Scalable data harmonization, enrichment and validation. Data access, .parsing, cleaning, harmonization, enrichment,
Obtaining valid conclusions depends on efficient and reliable harmonization and augmentation of the raw entries.
Furthermore, we show how external sources of metadata, for instance, on authors, publishers, or geographical places, can be used to enrich and verify bibliographic information. This type of ecosystem has potential for wider implementation in related studies and other bibliographies.
Research use is part of validation
Discussion: potential ML/AI
selitykset miten erilaiset arviot on tehty. Nämä kannattais tehdä melkein erillisenä ekaks että niitä vois sitten käyttää myös muualla. Tämän jälkeen yhdistää tekstiin ja ehkä lyhentää jne. Tarkoitan siis esim. kuvausta siitä miten formaattitietoja puuttuvat on täydennetty jne. Eikö nämä pidä jotenkin olla mukana?
Towards a unified view: catalogue integration
This paper demonstrates how such challenges can be overcome by specifically tailored data analytical ecosystems that provide scalable tools for data processing and analysis.
Recognition of duplicates
Furthermore, we show how external sources of metadata, for instance, on authors, publishers, or geographical places, can be used to enrich and verify bibliographic information. This type of ecosystem has potential for wider implementation in related studies and other bibliographies.
Open bibliographic data science
data organization, data and code sharing, interfaces, software modules, analytical ecosystems