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Operas Metrics Service

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Presentation by Pierre Mounier, EHSS/OpenEdition/OPERAS

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OPERAS Metrics Service
Pierre Mounier
EHESS/OpenEdition/OPERAS
This project has received funding from the European
Union‘s Horizon 2020 research and innovation programme
under grant agreement No731102
Context of development
HIRMEOS Project (2017-2019)
• 9 partners: CNRS, UGOE, Dariah, UP, OBP, EKT, Unito, Oapen, MWS
• 5 platforms: OAPEN, OpenEdition, Ubiquity Press, GUP, EKT e-publishing
• 5 services: identification, entity recognition, certification, annotation,
metrics
• 3 levels of implementation: connect, visualize, reuse
• 1 common method: implement at the same time the same services on top
of a diverse environment
• 1 goal: to remedy the fragmentation of SSH scholcomm infrastructure by
aggregating and then coordinating projects, resources, expertise and data
Operas Metrics Service
Metrics Service: developed and
maintained by Ubiquity Press,
OpenBook Publishers and KU
Research
Metrics Service Main Objective
• Collect various usage and impact metrics related identified open
acces books:
• “Usage metrics” : dissemination on different plateforms
• “Impact metrics”: different types of citation, sharing, references
• “Identified books” : can be identified with different types of identifiers
• Collect and not merge the metrics (prevent the doughnut syndrome)
• Provide easy access and transparency to book metrics via various data
access and visualization tools
• Develop a modular, open, distributed infrastructure that would
prevent any lock-in from any player on the service
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Operas Metrics Service

