute nodes like Graphics Processing Units (GPU). A good neural network requires careful engineering and considerable domain expertise in network training. It is never easy to fit DL on any Earth dataset. This session will carry out discussion on the research areas, technical details, data sources, and performances of DL in agriculture. We will work on harmonizing and generating a common strategy to connect and prepare Earth datasets for the training/testing of customized deep neural networks to help advance agricultural researches into next level: intelligent agriculture.
Increase the use and value of Earth science data and information., Strengthen the ties between observations and user communities (e.g. technologies, research, education and applications)., Promote techniques to articulate and measure the socioeconomic value and benefit of Earth science data, information and applications., Position ESIP to play a major role in Earth science issues (e.g. addressing effects of climate change mitigation, adaptation and supporting sustainable science data infrastructure).
Working SessionZiheng Sun, Liping Di, Annie BurgessZiheng Sun, Liping Di
Skim the Surface, Jump In, Deep Dive
Agriculture and Climate, Cloud Computing, Data to Decisions, Machine Learning, Science Software
deep learning, agriculture, remote sensing, big data, high performance computing
YesM: Ziheng Sun, Liping Di, Annie Burgess; S: Ziheng Sun, Liping Di
18
20 years of Making Data MatterMaking data matterA review of results from data collected among ESIP members about their perspective and vision of the changing state of making Earth Science data matter.
Increase the use and value of Earth science data and information., Strengthen the ties between observations and user communities (e.g. technologies, research, education and applications)., Promote techniques to articulate and measure the socioeconomic value and benefit of Earth science data, information and applications., Position ESIP to play a major role in Earth science issues (e.g. addressing effects of climate change mitigation, adaptation and supporting sustainable science data infrastructure).
Working SessionArika VirapongseArika VirapongseJump In, Deep DiveESIP strategic developmentNoM: Arika Virapongse; S: Arika Virapongse
19
Enhanced Reality: Data Visualization and Immersive Technologies
Data Visualization and Immersive Technologies
Across industries and government, there are many groups working with virtual, augmented, and mixed reality technologies inside and outside of the realm of Earth science. In this dynamic panel, we will hear from scientists and researchers working with VR/AR/MR from various scientific disciplines about their approach to data visualization techniques. Interdisciplinary work and complex data sets will provide interesting perspective to the ongoing exploration of how immersive technologies can be used for Earth science and beyond.
Increase the use and value of Earth science data and information., Strengthen the ties between observations and user communities (e.g. technologies, research, education and applications)., Position ESIP to play a major role in Earth science issues (e.g. addressing effects of climate change mitigation, adaptation and supporting sustainable science data infrastructure).
PanelShayna Skolnik(These speakers will need to be confirmed) Jordan Higgins-ByteCubed, Kaur Kullman - US Army Research Lab, Bryan Stephenson-NASA GSFC Heliophysics, Emily Law-NASA JPLJump InData Models, Data to Decisions, Discovery, Data Analytics, Education, Energy and Climate, Research Data Management, Science Communication, Science Software, Usability, VR/AR for Science
VR,AR,MR,technology,innovation, data visualization
MaybeM: Shayna Skolnik; S: (These speakers will need to be confirmed) Jordan Higgins-ByteCubed, Kaur Kullman - US Army Research Lab, Bryan Stephenson-NASA GSFC Heliophysics, Emily Law-NASA JPL
20
Cloud Analytics Reference Architecture
Cloud Analytics Ref Arch
NASA ESDSWG Cloud Analytics Reference Architecture WG was established to define a reference architecture to bring analytics to big data on the cloud to enable discovery and analysis. Current key activities include gathering use cases for cloud analytics and development of the reference architecture document. In this working session, we will provide status update of the activities, solicit inputs, and work together to draft specific sections of the reference architecture document.
Increase the use and value of Earth science data and information., Strengthen the ties between observations and user communities (e.g. technologies, research, education and applications)., Position ESIP to play a major role in Earth science issues (e.g. addressing effects of climate change mitigation, adaptation and supporting sustainable science data infrastructure).
