Publication

Automating Data Imports in a DSpace-CRIS’s Institutional Repository

2025

Abstract

The migration of Infoscience, EPFL’s institutional repository, to DSpace-CRIS required a custom Python-based pipeline to automate the ingestion of research outputs and datasets. Limitations in default DSpace-CRIS import tools, such as insufficient query controls, incomplete metadata mappings, and a lack of deduplication mechanisms, necessitated a tailored approach. 

The pipeline leverages the DSpace REST API to enable precise queries, metadata reconciliation, and robust deduplication. It incorporates fallback mechanisms, such as publisher-specific APIs, for full-text retrieval when standard tools like Unpaywall and CrossRef prove insufficient. Key challenges included reconciling authorship with EPFL directories, aligning metadata across diverse collections, and maintaining data consistency during imports. 

The developer track presentation will provide a visual breakdown of the pipeline’s architecture, highlight key challenges, and illustrate the solutions implemented. The presentation will complement this by delving deeper into the technical details and lessons learned. Both formats will offer practical insights for repository managers and developers seeking to automate data imports and optimize workflows in institutional repositories.

Official source

https://infoscience.epfl.ch/entities/publication/6deba0e7-b27c-4383-ae15-3cbb5eb2119c

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2025

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/6deba0e7-b27c-4383-ae15-3cbb5eb2119c

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Related concepts (32)

Institutional repository

An institutional repository is an archive for collecting, preserving, and disseminating digital copies of the intellectual output of an institution, particularly a research institution. Academics also utilize their IRs for archiving published works to increase their visibility and collaboration with other academics However, most of these outputs produced by universities are not effectively accessed and shared by researchers and other stakeholders As a result Academics should be involved in the implementation and development of an IR project so that they can learn the benefits and purpose of building an IR.

Full-text search

In text retrieval, full-text search refers to techniques for searching a single computer-stored document or a collection in a full-text database. Full-text search is distinguished from searches based on metadata or on parts of the original texts represented in databases (such as titles, abstracts, selected sections, or bibliographical references). In a full-text search, a search engine examines all of the words in every stored document as it tries to match search criteria (for example, text specified by a user).

Information retrieval

Information retrieval (IR) in computing and information science is the process of obtaining information system resources that are relevant to an information need from a collection of those resources. Searches can be based on full-text or other content-based indexing. Information retrieval is the science of searching for information in a document, searching for documents themselves, and also searching for the metadata that describes data, and for databases of texts, images or sounds.

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