Using shape expressions (ShEx) to share rdf data models and to guide curation with rigorous validation

International Conference, European Semantic Web Conference, ESWC (16th. 2019. Portorož, Slovenia

ARL White Paper on Wikidata: Opportunities and Recommendations

In this Association of Research Libraries white paper, a task force of expert Wikidata users recommend a variety of ways for librarians to use the open knowledge base in advancing global discovery of their collections, faculty, and institutions. Beyond the task force, many library professionals from within and outside the Wikimedia community contributed to the white paper in draft form, offering a productive mix of enthusiasm and skepticism that improved the final product. ARL convened the task force and wrote this white paper to inform its membership about GLAM (galleries, libraries, archives, and museums) activity in Wikidata and to highlight opportunities for research library involvement, particularly in community-based collections, community-owned infrastructure, and collective collections

ARL White Paper on Wikidata: Opportunities and Recommendations

This white paper highlights opportunities for research library involvement in Wikidata, particularly in community-based collections, community-owned infrastructure, and collective collections

Knowledge Graphs Evolution and Preservation -- A Technical Report from ISWS 2019

One of the grand challenges discussed during the Dagstuhl Seminar "Knowledge Graphs: New Directions for Knowledge Representation on the Semantic Web" and described in its report is that of a: "Public FAIR Knowledge Graph of Everything: We increasingly see the creation of knowledge graphs that capture information about the entirety of a class of entities. [...] This grand challenge extends this further by asking if we can create a knowledge graph of "everything" ranging from common sense concepts to location based entities. This knowledge graph should be "open to the public" in a FAIR manner democratizing this mass amount of knowledge." Although linked open data (LOD) is one knowledge graph, it is the closest realisation (and probably the only one) to a public FAIR Knowledge Graph (KG) of everything. Surely, LOD provides a unique testbed for experimenting and evaluating research hypotheses on open and FAIR KG. One of the most neglected FAIR issues about KGs is their ongoing evolution and long term preservation. We want to investigate this problem, that is to understand what preserving and supporting the evolution of KGs means and how these problems can be addressed. Clearly, the problem can be approached from different perspectives and may require the development of different approaches, including new theories, ontologies, metrics, strategies, procedures, etc. This document reports a collaborative effort performed by 9 teams of students, each guided by a senior researcher as their mentor, attending the International Semantic Web Research School (ISWS 2019). Each team provides a different perspective to the problem of knowledge graph evolution substantiated by a set of research questions as the main subject of their investigation. In addition, they provide their working definition for KG preservation and evolution

NFDI4Culture - Consortium for research data on material and immaterial cultural heritage

Digital data on tangible and intangible cultural assets is an essential part of daily life, communication and experience. It has a lasting influence on the perception of cultural identity as well as on the interactions between research, the cultural economy and society. Throughout the last three decades, many cultural heritage institutions have contributed a wealth of digital representations of cultural assets (2D digital reproductions of paintings, sheet music, 3D digital models of sculptures, monuments, rooms, buildings), audio-visual data (music, film, stage performances), and procedural research data such as encoding and annotation formats. The long-term preservation and FAIR availability of research data from the cultural heritage domain is fundamentally important, not only for future academic success in the humanities but also for the cultural identity of individuals and society as a whole. Up to now, no coordinated effort for professional research data management on a national level exists in Germany. NFDI4Culture aims to fill this gap and create a usercentered, research-driven infrastructure that will cover a broad range of research domains from musicology, art history and architecture to performance, theatre, film, and media studies. The research landscape addressed by the consortium is characterized by strong institutional differentiation. Research units in the consortium's community of interest comprise university institutes, art colleges, academies, galleries, libraries, archives and museums. This diverse landscape is also characterized by an abundance of research objects, methodologies and a great potential for data-driven research. In a unique effort carried out by the applicant and co-applicants of this proposal and ten academic societies, this community is interconnected for the first time through a federated approach that is ideally suited to the needs of the participating researchers. To promote collaboration within the NFDI, to share knowledge and technology and to provide extensive support for its users have been the guiding principles of the consortium from the beginning and will be at the heart of all workflows and decision-making processes. Thanks to these principles, NFDI4Culture has gathered strong support ranging from individual researchers to highlevel cultural heritage organizations such as the UNESCO, the International Council of Museums, the Open Knowledge Foundation and Wikimedia. On this basis, NFDI4Culture will take innovative measures that promote a cultural change towards a more reflective and sustainable handling of research data and at the same time boost qualification and professionalization in data-driven research in the domain of cultural heritage. This will create a long-lasting impact on science, cultural economy and society as a whole

Editorial of the Special issue on Cultural heritage and semantic web

[no abstract available

Researching Wikidata’s added value in accommodating audio-visual researchers’ information needs

Linked Data is playing an increasingly significant role in the field of cultural heritage. This paper aims to find out how Linked Data techniques can add value for external researchers who collaborate at cultural heritage institutions and will take the form of a case study at the Netherlands Institute for Sound & Vision (NISV). NISV manages an audio-visual collection and is looking for ways to implement Linked Data principles on its collection. Specifically, NISV is looking at a general purpose knowledge base, Wikidata. This research is part of a broader project aiming to map the possibilities of Linked Data principles for internal and external audiences. This paper will focus on external audiences that collaborate at NISV and will describe these external researchers, including their information needs when it comes to accessing NISV’s audiovisual collection. To see what information it contains and how this existing information matches external researchers’ information needs, we analyse NISV’s General Thesaurus for Audio-visual Archives (GTAA). We also analyse the Person facet of Wikidata to compare both datasets and see which data is relevant to align with the GTAA, specifically for the needs of external researchers. Based on this, we propose an improvement to the Clariah Mediasuite as a mock-up prototype, which incorporates Wikidata as an additional functionality to serve as a method for performing exploratory research on external researchers’ subjects of interest. A qualitative evaluation of the mock-up prototype by external researchers shows that the proposed addition to the Clariah Mediasuite adds value for external researchers, as long as they are carrying out research in an exploratory manner. We discuss limitations of the proposed addition, including incomplete and corrupted data, overabundance of properties, technical limitations and future work

Examining the Impact of Algorithm Awareness on {W}ikidata's Recommender System Recoin

The global infrastructure of the Web, designed as an open and transparent system, has a significant impact on our society. However, algorithmic systems of corporate entities that neglect those principles increasingly populated the Web. Typical representatives of these algorithmic systems are recommender systems that influence our society both on a scale of global politics and during mundane shopping decisions. Recently, such recommender systems have come under critique for how they may strengthen existing or even generate new kinds of biases. To this end, designers and engineers are increasingly urged to make the functioning and purpose of recommender systems more transparent. Our research relates to the discourse of algorithm awareness, that reconsiders the role of algorithm visibility in interface design. We conducted online experiments with 105 participants using MTurk for the recommender system Recoin, a gadget for Wikidata. In these experiments, we presented users with one of a set of three different designs of Recoin's user interface, each of them exhibiting a varying degree of explainability and interactivity. Our findings include a positive correlation between comprehension of and trust in an algorithmic system in our interactive redesign. However, our results are not conclusive yet, and suggest that the measures of comprehension, fairness, accuracy and trust are not yet exhaustive for the empirical study of algorithm awareness. Our qualitative insights provide a first indication for further measures. Our study participants, for example, were less concerned with the details of understanding an algorithmic calculation than with who or what is judging the result of the algorithm