Working SessionEmily Law, Dave Meyer, Chris LynnesSession chairsJump In, Deep DiveCloud Computing, Data Models, Data Analytics, Machine Learning, Semantic Technologies, Web Services
Cloud, Analytics, Architecture, Analysis, Processing, Visualization, Data Service, Cloud Analytics Service
MaybeM: Emily Law, Dave Meyer, Chris Lynnes; S: Session chairs
21
Evolving the Editorial Policies and Practices of the Data Management Training Clearinghouse: A Working Session
DMT Clearinghouse Working Session
Since 2016, selection criteria have guided decisions made about the range, type and depth of educational resources published in the ESIP-hosted Data Management Training Clearinghouse (DMTC). The selection criteria were chosen with input from the first three organizational collaborators: ESIP, DataONE, and the U.S. Geological Survey. Once accepted for publication, the educational resources have been described using a subset of the Schema.org endorsed metadata schema for educational resources called the Learning Resource Metadata Initiative (LRMI) that is maintained by the Dublin Core Metadata Initiative (http://dublincore.org/dcx/lrmi-terms/1.1/ ). Specific elements of the LRMI metadata scheme were then chosen as featured search facets and descriptive elements in the search results display of the DMTC.
In July of this year, the DMTC received an Institute of Museum & Library Services (IMLS) National Leadership Grant focused on the expansion of the disciplines in the Clearinghouse, and enhancing the discovery and evaluation of the resources in the DMTC. As a result, it is good time to solicit feedback from the science and social science researcher and trainer communities on the DMTC editorial policies described above. In this working session, participants serving as DMTC resource submitters, reviewers and editors will be invited to test current submission and editorial practice by choosing educational resources not yet included in the publishing queue, deciding whether to submit them for publication using the DMTC selection criteria, and describing them using the LRMI metadata elements present in the full DMTC submission form. A discussion will follow these individual or small group activities in which participants will be asked to provide feedback on what was challenging and/or positive about their experience. The purpose of the discussion will be to reflect upon how the editorial policies and practices affect the scope, range and potential for sustainable growth of the DMTC inventory. Information to provide context and background data for the activities will be distributed to participants ahead of time based on the Sched participant list.
Increase the use and value of Earth science data and information.
Working SessionNancy Hoebelheinrich, Karl BenedictNancy Hoebelheinrich, Karl BenedictJump In, Deep DiveEducation, ESIP-E2SIP, Research Data Management, Usability
Editorial policies, data management training, train the trainers
NoM: Nancy Hoebelheinrich, Karl Benedict; S: Nancy Hoebelheinrich, Karl Benedict
22
Cloud Analytics Reference Architecture
Cloud Analytics Reference Architecture
NASA's Cloud Analytics Reference Architecture (CARA) Working Group was established at the 2018 Earth Science Data Systems Working Group (ESDSWG) annual meeting to define a reference architecture enabling discovery and analysis of big data in cloud environments. Current key activities include gathering use cases for cloud analytics, and development of the reference architecture document. The goal of this working session is to inform the ESIP community of the CARA WG's efforts to date, and solicit review and contributions to the use cases and reference document.
Increase the use and value of Earth science data and information., Strengthen the ties between observations and user communities (e.g. technologies, research, education and applications)., Position ESIP to play a major role in Earth science issues (e.g. addressing effects of climate change mitigation, adaptation and supporting sustainable science data infrastructure).
Working SessionEmily Law, Dave MeyerTBDJump In, Deep DiveCloud Computing, Data to Decisions, Discovery, Data Analytics, Science Software, UsabilityMaybeM: Emily Law, Dave Meyer; S: TBD
23
Community resilience for earth science data institutions and place-based communitiesCommunity resilienceThis session examines how data and information can be a catalyst for overcoming social barriers in communities to help them realize and work collaboratively towards broadly appreciated, overarching goals, like the enhanced sustainability of their food and/or energy system. Concrete examples are drawn from both place-based and institutional communities, regarding how data and information are used in innovative ways to overcome challenges. Place-based examples include the assessment and mitigation of community vulnerability to climate change, such as in coastal communities. Institutional examples from governmental organizations, NGOs, and Private Sector entities demonstrate how their systems are better defined and efforts are best aligned in the context of their long established missions. These examples highlight how a re-framing of established norms through resilience thinking provides an innovative tool, and how the ESIP Federation can step into a leading role toward more effective and efficient use of the Nation’s earth science data and information within a community context.
