VIVO Cornell: Lessons from the field Kathy Chiang, Jon Corson-Rikert, Elizabeth Hines, Joseph McEnerney Stella Mitchell, Christopher Westling, Tim Worrall. Abstract VIVO is: an organic approach to reflecting the research at an institution; the antithesis of a static set of web pages.
Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.
Kathy Chiang, Jon Corson-Rikert, Elizabeth Hines, Joseph McEnerney
Stella Mitchell, Christopher Westling, Tim Worrall
Revised view: Mockup 3
Mockup 3: Expanded
Current production VIVO
Revised view: Mockup 1
Revised view: Mockup 2
Publications management: PubMed, Researcher ID, Google Scholar
We coordinate and integrate our contribution to Cornell’s information discovery goals as researchers’ information practices change and competing and complementary information products are introduced. Some researchers pay detailed attention to their web presence, others do not. With VIVO 1.5 we are designing display options to meet the varying needs of our researchers. We are looking at how publications could be managed to meet both individual and institutional goals.
Faculty lab web page
VIVO Cornell data come from heterogeneous overlapping sources reflecting the diversity and complexity of our institution. In addition to manual data entry (with all its attendant quality issues) the Cornell data systems of record deliver duplicate and contradictory data that must be cleaned and reconciled.
We have developed a tool that semi-automates this process. We apply heuristic matching algorithms to VIVO data to cluster similar names (of people, journal titles and organizations).The URI Tool presents those results for manual review and resolution. We identify, or create (from online sources such as Ulrichs) an authoritative version and then merge all the variants to that name. Journal titles can vary by one word; we have researchers with the same name, but in different Colleges; this manual step is the only reliable way to clean a dataset of this size.
VIVO data sources and data feeds
Data integrity: URI Tool
Since we are required to take data from Cornell’s systems of record we cannot ‘clean up’ the data in VIVO. It must be done at the source. For example: several Colleges at Cornell use Activity Insight from Digital Measures. It is difficult to identify missing or malformed values using the Activity Insight administrative interface. We are developing a tool that presents the information in a format that College administrators can use to correct the data, which will then feed into VIVO.
AI feedback form