This event has ended. Create your own event on Sched.
Join the 2020 ESIP Winter Meeting Highlights Webinar on Feb. 5th at 3 pm ET for a fast-paced overview of what took place at the meeting. More info here.
Back To Schedule
Thursday, January 9 • 12:00pm - 1:30pm
Research Object Citation Cluster Working Session

Sign up or log in to save this to your schedule, view media, leave feedback and see who's attending!

Feedback form is now closed.
ESIP has published guidelines for citing data and for citing software and services. These have been important and influential ESIP products. Now a new cluster is working to address the issues of “research object” citation writ large. The cluster has been working to identify the various types of research objects that could or should be cited such as samples, instruments, 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. We find that citation of different types of objects may need to address different concerns and that different approaches may be necessary for different concerns and objects. We have, therefore, been working through a matrix that attempts to map all the various objects and citation concerns.

In this working session, we will provide a brief overview of the cluster's work to date on determining when different research objects get IDs. We will then work in small groups to determine when different research objects need to be identified to ensure reproducibility or validity of a result. For this purpose, we define reproducibility as the ability to independently recreate or confirm a result (not the data). A result could be a finding in a scientific paper, a legal brief, a policy recommendation, a model output or derived product — essentially any formal, testable assertion. This is essentially a provenance use case. It is very broad, but distinct from the credit and even the access concerns of citation. This is primarily about unambiguous reference. When does an object become a first-class research object?
To approach the problem, we will break up into 4-5 groups to define and give examples of different clusters of research objects and then work to answer When or under what circumstance is it necessary to identify an object to enable reproducibility. 
Potential groups include:
  1. Literature and related objects (not to be discussed)
  2. Software and related objects — Dan Katz
  3. Data and related objects — Mark Parsons
  4. Samples — Sarah Ramdeen
  5. Ontologies and vocabularies — Ruth Duerr
  6. Complex research objects (esp. but not exclusively learning resources) — Nancy Hoebelheinrich
  7. Instruments and facilites — Mike Daniels
  8. Organizations 
  9. Activities
We encourage everyone  to start drafting definitions and examples in the spreadsheet now: https://docs.google.com/spreadsheets/d/1VEYPLgTsCR_zbMUbThonBrqaYqBiMT4e525NzFi7ql8/edit#gid=1494916301
Our goal is to have a draft recommendation or complete matrix by the end of the meeting as well as potential follow-on activities for the cluster.

How to Prepare for this Session: Participants should be familiar with existing ESIP citation guidelines and have reviewed the minutes of the last several meetings, especially the "Objects and Concerns Matrix". See http://wiki.esipfed.org/index.php/Research_Object_Citation


View Recording:
https://youtu.be/5MXzBLu7hjg (abbreviated due to breakout group emphasis of session).

  • What is a ‘thing’? ‘Research object’ is a defined term in other communities. Our conception is broader. Perhaps we need a new term, but much of the issue is defining when something becomes a ‘thing’ that is named and located.
  • The particular citation use case matters a lot. Reproducibility demands different considerations than credit. The cluster will consider more use cases.
  • There appears to be classes of things that can be treated similarly, but we haven’t sorted that out yet.

avatar for Jessica Hausman

Jessica Hausman

NASA HQ / ASRC Federal
avatar for Mark Parsons

Mark Parsons

Editor in Chief, Data Science Journal

Thursday January 9, 2020 12:00pm - 1:30pm EST
Linden Oak
  Linden Oak, Working Session