Increase the use and value of Earth science data and information., Strengthen the ties between observations and user communities (e.g. technologies, research, education and applications).
Breakout SessionArika Virapongse, Jonathan Blythe, Rupu Gupta, Ruth Duerr Jonathan Blythe, Rupu Gupta, Ranalda TsosieSkim the SurfaceCommunity ResilienceNoM: Arika Virapongse, Jonathan Blythe, Rupu Gupta, Ruth Duerr ; S: Jonathan Blythe, Rupu Gupta, Ranalda Tsosie
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Soils Data Integration Challenges throughout the Research Data Lifecycle
Soils Data Integration Challenges
The use of soils data within the Earth sciences often requires the researcher to harmonize and reconcile data from multiple sources. This process can take up to 80% of a researcher’s time (OGC, 2016). Multiple groups are discussing standards for data collection, archival, and metadata to increase the ease-of-use and portability of data. These groups include (1) the International Union of Soil Sciences Working Group on Soil Information Standards, which has conducted an Open Geospatial Consortium (OGC) Soil Data Interoperability Experiment (OGC, 2016); (2) the UN Food and Agriculture Organization (FAO) Global Soil Partnership, which has developed the “Five Pillars of Action” -- three of which relate directly to the research data lifecycle (UNFAO, 2018); (3) the USDA National Institute of Food and Agriculture (NIFA), which has co-convened a Data Science in Agriculture Summit (NIFA, 2017); and (4) the USDA Natural Resources Conservation Service (NRCS), which recently released a technical note on common protocols to improve data quality and facilitate data sharing (NRCS, 2018).

In this session, we will hear from speakers in the Earth sciences community who are utilizing soils data in their research. We will focus on integration challenges they've had using these data through the research data lifecycle, from data creation to archival in a repository for re-use. The session will also provide perspectives on how these problems were (or may be) addressed and the effect these problems -- and solutions -- have on data analysis and the re-use of data. We will have presentations from researchers conducting both primary and secondary research, with the goal of highlighting solutions and next steps for the use and curation of soils data in the Earth sciences. By the end of the session, we aim to have identified the major challenges in using and re-using soils data, particularly as they relate to the use of soils standards.

References

NIFA, 2017, Data Science in Agriculture Summit (https://nifa.usda.gov/data-science-agriculture-summit)
NRCS, 2018, USDA Releases Standard Indicators and Laboratory Procedures to Assess Soil Health for Public Comment (https://www.nrcs.usda.gov/wps/portal/nrcs/detail/national/newsroom/releases/?cid=NRCSEPRD1420430)
OGC, 2016, OGC Soil Data Interoperability Experiment (https://portal.opengeospatial.org/files/?artifact_id=69891)
UNFAO, 2018, The 5 pillars of action
http://www.fao.org/global-soil-partnership/pillars-action/en/
Increase the use and value of Earth science data and information., Strengthen the ties between observations and user communities (e.g. technologies, research, education and applications).
Breakout SessionBill Teng, Nancy Hoebelheinrich, Chris Beltz, Lindsay BarbieriTBD
Skim the Surface, Jump In
Agriculture and Climate, Data AnalyticsNoM: Bill Teng, Nancy Hoebelheinrich, Chris Beltz, Lindsay Barbieri; S: TBD
25
Want to know how to delight your repository users? - Usability can help!
Improving Repository Usability
Are you providing data services? Do you know what your users would say about using your services? If you answer yes to the first question but no to the second, you will want to join this session!

