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The datahub: de/blending museum data

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dc.contributor.authorVandermaesen, Matthias
dc.date.accessioned2023-11-21T13:49:48Z
dc.date.available2023-11-21T13:49:48Z
dc.date.issued2018-06-06
dc.description.abstractThe Flemish Museums for Fine and Contemporary Art offer an overview of the art production in the Southern Netherlands and Belgium form the Middle Ages to the Twenty-First Century. The Flemish Art Collection is a non-profit organisation tasked with promoting the collection to an international and diverse audience. Delivery of knowledge and expertise curated by the museums is a big challenge. Blending cultural object records stored accross various databases and commercial registration systems is non-trivial and prevents opening up the collections across the walls of the museums. In 2015, the Flemish Art Collection started the Datahub Project. Over the past years, a modern metadata aggregation platform was built, leveraging open source technologies and open standards. This presentation will highlight the architecture of this platform, and the design process. The Datahub platform is a service oriented architecture and consists of three major components. The core is a home grown, reusable metadata aggregator called The Datahub. This web-application is build with the Symfony framework. Metadata records are ingested via a RESTful API, stored in a MongoDB database and disseminated via an OAI-PMH endpoint. User friendly discovery of metadata is covered via Project Blacklight and geared towards museal workers as well as the general public. Finally, we repurposed the Catmandu framework for flexible and extensible setup of ETL pipelines between the registration systems of the data providers, the Datahub and the discovery interface. Since we are exchanging information about cultural heritage objects, we use the LIDO XML exchange format designed and developed by ICOM. The project taught us several valuable lessons. What are the benefits of looking across the borders of your own domain? What are key success factors? How do you identify pitfalls? But it also raises a set of new questions. How do we go from here? What’s next? The tools and the codebase are freely available under a GPLv3 license and are actively documented and maintained on Github.en
dc.identifier.urihttps://hdl.handle.net/20.500.14391/1177
dc.language.isoen
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.rights.licensehttp://creativecommons.org/licenses/by-nc-nd/4.0
dc.sourceoai:repozitar.techlib.cz:1263
dc.subject.pshteorie datcs
dc.subject.pshmuzeacs
dc.subject.pshuměnícs
dc.subject.pshprojektycs
dc.subject.pshdata theoryen
dc.subject.pshmuseumsen
dc.subject.psharten
dc.subject.pshprojectsen
dc.subject.urihttp://psh.ntkcz.cz/skos/PSH6590
dc.subject.urihttp://psh.ntkcz.cz/skos/PSH143
dc.subject.urihttp://psh.ntkcz.cz/skos/PSH11591
dc.subject.urihttp://psh.ntkcz.cz/skos/PSH11945
dc.titleThe datahub: de/blending museum datacs
dc.typeconference paper
dspace.entity.typePublication
idr.event.endDate2018-06-07
idr.event.locationPraha (CZ)
idr.event.nameOriginalELAG 2018
idr.event.startDate2018-06-04
relation.isAuthorOfPublicatione72c6c35-8987-40c1-8ead-3af9d56c4bed
relation.isAuthorOfPublication.latestForDiscoverye72c6c35-8987-40c1-8ead-3af9d56c4bed
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