UKSG Conference 2017 Breakout - Crossref Event Data: tools for DIY analyses of non-traditional...
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Event Data: DIY analyses of non-traditional scholarly mentions (and more) Jennifer Kemp Madeleine Watson UKSG April 2017
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Transcript of UKSG Conference 2017 Breakout - Crossref Event Data: tools for DIY analyses of non-traditional...
Event Data: DIY analyses of non-traditional scholarly mentions (and more) Jennifer Kemp
Madeleine Watson
UKSG April 2017
What are we talking about?
Article
Blog
Tweet
Wikipedia page
Dataset
Article
Blog
Tweet
Wikipedia page
Dataset
What does this have to do with Event Data?
Article
Blog
Tweet
Wikipedia
Datasets
Event Data provides a unique record of the web activity related to individual scholarly content items.
Where does our data come from?
Great, you’re making more metrics?
No metrics
No totals
No scores
No interpretation
(Also: no user interface)
It’s just open attention data
Tweet or retweet?
Discussion versus promotion?
Reference added or an edit war?
Ready for your interpretation
What does the data look like?
<subject> <relation> <object>
<wikipedia page> <references> <article>
<tweet> <mentions> <article>
<reddit comment> <mentions> <article>
<dataset> <relates to> <article>
Each event returns:
Data Contributors Event Data
API
The Crossref Event Data Pipeline
How much data?Between 10 - 100k Events every dayOver 2 million Events since 1st March 2017
Take a look at our User Guide to learn more:https://www.eventdata.crossref.org/guide/
Event Data Query Api
Filter by prefix, work, source or date
Can I do ____ with Event Data?
Graph modellingData visualisationsDiscoverabilityRecommendationBibliometricsAltmetricsLinked data
Graph modeling
Neo4j
These both represent a dataset DOI which cites an article DOI, which has been discussed on Twitter.
Dataset
Article
Tweet
relation type
Discoverability & comparison
● Editors can identify new areas to grow author submissions, track the reach of publications or quickly find reviewers based on publication network analysis
● Publishers can undertake metric-lead analysis to help drive business needs
● Researchers can analyze data from blogs and social media to help with preprint discoverability and impact analysis
Impact & Usage
● Track impact across subject areas, journals, publishers, funders etc.
● Publishers, journals or institutions can analyze data on their own outputs and include in impact reports
● Publishing service providers can feed Event Data in their usage or altmetrics dashboards or visualisations
● Funders can use Event Data to isolate and track the dissemination and usage of the research they funded
Recommendations & tools
● Build a reading recommendation tool for researchers by using Event Data to analyse co-citations in Wikipedia
● Notify an organization that their research is trending
● Notify an author their research has been recommended on F1000 or referenced in Wikipedia
● Build a collaboration tool which connects and introduces researchers
Part 2: Use Case discussion
I work at a _______________. I would like to _____________ events about ______________ specifically to ________________.
Sound good? _____________
(institution type) (track, collect, analyze, etc.)
(my journal, an author, my institution, etc.)
(store it until we figure out what to do with it, build a new metric, follow the conversation about a few DOIs, etc.)
(yes/no/it depends)
Next Steps & Questions
Questions
?Further Development Additional sources
More data contributorsInterested? [email protected]
Beta testing
Late April - next several months
Interested? [email protected]
https://www.crossref.org/services/event-data/
Thank you!
& special guest appearance by [email protected]
[email protected]@crossref.org