At the National Center for Atmospheric Research (NCAR), a new suite of data system tools is being developed and collectively called the NCAR Digital Asset Services Hub (DASH). It is crucial that the DASH services help the users in achieving their data goals regardless of whether or not they are familiar with data repositories. Additionally, it is vital that the user interactions are friendly and intuitive, so that the users will not mind coming back!

During this session, the attendees will have the opportunity to learn about the techniques that can be applied to a data repository, see evaluation examples and results from DASH, and practice how to evaluate the usefulness of a data repository by using the newly created DASH Repository as the test case.
Increase the use and value of Earth science data and information., Strengthen the ties between observations and user communities (e.g. technologies, research, education and applications)., Promote techniques to articulate and measure the socioeconomic value and benefit of Earth science data, information and applications.
Working SessionSophie HouSophie HouJump InUsability, Data Stewardship
Data Repository, User Interface, User Experience
MaybeM: Sophie Hou; S: Sophie Hou
26
Approaching Sustainability with Techniques from an Entrepreneurial Mindset
SGCI Sustainability Panel
Sustaining our data resources is part of the bigger issue of sustaining all research products. As we contemplate technologies to enable this, we must also consider organizational and financial enablements. The Science Gateway Community Institute recently conducted a session to work on characterizing 11 ESIP related projects in terms of concepts borrowed from entrepreneurship. This panel will focus on discussion of some of those results and their applicability in a broader sense to sustainable data infrastructures and repositories.
Position ESIP to play a major role in Earth science issues (e.g. addressing effects of climate change mitigation, adaptation and supporting sustainable science data infrastructure).
PanelMichael Zentner, Claire Stirm, Juliana CasavanMichael Zentner, Claire Stirm, Juliana Casavan, and others TBD
Skim the Surface, Jump In
Sustainable Data ManagementNoM: Michael Zentner, Claire Stirm, Juliana Casavan; S: Michael Zentner, Claire Stirm, Juliana Casavan, and others TBD
27
The Latest in ESIP Software and Data CitationsThe Latest in CitationsCitation formulations have been very active over the past year at ESIP. The new Software and Services Citation Cluster formed and provided citation recommendations along with why it is important to cite software and services. They also consider the recommendations provided by DataCite and Force11. The Data Stewardship Committee formed a subgroup to revisit data citations and provide updates as these formats were provided several years ago. These new and updated citations will be presented along with how they are applicable with the FAIR principles.
Increase the use and value of Earth science data and information., Strengthen the ties between observations and user communities (e.g. technologies, research, education and applications)., Position ESIP to play a major role in Earth science issues (e.g. addressing effects of climate change mitigation, adaptation and supporting sustainable science data infrastructure).
Breakout SessionJessica Hausman, Mark ParsonsJessica Hausman, Mark Parsons, Ruth Duerr
Skim the Surface, Jump In
COPDESS, Documentation, Research Data Management, Software & Services Citationscitations, FAIRNoM: Jessica Hausman, Mark Parsons; S: Jessica Hausman, Mark Parsons, Ruth DuerrCombine with below?
28
Research Objects, What are They and How do You Cite Them?
Research Objects and Citations
As data, software and services have citations there are other objects that do not fall easily into these categories. These “Research Objects” can include ontologies, semantics, physical samples, etc. As these are used as elements in one’s research they should be properly attributed to and referenced, thus citable. This session will discuss and try to quantify what research objects are, how do they effect the research community and how can the current citation formats be used or adjusted to suit a wider breadth of objects.
Increase the use and value of Earth science data and information., Strengthen the ties between observations and user communities (e.g. technologies, research, education and applications)., Position ESIP to play a major role in Earth science issues (e.g. addressing effects of climate change mitigation, adaptation and supporting sustainable science data infrastructure).
