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

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