Publicly reported feedback and issues for Aggie Experts
Aggie Experts is a joint pilot project between the Office of the Provost and the UC Davis Library team. Its purpose is to create a central registry of UC Davis scholarship produced by faculty, researchers, experts and creators. Aggie Experts can be used as an expertise discovery platform for finding collaborators, mentors and expert opinions, as a showcase of the UC Davis excellence in research, teaching and community service, and as a tool that reduces the administrative load on UC Davis researchers and administrators. In the course of two years (2020-2022) we will be expanding the registry by adding faculty from the College of Engineering and adjusting its functionality based on user feedback.
The overarching principles of building out the Aggie Experts platform are to avoid hosting data locally and to present all content as linked data. The data sources are described in more detail below. Aggie Experts is inspired by the VIVO software tool and uses their schema to represent the data in RDF format. For more information, refer to our GitHub repository.
We use the UC Davis identity management system as the source for the scholar’s name, title and unit affiliation. Researchers can change that information in the campus directory listing.
Publications metadata is based on scholars’ claims of publications in support of the UC Open Access Policy. Faculty can review with publications they have claimed, and what additional publications are pending review and approval in the California Digital Library instance of Symplectic Elements publication management system.
Research subject areas are generated in one of the following manners:
The researcher has already selected relevant keywords in the Symplectic Elements publication management system.
The keywords are extracted from the researchers’ claimed publications, and the ones that occur three or more times are added to their profiles.
The grants data are obtained from the university’s financial data warehouse.
Activities and contributions to research, teaching and the community are extensive. We work with faculty to choose from the following list of fields for each new iteration of the registry. It is by no means exhaustive, and we are open to additions: Name, Home department, Current position, Additional affiliations, Photo, Research bio, Openness to collaborations, Websites, Courses, Awards, Patents, Grants, Publications, Datasets, Software, Exhibits, Performances, Conference papers, Gray literature, Collaborations, Mentorship, Service. This list exceeds the scope of the pilot and is intended long-term visioning.
A good registry needs to have a good search mechanism. We enable discovery of expertise on campus through researchers’ scholarship reflected in each field we add to the registry.
Aggie Experts is intended to function in accordance with the FAIR data principles. In many cases faculty are required to provide the same information to the university, grant-funding agencies, and conferences. Exports from Aggie Experts would allow the faculty to reformat their content for those needs and reduce the time spent on administrative work.
To report an issue or provide feedback go to https://github.com/ucd-library/aggie-experts-public-issues/issues/new/choose
Review Issues to see all reported issues.
Thanks for taking an active role in the development of Aggie Experts!
August 2019 Convene Faculty Advisory Board and establish the parameters for a minimal viable product
October 2020 Roll out to the Department of Materials Science and Engineering
Data fields: affiliations, titles, email contact, publications
Functionalities: search, export of publications as a RIS file
March 2021 Roll out to the Department of Biological and Agricultural Engineering
Data fields: research areas
Functionalities: improved search
May 2021 Roll out to the Department of Mechanical and Aerospace Engineering
Functionalities: refinement of previous iteration
July 2021
Data fields: grants
Functionalities: website plug-in
TBD
Functionalities: subject-expertise visualization