Working SessionMark Parsons, Ruth Duerr, Jessica HausmanRuth Duerr, Mark Parsons, Jessica HausmanJump In, Deep DiveCOPDESS, Documentation, Information Quality, Software & Services Citations
research objects, citations, ontologies, physical samples, semantics
MaybeM: Mark Parsons, Ruth Duerr, Jessica Hausman; S: Ruth Duerr, Mark Parsons, Jessica HausmanCombine with above?
29
Establishing Trust in Centralized RepositoriesCentralized or common repositories expose data to new users by bringing together metadata from various archives into a single repository. Centralized repositories also serve as a one stop for data discovery and help increase the likelihood that data will be reused for new research and applications.

Since these repositories expose new users to new data, it is essential that the information provided in these repositories be trustworthy and reliable. Ensuring trustworthiness is an ongoing challenge for centralized repositories.

This session will focus on approaches to ensuring quality and trustworthiness in centralized repositories and the challenges faced by centralized repositories in meeting those goals.
Increase the use and value of Earth science data and information., Strengthen the ties between observations and user communities (e.g. technologies, research, education and applications)., Promote techniques to articulate and measure the socioeconomic value and benefit of Earth science data, information and applications.
Breakout SessionSean Gordon, Kaylin BugbeeSean Gordon, Kaylin Bugbee
Skim the Surface, Jump In
DocumentationM: Sean Gordon, Kaylin Bugbee; S: Sean Gordon, Kaylin Bugbee
30
GIS for Sustainability in the CloudTBD
Increase the use and value of Earth science data and information., Strengthen the ties between observations and user communities (e.g. technologies, research, education and applications)., Promote techniques to articulate and measure the socioeconomic value and benefit of Earth science data, information and applications., Position ESIP to play a major role in Earth science issues (e.g. addressing effects of climate change mitigation, adaptation and supporting sustainable science data infrastructure).
PanelAna Pinheiro Privette, Sudhir Raj Shrestha
Skim the Surface, Jump In, Deep Dive
Agriculture and Climate, Cloud Computing, Data Models, Data to Decisions, Discovery, Data Analytics, Energy and Climate, Machine Learning, Sustainable Data Management, Web Services, GIS
GIS, Sustainability, Data Science, Cloud computing, Web Services, Scientific Data
MaybeM: Ana Pinheiro Privette, Sudhir Raj Shrestha; S:
31
Applying Earth Science Data to Environmental Health Research and Decisions
Environmental Health and Earth Science Data
This session is proposed to explore topics involving the application of Earth science data to environmental health issues and decision making, and whether there is enough interest within the ESIP community to start a new cluster addressing the application of Earth science data to health community interests - research, applications, etc. The session will begin exploring what are some of the issues, challenges and concerns of integrating Earth science data with environmental health research, and how might the ESIP community contribute to solutions.

The session organizers will begin the session with presentations for some known activities, and solicit participation from the ESIP community, and then gauge the interest to decide whether to push ahead with a new ESIP cluster on a related topic.
Increase the use and value of Earth science data and information., Strengthen the ties between observations and user communities (e.g. technologies, research, education and applications)., Promote techniques to articulate and measure the socioeconomic value and benefit of Earth science data, information and applications.
Breakout SessionJohn Beck, Ken KeiserTBDSkim the SurfaceEnvironmental HealthHealth, DecisionsNoM: John Beck, Ken Keiser; S: TBD
32
Decentralized Data StewardshipHow can we make it possible to coordinate management, replication, and governance of data on decentralized infrastructure? What efficiencies can we gain? What practices and lessons from centralized data governance should we take care to protect or learn from? ...and what does 'decentralized infrastructure' even mean!? Let's talk, together.
Increase the use and value of Earth science data and information., Position ESIP to play a major role in Earth science issues (e.g. addressing effects of climate change mitigation, adaptation and supporting sustainable science data infrastructure).
