Digital Information Curation in Multilingual Contexts
Summary
Digital information curation in multilingual contexts encompasses the processes by which information is selected, organised, enriched and preserved across diverse language communities. These processes involve metadata generation, taxonomy alignment, translation and cross-lingual linking to ensure that knowledge resources remain discoverable and semantically coherent regardless of language. Challenges include heterogeneity of linguistic structures, inconsistent use of controlled vocabularies, and the need for interoperable metadata schemas. Advances in machine translation, natural language processing and knowledge-graph technologies have facilitated automated entity recognition, metadata harmonisation and semantic annotation across language editions of repositories such as Wikipedia, institutional archives and digital libraries. Effective multilingual curation underpins equitable access to information in global research collaborations, emergency response scenarios and cultural heritage institutions, ensuring that users can retrieve consistent and contextualised content irrespective of their native tongue.
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Digital Information Curation in Multilingual Contexts publication trend
The graph below shows the total number of articles in digital information curation in multilingual contexts across all publications each year (not limited to Nature Index journals).
Technical terms
Cross-lingual information retrieval (CLIR): Techniques that allow users to submit queries in one language and retrieve documents in another, typically by translating queries or documents and aligning semantic representations.
Metadata interoperability: The capacity of disparate metadata schemas to exchange and interpret information consistently, enabling resource discovery across different systems and languages.
Knowledge graph: A structured network of entities and relationships that supports semantic linking and reasoning, often used to interconnect multilingual data sources.
Controlled vocabulary: A predefined set of terms used for indexing and retrieval, ensuring consistency in the description of content across language editions.
Entity recognition: Automated identification and classification of proper names, concepts and other predefined entities within text, facilitating multilingual annotation and linking.
References
- Crowdsourcing Knowledge Production of COVID-19 Information on Japanese Wikipedia in the Face of Uncertainty: Empirical Analysis. Journal of Medical Internet Research (2023).
- Transforming higher education: a decade of integrating wikipedia and wikidata for literacy enhancement and social impact. Journal of Computers in Education (2024).
- Wikipedia and Medicine: Quantifying Readership, Editors, and the Significance of Natural Language. Journal of Medical Internet Research (2015).
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