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Inclusion, transparency,
quality, state of the art
technology.

Our methodological approach is based on the following operational quality criteria:

  • Openness and transparency: Methodological assumptions are openly and clearly presented.
  • Coverage and accuracy: As detailed in graph.openaire.eu multiple data sources are ingested in the OpenAIRE research graph for coverage to the fullest extent possible, in order to provide meaningful indicators.
  • Clarity and replicability: We describe our construction methodology in detail, so that it can be verified and used by the scholarly communication community to create ongoing updates to our proposed statistics and indicators.
  • Readiness and timeliness: The methodology is built around well-established open databases and already tested knowledge extraction technologies - natural language processing (NLP)/machine-learning (ML) - using operational workflows in OpenAIRE to warrant timely results.
  • Trust and robustness: Our methodology also strives to be reliable, robust, and aligned to other assessment methods so that it can be operationalized, used and reused, in conjunction with other assessment methods.
The text above is modified from this report (DOI: 10.2777/268348).
Completeness, inclusion, transparency and replicability

How? It’s about open data and collaboration.

  • Built on the OpenAire Research GraphLinked scholarly information from open initiatives around the world. Beyond publications.
  • Based on Open Science principlesOpen data sources, Open APIs, well documented metrics and indicators.
  • Relevance for the CommunityIndicators development and visualizations to meet community requirements.
OpenAIRE Research Graph

Inclusion, transparency,
quality, state of the art
technology.

Our methodological approach is based on the following operational quality criteria:

  • Openness and transparency: Methodological assumptions are openly and clearly presented.
  • Coverage and accuracy: As detailed in graph.openaire.eu multiple data sources are ingested in the OpenAIRE research graph for coverage to the fullest extent possible, in order to provide meaningful indicators.
  • Clarity and replicability: We describe our construction methodology in detail, so that it can be verified and used by the scholarly communication community to create ongoing updates to our proposed statistics and indicators.
  • Readiness and timeliness: The methodology is built around well-established open databases and already tested knowledge extraction technologies - natural language processing (NLP)/machine-learning (ML) - using operational workflows in OpenAIRE to warrant timely results.
  • Trust and robustness: Our methodology also strives to be reliable, robust, and aligned to other assessment methods so that it can be operationalized, used and reused, in conjunction with other assessment methods.
The text above is modified from this report (DOI: 10.2777/268348).
OpenAIRE Research Graph
Completeness, inclusion, transparency and replicability

How?

It’s about open data and collaboration.

  • Built on the OpenAire Research GraphLinked scholarly information from open initiatives around the world. Beyond publications.
  • Based on Open Science principlesOpen data sources, Open APIs, well documented metrics and indicators.
  • Relevance for the CommunityIndicators development and visualizations to meet community requirements.
OpenAIRE
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OpenAIRE has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreements No. 777541 and 101017452
Creative-CommonsLicenceUnless otherwise indicated, all materials created by OpenAIRE are licenced underCC ATTRIBUTION 4.0 INTERNATIONALLICENSE
OpenAIRE
flag black white low
OpenAIRE has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreements No. 777541 and 101017452
Creative-CommonsLicenceUnless otherwise indicated, all materials created by OpenAIRE are licenced under
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