Working SessionMichelle Hertzfeld
Skim the Surface, Jump In
Community Resilience, Information Quality, Research Data Management, Sustainable Data ManagementNoM: Michelle Hertzfeld; S:
33
ESIP's Marine Data Cluster - Introduction and Development of Focus Areas
ESIP's Marine Data Cluster
This session will introduce the Marine Data Cluster with brief presentations from chairs and founding members, followed by an open discussion on what the Marine Data Cluster should focus on in the first year. What problems will we tackle? What are the most important Marine Data topics on which this group can focus its efforts? We will also brainstorm the infrastructure and support needs and opportunities of the cluster.
Increase the use and value of Earth science data and information., Position ESIP to play a major role in Earth science issues (e.g. addressing effects of climate change mitigation, adaptation and supporting sustainable science data infrastructure).
Working SessionJocelyn Elya, Carolina Berys-Gonzalez, Christopher Olson, Steve DiggsJocelyn Elya, Carolina Berys-Gonzalez, Christopher Olson, Steve Diggs, Karen Stocks
Skim the Surface, Jump In
Data Models, Documentation, Information Quality, Research Data Management, Science Software, Sustainable Data Management, UsabilityM: Jocelyn Elya, Carolina Berys-Gonzalez, Christopher Olson, Steve Diggs; S: Jocelyn Elya, Carolina Berys-Gonzalez, Christopher Olson, Steve Diggs, Karen Stocks
34
The "I&R" in FAIR: Who develops, approves, and governs domain-specific standards in the Earth, Space, & Environmental Sciences?
Assessing "I&R" in FAIR for ESES Data
Researchers, data repositories, publishers, funders, and other stakeholders are increasingly obligated to ensure that data are not only open, but also FAIR - findable, accessible, interoperable, and re-usable. Various initiatives, projects, and working groups are working to advance the implementation of the FAIR principles, among them the AGU project "Enabling FAIR Data", the European GOFAIR initiative, and Working Groups within the RDA and WDS. This efforts are making it increasingly clear that many aspects of FAIRness, specifically reusability, are highly context and domain specific. The original FAIR guiding principles explicitly point to “domain-relevant community standards (R1.3.)”, but there are many open questions regarding such domain-relevant community standards: Who develops and maintains them? Who has the authority to approve them and govern them? How granular do domain-specific standard definitions need to be?
This session is intended to foster a dialog between data repositories, researchers, and other stakeholders to clarify and address the above listed questions for the Earth, Space, and Environmental informatics community.
Increase the use and value of Earth science data and information., Strengthen the ties between observations and user communities (e.g. technologies, research, education and applications).
PanelKerstin LehnertNot yet confirmed: Tim Ahern, Ted Haberman, Jocelyn ElyaJump InCOPDESS, Data Models, Documentation, Information Quality, Research Data Management
FAIR, reusability, domain standards, governance
NoM: Kerstin Lehnert; S: Not yet confirmed: Tim Ahern, Ted Haberman, Jocelyn Elya
35
Filling the Earth Science Cookbook: Discovery and registry of Earth Science workflows from public repositories.
Filling the Earth Science Cookbook
The majority of scientific programming workflows are developed in isolation by graduate students and postdoctoral researchers. While packages and libraries in R and Python help support the advancement of scientific discovery, researchers are often challenged with combining and analysing data in new ways. Regardless, code use and re-use in the Earth Sciences is often complicated by the fact that few well-developed workflows exist as templates. Most code examples in R packages for example, use well-worn datasets that are not well suited to extrapolation for Earth Science applications. For this reason, the discovery and analysis of existing code resources, such as those undertaken by the FUNding Friday grant, become critical to providing resources to scientific programmers in the Earth Sciences.

This Session will introduce early-career researchers to the principle workflows for sharing code publicly, including discussion of some of the pros and cons of sharing code before it is “good enough”. The session will then provide an overview of work that has been undertaken to analyse a large number of Jupyter notebooks on GitHub, and then provide session members with an opportunity to help build the web of examples for coding resources, discussing what makes code useful as a “cookbook recipe” for Earth Sciences, what particular libraries or data resources are of interest, and how further automation might be undertaken.
Increase the use and value of Earth science data and information.
