WHAT - mAuth is a semantic crawler designed for harvesting information on artwork attributions in the web of data. mAuth API is implemented in Python, using Flask microframework.
WHY - mAuth is a proof of concept. The aim is leveraging Semantic Web technologies to (a) support historians' daily tasks (such as retrieving information and sources), (b) evaluate the methodology underpinning decisions made by art historical data providers, and (c) investigate how authoritativeness can be automatically interpreted given a set of rules and believes shared in a community.
HOW - Attributions are sorted so as to immediately highlight the most well-documented, updated, and authoritative ones. The ranking is based on common requirements in the art historical methodology - information providers' reputation, timeliness of the attribution, completeness of motivations and cited sources, and relevance of information.
LIMITS - Attributions are extracted from secondary sources (e.g. cataloguing records, online web pages), hence the goodness of the attribution itself is not evaluated. Data sources currently harvested include art historical photo archives, such as the Federico Zeri Foundation (University of Bologna), the Berenson Library, Villa I Tatti (Univeristy of Harvard), and the Frick Art Reference Library of New York; multipurposes datasets, such as Wikidata, DBpedia, and VIAF; and libraries, such as BNF, LOC, DBN. More data sources will be (hopefully!) added soon.