7. Example Scenario
Melissa creates mouse1
David creates mouse2
Layne uses performs RNAseq analysis on
mouse1 and mouse2 to generate
dataset3, which he subsequently
curates and analyzes
Layne writes publication pmid:12345
about the results of his analysis
Layne explicitly credits Melissa as an
author but not David.
8. Credit is connected
=> Credit to Melissa is asserted, but credit to David can be inferred
11. Others have been here before
http://www.w3.org/TR/prov-o/ https://github.com/vivo-isf
12. A little VIVO-ISF History
eagle-i
Resources
People
VIVO
Semantic
VIVO
Coordination
eagle-i
Clinical
activities
eagle-i is an ontology-driven application . . . for collecting and
searching research resources.
VIVO is an ontology-driven application . . . for collecting and
displaying information about people.
CTSAconnect produced a single Integrated Semantic
Framework, a modular collection of ontologies that also
includes clinical expertise
This new research activity exchange standard is VIVO-ISF
13.
14.
15. Roles can be hierarchal
Representation of more
general or more specific
roles
Definitions are inherited
Role based queries enable
aggregate results
Extensibile by end users to
address local needs
Computable when
represented in a formal
language
16. What kind of questions can we ask?
Find all people who made contributions to a given
publication
Find all publications or research entities to which a person
has contributed
Track what types of contributions a person made during
their post-doc
Find all persons at my institution who have contributed to
publications as a data curator or software developer
Find all papers that used software developed by a given
person
Find all research entities that are related to the funding of a
particular grant
17. Contact Info
VIVO-ISF Data Standard github issue tracker:
https://github.com/vivo-isf/vivo-isf-data-standard/
issues
Discussion List:
https://groups.google.com/forum/#!forum/vi
vo-isf
Simplest diagram modeling the structure of attribution as implemented in PROV (and roughly mirrored in VIVO-ISF using different term labels). PROV highlights three core types of things - Entities (resources), Activities (processes), and Agents (persons, organizations, etc). These can be connected directly by binary relations, if nothing more is needed to be said about them. Or they can be connected by reified relationships (Attribution between an Entity and an Agent, or Association between an Activity and an Agent), when additional information is to be captured such as the role an agent played or a time/location of the relationship.
A graph representing this scenario. Note that we removed the Activity and Association components of the core model as we are interested in capturing Attribution between an entity and an Agent. Association between an Activity and Agent could also be modeled if desired.
Note also that we intentionally attributed melissa on the publication, but not david. David’s attribution could be inferred from the graph.
Graph showing how the ISF structure for representing this is similar to prov (note that prov and isf names for each node/edge is shown (where applicable).
Here we renamed the original roles to be framed as ontology roles, and broke down some of the more complex ones into simpler sub-roles that were mentioned in the CASRAI definitions (e.g. the software definition described several more specific contribution roles such as programmer, designer, tester).
The numbers refer to the number of the original CRediT role here: http://credit.casrai.org/proposed-taxonomy/
Some example types of questions that could be answered by structuring contribution data in this way.