Working SessionBen GalweskiSimon Goring, Ben Galweski, others TBA
Skim the Surface, Jump In
Data Models, Discovery, Data Analytics, Education, Information Quality, IM Code Registry, Sustainable Data Management
GitHub, Python, Jupyter, RMarkdown, R, Go, Repositories, libraries, packages, code, cookbook, documentation, sustainability, metrics
MaybeM: Ben Galweski; S: Simon Goring, Ben Galweski, others TBA
36
Maturing the Operational Readiness Level – ORL Framework for Disasters Applications
Maturing the ORL Framework
The Disasters Lifecycle cluster in collaboration with the All Hazards Consortium developed initial ORLs with the electric utilities, and is now “operationalizing” ORLs for data-driven decision-making support to improve situational awareness. The criteria for the ORLs and a flowchart assessment tool, exercised by the AHC team at Duke Energy for response to the 2018 Hurricane Florence, proved very useful. The initial ORL criteria were defined for the electric sector’s use to transport work crews and restore power after destructive storms. However the usability criteria is expected to change for different disaster scenarios. Some factors may go across many use cases for many applications, such as security criteria that is key to establishing trust. However other factors are driven by the use case to address latency or resolution criteria. Work continues on refining strategies and criteria for assessing candidate datasets for specific operational use cases, and maturing the ORL concept as a Framework for different applications.

During this session we plan to address the issue of terminology to seek a common vocabulary relevant to various disasters application, leveraging what we’ve learned from the electric utility sector. We also would like to examine the ORL assessment tool and how the current ORL criteria are applied and look for gaps and lessons learned. The goal is to refine a framework strategy enabling the ORL concept to be applied to other disasters applications.
Increase the use and value of Earth science data and information., Strengthen the ties between observations and user communities (e.g. technologies, research, education and applications)., Promote techniques to articulate and measure the socioeconomic value and benefit of Earth science data, information and applications.
Breakout SessionKaren Moe, Dave JonesKaren Moe, Dave Jones, TBD
Skim the Surface, Jump In
Data to Decisions, Disaster Lifecycle, Information Quality, Semantic Technologies, Usability
Trusted Data, Usability, Disasters Applications
NoM: Karen Moe, Dave Jones; S: Karen Moe, Dave Jones, TBD
37
Mapping & Connecting the Earth Science Project Landscapes
Mapping the Landscape
There are many efforts underway to map the landscape of projects in earth science, including Research Data Alliance, EarthCube, ESIP and the RISCAPE project in Europe. This session will provide the current status of many of these efforts. We would also like to use this session to describe how ESIP meeting participants can contribute to the mapping effort during the Winter Meeting.

Ideally this session would be scheduled on Tuesday to give meeting participants to add to the landscape that be available during the meeting for additions and corrections.
Increase the use and value of Earth science data and information., Strengthen the ties between observations and user communities (e.g. technologies, research, education and applications)., Position ESIP to play a major role in Earth science issues (e.g. addressing effects of climate change mitigation, adaptation and supporting sustainable science data infrastructure).
Breakout SessionRebecca KoskelaErin Robinson, Rowena Davis, Lesley Wyborn (not confirmed), Rebecca KoskelaJump InCOPDESS, Discovery, Education, Information Quality, Research Data Management, Science Software, Semantic Technologies, Sustainable Data ManagementMaybeM: Rebecca Koskela; S: Erin Robinson, Rowena Davis, Lesley Wyborn (not confirmed), Rebecca Koskela
38
The Latest in Citations Part II [postponed to Summer ESIP]
The Latest in Citations Part II
You heard what ESIP is doing, but what about other groups and agencies? This session will present the various citation formats being practiced by other groups and compare how similar or dissimilar they are to each other and how much of that is driven by their specific communities and/or availability of resources.
Increase the use and value of Earth science data and information., Strengthen the ties between observations and user communities (e.g. technologies, research, education and applications).
