CrowdHeritage: Crowdsourcing for Improving the Quality of Cultural Heritage Metadata

Information

Vassilis Tzouvaras¹  Maria Ralli¹  Giorgos Stamou¹  Orfeas Menis-Mastromichalakis¹  Eirini Kaldeli¹  Spyros Bekiaris¹ 

[1] Artificial Intelligence and Learning Systems Laboratory, School of Electrical and Computer Engineering, National Technical University of Athens, 15780 Athens, Greece;

关键词: crowdsourcing;    automatic enrichment;    user validation;    annotation model;    cultural heritage;   

DOI  :  10.3390/info12020064

来源: DOAJ

【 摘 要 】

The lack of granular and rich descriptive metadata highly affects the discoverability and usability of cultural heritage collections aggregated and served through digital platforms, such as Europeana, thus compromising the user experience. In this context, metadata enrichment services through automated analysis and feature extraction along with crowdsourcing annotation services can offer a great opportunity for improving the metadata quality of digital cultural content in a scalable way, while at the same time engaging different user communities and raising awareness about cultural heritage assets. To address this need, we propose the CrowdHeritage open end-to-end enrichment and crowdsourcing ecosystem, which supports an end-to-end workflow for the improvement of cultural heritage metadata by employing crowdsourcing and by combining machine and human intelligence to serve the particular requirements of the cultural heritage domain. The proposed solution repurposes, extends, and combines in an innovative way general-purpose state-of-the-art AI tools, semantic technologies, and aggregation mechanisms with a novel crowdsourcing platform, so as to support seamless enrichment workflows for improving the quality of CH metadata in a scalable, cost-effective, and amusing way.

【 授权许可】

Unknown