Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
Towards Metadata-enriched Literary Corpora in Line with FAIR Principles: 19/20MetaPNC
Cezary Rosiński1, Agnieszka Karlińska4, Marek Kubis2, Patryk Hubar1, Jan Wieczorek3
1The Institute of Literary Research of the Polish Academy of Sciences, Poland; 2Adam Mickiewicz University in Poznan, Poland; 3Wroclaw University of Science and Technology, Poland; 4NASK National Research Institute
We aim to introduce a comprehensive workflow for the enrichment and linking the metadata of a literary corpus, including an implementation of FAIR principles, which have been developed in the field of scientific data management. We will present the practical application of the workflow using a corpus of Polish novels.
Investigating Decentralized Alternatives to Collaborative Long-term Research Data Preservation Infrastructure
Pascal Belouin, Kim Pham, Steffen Hennicke
Max Planck Institute for the History of Science, Germany
The sustainability, preservation, and long-term availability of research data is a growing concern for academic institutions. We aim to propose an alternative to the existing, "centralized" solutions to this problem by presenting our attempts to build a prototype for a decentralized research data repository relying on decentralized, blockchain-adjacent technology.
There is no “I” in "Infrastructure": Creating a shared data-centric DH Infrastructure for Cultural Heritage Research in Saxony/Germany
Dirk Goldhahn, Peter Mühleder, Franziska Naether
Saxon Academy of Sciences and Humanities, Germany
Establishing and operating research infrastructures designed for long-term use is a challenge. This holds especially true in small to medium scale institutes carrying out short-term projects. In our presentation, we would like to describe our approach to building an infrastructure for collecting and linking local cultural heritage data in Saxony.
From unstructured texts to RDF-star-based open research data queryable by references
University of Basel, Switzerland
Humanities textual data is full of references to persons and locations given in various languages. Researchers want to perform queries to retrieve data, in which a certain place or a person is mentioned, irrespective of the language of the text. In this paper, I present how we automatically extract named entities (geolocation information and person references) from textual data and homogenize and store them as Linked Open Data (LOD) with unique identifiers such as the GeoName ID and the GND (Gemeinsame Normdatei) number. Then the plain references in the text are substituted with standoff links to the corresponding RDF resources and the textual document is stored in RDF format. This enables humanities scholars to perform advanced SPARQL queries to collect textual resources containing specific references regardless of the language of the text. Furthermore, the relations between these named entities can be parsed from the text based on ontology definition, dependency graph of sentences, and POS tags to be added to the knowledge graph. Since the citability of the information is crucial for humanities research, this workflow adds the metadata regarding the source document of extracted information to the edges of the knowledge graph using RDF-star. This allows queries for documents containing a certain relationship between entities through SPARQL-star.
Russian-Ukrainian War Art: Data Collection and Analysis
The Russia-Ukraine war became an impetus for the creation of many objects of folk and professional art. There are street art, memes, fine arts, poetry, music, etc. The goal of the research is development of knowledge representation models of this objects, as well as collecting and analysis of the collection.