Breakout SessionRuth Duerr, Jessica Hausman, Mark ParsonsHeather Brown, Jessica Hausman, and moreSkim the SurfaceCOPDESS, Software & Services CitationscitationsMaybeM: Ruth Duerr, Jessica Hausman, Mark Parsons; S: Heather Brown, Jessica Hausman, and more
39
Scaling Machine Learning Applications in Earth Sciences
Scalable Architectures for ML and AI
This panel will focus on scalable architectures for implementing machine learning and AI models across Earth Sciences focus areas. The specific details would include both HPC and cloud-centric operational pipelines for automated data processing, parallel multi-GPU model implementations, cluster scheduling, resource optimization and time to delivery - a few tools of discussion can focus around DC/OS, Terraform/Nomad, and Kubernetes. In addition to compute constraints, the panel also encourages discussion on ML framework optimizations and operational complexity, including available frameworks and workflow tools like Tensorflow, Mxnet, Pytoch, Google ML pipeline, AWS Sagemaker and others. GPU hardware optimization is another topic of interest where the panel will focus on how new generation GPU’s (with more CUDA cores) are able to perform faster training as opposed to old generation GPUs.
Increase the use and value of Earth science data and information., Position ESIP to play a major role in Earth science issues (e.g. addressing effects of climate change mitigation, adaptation and supporting sustainable science data infrastructure).
PanelKimberly Hines, Sangram GangulySangram Ganguly, Nikunj Oza, TJ Vandal, Kim Hines, Diptanu Choudhury, Tom Faulhaber
Skim the Surface, Jump In
Machine Learning
Machine Learning, HPC, Cloud
MaybeM: Kimberly Hines, Sangram Ganguly; S: Sangram Ganguly, Nikunj Oza, TJ Vandal, Kim Hines, Diptanu Choudhury, Tom Faulhaber
40
The Metadata GameThe Metadata GameThe Metadata Game brings teams together to collaborate to create complete metadata repositories.
Increase the use and value of Earth science data and information., Strengthen the ties between observations and user communities (e.g. technologies, research, education and applications).
Breakout SessionTed HabermannJump InDocumentationMetadata,FAIRNoM: Ted Habermann; S:
41
Metadata Use CasesUse CasesMetadata standards can support many use cases and approaches to sharing information about many kinds of resources. This session provides an opportunity for data providers and researchers to share ideas about needs and solutions.
Increase the use and value of Earth science data and information., Strengthen the ties between observations and user communities (e.g. technologies, research, education and applications).
Breakout SessionTed HabermannDeep DiveDocumentationMetadataNoM: Ted Habermann; S:
42
FAIR Samples and Collections in the Earth, Space, & Environmental Sciences
FAIR Samples & Collections
FAIR principles need to be applied to all outputs of scientific research, including physical materials such as natural and synthetic specimens that are collected as part of the scientific process. Making physical samples and collection FAIR requires virtual representations of the physical objects that can be located on the web via a persistent identifier and that are documented with sufficient metadata that are persistently accessible in trustworthy metadata catalogs to be findable and reusable, and that follow standard protocols for accessibility and interoperability. While best practices for sample identification, documentation, and citation are emerging, there are many open questions and challenges that need to be solved, including vocabularies and ontologies for describing and classifying samples; effective and consistent ways to link samples with the literature and digital data; as well as policies and infrastructure for trustworthy curation of the sample metadata and of the actual physical objects. In this session we will look at ongoing and new initiatives related to physical samples as part of digital research data infrastructure and explore how ESIP can facilitate collaborative solutions to some of the most urgent problems.
Increase the use and value of Earth science data and information., Promote techniques to articulate and measure the socioeconomic value and benefit of Earth science data, information and applications.
Breakout Session
Kerstin Lehnert, Lesley Wyborn
Lindsay Powers, Doug Fils, Ramona Walls
Deep Dive
COPDESS, Data Models, Discovery, ESIP-E2SIP, Research Data Management, Semantic Technologies
Physical samples, identifiers, FAIR
NoM: Kerstin Lehnert, Lesley Wyborn; S: Lindsay Powers, Doug Fils, Ramona Walls
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