  • 1. OPERAS Metrics Service Pierre Mounier EHESS/OpenEdition/OPERAS This project has received funding from the European Union‘s Horizon 2020 research and innovation programme under grant agreement No731102
  • 3. HIRMEOS Project (2017-2019) • 9 partners: CNRS, UGOE, Dariah, UP, OBP, EKT, Unito, Oapen, MWS • 5 platforms: OAPEN, OpenEdition, Ubiquity Press, GUP, EKT e-publishing • 5 services: identification, entity recognition, certification, annotation, metrics • 3 levels of implementation: connect, visualize, reuse • 1 common method: implement at the same time the same services on top of a diverse environment • 1 goal: to remedy the fragmentation of SSH scholcomm infrastructure by aggregating and then coordinating projects, resources, expertise and data
  • 5. Metrics Service: developed and maintained by Ubiquity Press, OpenBook Publishers and KU Research
  • 6. Metrics Service Main Objective • Collect various usage and impact metrics related identified open acces books: • “Usage metrics” : dissemination on different plateforms • “Impact metrics”: different types of citation, sharing, references • “Identified books” : can be identified with different types of identifiers • Collect and not merge the metrics (prevent the doughnut syndrome) • Provide easy access and transparency to book metrics via various data access and visualization tools • Develop a modular, open, distributed infrastructure that would prevent any lock-in from any player on the service
  • 7. Metrics Service architecture • Local module : • collection of drivers to collect usage metrics from various platforms • Identifier translation service • Widget to visualize the metrics on website • Dashboard to analyze data • Local/Central Module : • Metrics Database • Impact metrics collection • Public API to access metrics • OPERAS module • Metrics portal • Source code repository • Standard
  • 8. OPERAS Metrics past, present, future • HIRMEOS developements (done): • The data model : an open standard proposed to the community • The source code : available on GitHub under an open license • The implementations on the 5 HIRMEOS platforms • OPERAS Service (work in progress) • Further implementation on the platforms • A service provided to OPERAS members and partners: • Beta phase with a limited number of additional partners • Full release in OPERAS catalog of service • The metrics database : publicly accessible and released on a regular basis • Coordination with other similar initiatives: BISG ”Data Trust”
  • 9. This project has received funding from the European Union‘s Horizon 2020 research and innovation programme under grant agreement No731031 Open Standard: Measures
  • 10. This project has received funding from the European Union‘s Horizon 2020 research and innovation programme under grant agreement No731031 Open Standard • Book ID (RFC 3986) • Country (ISO 3166-2) • Timestamp (ISO 8601) • Measure (RFC 3986) • Platform (e.g. Google Books, Open Edition, OAPEN, OBP HTML Reader) • Type (e.g. Session, Download, Page View, Sale) • Namespace (e.g. metrics.operas-eu.org) • Version (e.g. v1, v2) • Event URI (RFC 3986)
  • 11. This project has received funding from the European Union‘s Horizon 2020 research and innovation programme under grant agreement No731031
  • 12. This project has received funding from the European Union‘s Horizon 2020 research and innovation programme under grant agreement No731031 Metrics Service: Usage Metrics • Drivers run locally, within the publishers/platform environment. • Independent modules (one per platform metrics are collected from). • Collect metrics and submit them to the metrics database via API. • Can be used by: • Publishers: to submit data from a third party platform hosting their books. • Platforms: to submit data from their own system. • Use the Identifier Translation Service for URI resolution.
  • 13. This project has received funding from the European Union‘s Horizon 2020 research and innovation programme under grant agreement No731031 Metrics Service: Drivers • Google Analytics* • Matomo* • Access Logs* • Google Books • OAPEN • Open Edition • JSTOR • World Reader • Classics Library • Unglue.it • OpenAIRE • IRUS-UK • Wikimedia • Crossref Cited-By
  • 14. This project has received funding from the European Union‘s Horizon 2020 research and innovation programme under grant agreement No731031 Metrics Service: impact metrics • Run centrally on behalf of publishers/platforms • Users submit a mapping of DOI->URLs for automatic collection • Collects data from: • Crossref EventData ■ Wikipedia ■ Wordpress.com • Twitter • Hypothes.is • Collect impact metrics and submit them to the metrics database via API
  • 15. This project has received funding from the European Union‘s Horizon 2020 research and innovation programme under grant agreement No731031 Metrics Service: Identifier Translation Service • Runs locally, within the publishers/platform environment • Translates book URIs to a preferred scheme (e.g. DOI) • Uses a database of book metadata from: • Publishers/Platform • Crossref • Can be integrated into an existing system (e.g. OMP) via API using containers provided
  • 16. This project has received funding from the European Union‘s Horizon 2020 research and innovation programme under grant agreement No731031 Metrics Service: Metrics API • Read access publicly available • HIRMEOS partners can write data • Aggregation by: • Measure • Country • Date
  • 17. This project has received funding from the European Union‘s Horizon 2020 research and innovation programme under grant agreement No731102 Metrics Service - Widget • Does not use an attention score. • Transparently displays metrics by source and type. • Links to the description of measure and to the dashboard for granularity
  • 18. This project has received funding from the European Union‘s Horizon 2020 research and innovation programme under grant agreement No731102 Metrics Service - Dashboard
  • 19. This project has received funding from the European Union‘s Horizon 2020 research and innovation programme under grant agreement No731102 Metrics Service - Dashboard
  • 20. Links • Data model: • metrics_db: https://github.com/hirmeos/metrics_db • Services: • metrics-api: https://github.com/hirmeos/metrics-api • altmetrics: https://github.com/hirmeos/altmetrics • translation*: https://github.com/hirmeos/identifier_translation_service • Visualization: • widget: https://github.com/hirmeos/widget • Dashboard: code: https://github.com/hirmeos/shiny_dashboard • Documentation: • metrics_portal: https://github.com/hirmeos/metrics_portal • available at: https://metrics.operas-eu.org/
  • 21. Links Drivers: ● metrics_submission: https://github.com/hirmeos/metrics_submission ● google_books: https://github.com/hirmeos/google_books_driver ● crossref_cited_by: https://github.com/hirmeos/crossref-citedby-driver ● access_logs: https://github.com/hirmeos/access_logs_driver ● oapen: https://github.com/hirmeos/oapen_driver ● world_reader: https://github.com/hirmeos/world_reader_driver ● google_analytics: https://github.com/hirmeos/google_analytics_driver ● open_edition: https://github.com/hirmeos/open_edition_driver ● unglue_it: https://github.com/hirmeos/unglueit_driver

Editor's Notes

  1. The measure could be defined by just its platform and type (e.g. Google Books page views), however, users may (and will) have discrepancies towards whether platform A’s page views can be aggregated to platform B’s. Therefore we are adding the flexibility for any implementing platform to define their aggregation methodology (which must be documented properly) and store their data under a particular namespace; if a namespace is contributed to by many (e.g. operas), then all uploaders should have to agree on the type of data that can be aggregated.
  2. Drivers may be used as a template to develop more drivers. There is a finite ways in which data can be collected, e.g. via API, CSV report, scraping. GA, Downloads, Matomo, may be used by platforms to collect their own data; others are third-party.
  3. Essentially equal to “find the DOI of a monograph associated to this ISBN”, or “find all ISBNs associated with this URL”
  4. Essentially equal to “find the DOI of a monograph associated to this ISBN”, or “find all ISBNs associated with this URL”