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? eventdata@crossref.org

Beta testing

Late April - next several months

Interested? eventdata@crossref.org

https://www.crossref.org/services/event-data/

Thank you!

& special guest appearance by jwass@crossref.org

jkemp@crossref.orgmwatson@crossref.org