Enrico Daga

The process of news digitalization over the past decades has released massive amounts of news content, revolutionizing consumer access to news and disrupting traditional business models. These radical changes have also introduced new opportunities for media content analysis, opening up new scenarios for ambitious large-scale media analytics initiatives, which can go well beyond the relatively small-scale studies currently carried out by media scholars and practitioners. However, take-up of computational methods to support media content analysis activities has been rather modest, reflecting a degree of disconnect between the needs of scholars and practitioners for task-specific and usable software solutions and the state of the art in computational techniques for news media analysis. In this article, we perform an initial step toward bridging this gap, by looking in detail at the task of fine-grained news classification . In particular, we propose a typology of news topics, which is formally specified and realized into a family of reusable ontologies. The proposed model has been validated empirically, through an analysis of a multilingual news corpus, as well as formally, in terms of the functional and logical properties of the ontologies. Our analysis brings together the media and computer science literature, connecting the formal definitions provided in this article to the concepts used by media scholars.

New curatorial practices have emerged in the last decade to increase the engagement of citizens in cultural heritage, ranging from visitors’ experiential feedback to exhibitions and cultural artifa...

This article explores and presents innovative methods and technologies for supporting citizen curation of cultural heritage. Relevant outcomes of the Social Participation, Cohesion and Inclusion through Cultural Engagement (SPICE) project are presented, focusing on enhancing the state of content management and delivery strategies in museums and memory institutions. We argue that citizen curation requires a principled way of managing and integrating citizen responses, contributions and dataflows in the domain of cultural heritage, raising challenges and opportunities such as integration of distributed and diverse data sources, authoritativeness, interdependence, privacy, data reuse and rights management. The solution is a Linked Data Hub (LDH), which integrates museum collections and user-generated content and repurposes them to end-user systems tailored to specific use cases for citizens and museum practitioners. Such LDH must be non-open , by offering an approach that gives citizens and organisations, such as museums or engagement agencies, meaningful control over their data by implementing user-tailored policies and negotiated access and terms of use. Additionally, our solution addresses privacy violations in user-contributed content by offering a near-real-time content monitoring framework. We present the LDH discussing pilot applications within the EU-funded project SPICE, including ‘Deep Viewpoints’, which currently supports the Irish Museum of Modern Art (IMMA) in citizen curation activities. Overall, this article serves as a critical milestone in closing functional gaps and advancing the state of technology in managing citizen responses and contributions in the cultural heritage domain.

Knowledge Graphs are becoming widely used as a method to capture and integrate diverse sources of data into a unified structure of nodes and links. Cultural heritage is an active domain for Knowledge Graph research, bringing together the metadata of cultural objects with associated information about their use and history. Tools exist for the searching and browsing of Knowledge Graphs but on their own they often do not offer the interpretative support required by a more general audience. This paper describes an approach to creating a layer of interpretation over a Knowledge Graph. Experts in the cultural domain, without expertise in the underlying technology, can curate paths through the Knowledge Graph, selecting and associating cultural objects, which are automatically displayed in the path with relevant content from the Knowledge Graph. Path authors can also provide additional interpretation as well invite responses from followers of the paths. A case study is described in the domain of European pipe organs in which domain experts can curate paths through a Knowledge Graph of currently approximately 2000 objects. The potential of the approach as a way of incrementally formalizing changes or additions to the Knowledge Graph emerged as a theme with domain experts. The applicability of the approach to cultural Knowledge Graphs in general is discussed.

What should a data integration framework for knowledge engineers look like? Recent research on Knowledge Graph construction proposes the design of a façade, a notion borrowed from object-oriented software engineering. This idea is applied to SPARQL Anything, a system that allows querying heterogeneous resources as-if they were in RDF, in plain SPARQL 1.1, by overloading the SERVICE clause. SPARQL Anything supports a wide variety of file formats, from popular ones (CSV, JSON, XML, Spreadsheets) to others that are not supported by alternative solutions (Markdown, YAML, DOCx, Bibtex). Features include querying Web APIs with high flexibility, parametrised queries, and chaining multiple transformations into complex pipelines. In this paper, we describe the design rationale and software architecture of the SPARQL Anything system. We provide references to an extensive set of reusable, real-world scenarios from various application domains. We report on the value-to-users of the founding assumptions of its design, compared to alternative solutions through a community survey and a field report from the industry.