forked from D-Net/openaire-graph-docs
Merge pull request 'Restructuring data provision section' (#34) from restructure_data_provision into main
Reviewed-on: D-Net/openaire-graph-docs#34
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---
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# OpenAIRE compatible sources
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# OpenAIRE compatible sources
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The OpenAIRE aggregator collects metadata records from content providers compliant to the OpenAIRE guidelines.
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The OpenAIRE Guidelines help repository managers expose publications, datasets and CRIS metadata via the OAI-PMH protocol in order to integrate with OpenAIRE infrastructure.
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You can find more information in https://guidelines.openaire.eu/en/latest/
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# Indexing
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The final version of the OpenAIRE Research Graph is indexed on a Solr server that is used by the OpenAIRE portals (EXPLORE, CONNECT, PROVIDE) and APIs, the latter adopted by several third-party applications and organizations, such as:
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The final version of the OpenAIRE Research Graph is indexed on a Solr server that is used by the OpenAIRE portals ([EXPLORE](https://explore.openaire.eu), [CONNECT](https://connect.openaire.eu), [PROVIDE](https://provide.openaire.eu)) and APIs, the latter adopted by several third-party applications and organizations, such as:
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* The OpenAIRE Research Graph APIs and Portals will offer to the EOSC (European Open Science Cloud) an Open Science Resource Catalogue, keeping an up to date map of all research results (publications, datasets, software), services, organizations, projects, funders in Europe and beyond.
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* The OpenAIRE Graph APIs and Portals will offer to the EOSC (European Open Science Cloud) an Open Science Resource Catalogue, keeping an up to date map of all research results (publications, datasets, software), services, organizations, projects, funders in Europe and beyond.
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* DSpace & EPrints repositories can install the OpenAIRE plugin to expose OpenAIRE compliant metadata records via their OAI-PMH endpoint and offer to researchers the possibility to link their depositions to the funding project, by selecting it from the list of project provided by OpenAIRE.
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# Usage counts
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# Usage Statistics Indicators
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Usage counts cover the needs of content providers and consumers offering added value to assist them in reaching their goals.
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Usage Statistics indicators for research products, like publications, datasets,etc., are an important complement to other (traditional and alternative) bibliometric indicators to provide a comprehensive and recent view of the impact of such resources but also about their authors, institutions and the platforms themselves. They are taking into account different levels of information: the usage of data sources, the usage of individual items in the context of their resource type and the usage of individual web resources or files.
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They include metrics of usage activity of Open Access Repositories categorizing the data retrieved by country, number of downloads, number of views, number of repositories and all derivative quantitative open metrics, comprehensively.
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Usage Statistics Indicators are built by the OpenAIRE's UsageCounts Service. The service collects usage data and consolidated usage statistics reports respectively, from its distributed network of data providers (repositories, e-journals, CRIS) by utilizing open standards and protocols and delivers reliable, consolidated and comparable usage metrics like counts of item downloads and metadata views conformant to COUNTER Code of Practice.
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You can find more information about the UsageCounts service [here](https://usagecounts.openaire.eu/).
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You can find more information about the UsageCounts service [here](https://usagecounts.openaire.eu/).
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# Merge by id
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<span className="todo">TODO</span>
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In the metadata aggregation system it is common to find the same record provided by
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different datasources and, sometimes, even inside the same datasource (especially in
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case of aggregators). As the harmonisation processes are performed per datasource
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contents, the relative records are the output of different mapping implementations.
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This approach has the advantage to be deeply customisable to catch datasource specific
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aspects, but it leaves room for inconsistencies when evaluating the different mappings
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across the various datasources.
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This phase is therefore responsible to compensate for such inconsistencies and performs
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a global grouping of every record available in the graph:
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- entities are grouped by [`id`](../data-model/entities/result#id)
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- relations are grouped by [`source`, `target`, `reltype`](../data-model/relationships#the-relationship-object)
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This ensures that the same record, possibly assigned to different types by different
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mappings, appears only once in the graph and under a single typing. In case of clashing
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identifiers, the properties are merged (including the provencance information), considering
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the following precedence order for the result typing:
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```
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publication > dataset > software > other
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```
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The same holds for relationships, as the same (e.g.) DOI-to-DOI citation relation could
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be aggregated from multiple sources, this grouping phase would collapse all the different
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duplicates onto a single relation that would however include all the individual provenances.
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# Stats analysis
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The OpenAIRE Graph is also processed by a pipeline for extracting the statistics
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and producing the charts for funders, research initiative, research infrastructures,
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and policymakers available on [MONITOR](https://monitor.openaire.eu).
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Based on the information available on the graph, OpenAIRE provides a set of
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indicators for monitoring the funding and research impact and the uptake of
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Open Science publishing practices, such as Open Access publishing of publications
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and datasets, availability of interlinks between research products, availability
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of post-print versions in institutional or thematic Open Access repositories, etc.
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@ -151,6 +151,7 @@ const sidebars = {
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},
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{ type: 'doc', id: 'data-provision/finalisation' },
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{ type: 'doc', id: 'data-provision/indexing' },
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{ type: 'doc', id: 'data-provision/stats' }
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]
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},
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{
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