2019 ESIP Winter Meeting

Session Abstract:
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.

The UMM model documentation can be found at https://wiki.earthdata.nasa.gov/display/CMR/CMR+Documents

Meeting Notes can be found at https://tinyurl.com/yau45sqq

Session Takeaways (post-meeting):
1) The UMM models are continuing to evolve based on user needs and mission requirements.
2) There should be a regular schedule for UMM releases.
3) As UMM-S records mature, there needs to be UMM-S equivalent records go to the CMR.

Session Abstract:
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, workflows, physical samples, instruments, 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.

Agenda:

1. Intro and explanation about history of citing research Objects (Mark Parsons, Rensselaer Polytechnic Institute)
2. Work done by Force11 on software citationand what's next (Dan Katz, Univ. Illinois at Urbana-Champaign -- remote)
3. Identifiers for physical samples -- lessons learned and plans for IGSN2 (Kerstin Lehnert)
4. The Digitial Object Interface Protocol (DOIP) (Larry Lannom, CNRI--presented by Mark Parsons)
5. Discussion. What is a research object? What should be cited? What are the general use cases to consider.

Notes at https://docs.google.com/document/d/18ooEixbchKp-qgAG7qtnebKrWDYsutt4d2eX3HsaWls/edit?usp=sharing

Session Takeaways (post-meeting):
1) A grand challenge of citation is determining the purpose of citation: Credit? Access? Reusability? Interoperability?

Session Abstract:
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.
Agenda: Set-up of problem (20-30 minutes):

• Intro (Hills)
• RDA Data Rescue (Diggs
• EarthCube/GeoDeepDive (Goring)
• ESIP Data Stewardship (Mayernick) slides
• Data Nomination Toolkit (Boehm)
• CODATA IDAR TG (Diggs)

Working on defining the path to a solution (45-60 minutes) Topics might include:

• How to define risk
• categories of risk
• ways to quantify (or weight) various risk factors
• other geo-disciplines that we might need to reach out to
• other scientific disciplines that have addressed data at risk evaluation
• ??

Summary/wrap up (5-10 minutes)
Please help with collaborative note-taking HERE!

Session Takeaways (post-meeting):
1) Sharing/telling data rescue stories (the process; what was enabled by the rescue; financial benefit) is necessary to get the essential support for data rescue efforts.
2) Coordination with aligned groups is key to be sure that effort is not duplicated and that efforts are aligned.
3) Harnessing Code for America style-infrastructure to pair motivated people/students with relevant skills to the opportunities to participate in data rescue efforts could be a good model to identify data heroes / data minions within the data nomination tool.

How 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.

This is a working session -- there will be post-its for you to play with! Perfect for the last session of the day. It will be light on slides, heavy on small group conversation. The outputs of our time together will be digitized and share back to the ESIP community.