NameLázaro Gabriel Costa
Since15th April 2019
Costa, L; Freitas, N; da Silva, JR;
ACM JOURNAL ON COMPUTING AND CULTURAL HERITAGE
The Portuguese General Directorate for Book, Archives and Libraries (DGLAB) has selected CIDOC CRM as the basis for its next-generation digital archive management software. Given the ontological foundations of the Conceptual Reference Model (CRM), a graph database or a triplestore was seen as the best candidate to represent a CRM-based data model for the new software. We thus decided to compare several of these databases, based on their maturity, features, performance in standard tasks and, most importantly, the Object-Graph Mappers (OGM) available to interact with each database in an object-oriented way. Our conclusions are drawn not only from a systematic review of related works but from an experimental scenario. For our experiment, we designed a simple CRM-compliant graph designed to test the ability of each OGM/database combination to tackle the so-called diamond-problem in Object-Oriented Programming (OOP) to ensure that property instances follow domain and range constraints. Our results show that (1) ontological consistency enforcement in graph databases and triplestores is much harder to achieve than in a relational database, making them more suited to an analytical rather than a transactional role; (2) OGMs are still rather immature solutions; and (3) neomodel, an OGM for the Neo4j graph database, is the most mature solution in the study as it satisfies all requirements, although it is also the least performing.
Costa, L; da Silva, JR;
DIGITAL LIBRARIES FOR OPEN KNOWLEDGE, TPDL 2019
Dendro, a research data management (RDM) platform developed at FEUP/INESC TEC since 2014, was initially targeted at collaborative data storage and description in preparation for deposit in any data repository (CKAN, Zenodo, ePrints or B2Share). We implemented our own data deposit and dataset search features, consolidating the whole RDM workflow in Dendro: dataset exporting, automatic DOI attribution, and a dataset faceted search, among other features. We discuss the challenges faced when implemented these features and how they make Dendro more FAIR.
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