Merge pull request 'Update of introduction to the deduplication section' (#59) from deduplication into main

Reviewed-on: #59
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Claudio Atzori 2023-11-06 12:48:03 +01:00
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# Deduplication
Metadata records about the same scholarly work can be collected from different providers. Each metadata record can possibly carry different information because, for example, some providers are not aware of links to projects, keywords or other details. Another common case is when OpenAIRE collects one metadata record from a repository about a pre-print and another record from a journal about the published article. For the provision of statistics, OpenAIRE must identify those cases and “merge” the two metadata records, so that the scholarly work is counted only once in the statistics OpenAIRE produces.
The OpenAIRE Graph is populated by aggregating metadata records from distinct data sources whose content typically overlaps. For example, the collection of article metadata records from publisher' archives (e.g. Frontiers, Elsevier, Copernicus) and from pre-print platforms (e.g. ArXiv.org, UKPubMed, BioarXiv.org). In order to support monitoring of science, the OpenAIRE Graph implements record deduplication and merge strategies, in such a way the scientific production can be consistently statistically represented. Such strategies reflect the following intuition behind OpenAIRE monitoring: "Two metadata records are equivalent when they describe the same research product, hence they feature compatible resource types, have the same title, the same authors, or, alternatively, the same PID". Finally, groups of duplicates can be whitelisted or blacklisted, in order to manually refine the quality of this strategy.
It should be noticed that publication dates do not make a difference, as different versions of the same product can be published at different times; e.g. the pre-print and a published version of a scientific article, which should be counted as one object; abstracts, subjects, and other possible related fields, are not used to strenghten similarity, due to their heterogeneity or absence across different data sources. Moreover, even when two products are indicated as one a new version of the other, the presence of different authors will not bring them into the same group, to avoid unfair distribution of scientific reward.
Groups of duplicates are finally merged into a new "dedup" record that embeds all properties of the merged records and carries provenance information about the data sources and the relative "instances", i.e. manifestations of the products, together with their resource type, access rights, and publishing date.
## Methodology overview