arXiv subjects

Benjamin Zapilko

Publications and source records attributed to Benjamin Zapilko.

12 recordsLinked to original sources

arXiv2025

Research Knowledge Graphs in NFDI4DataScience: Key Activities, Achievements, and Future Directions

As research in Artificial Intelligence and Data Science continues to grow in volume and complexity, it becomes increasingly difficult to ensure transparency, reproducibility, and discoverability. To address these challenges, as research artifacts should be understandable and usable by machines, the NFDI4DataScience consortium is developing and providing Research Knowledge Graphs (RKGs). Building upon earlier works, this paper presents recent progress in creating semantically rich RKGs using standardized ontologies, shared vocabularies, and automated Information Extraction techniques. Key achievements include the development of the NFDI4DS ontology, metadata standards, tools, and services designed to support the FAIR principles, as well as community-led projects and various implementations of RKGs. Together, these efforts aim to capture and connect the complex relationships between datasets, models, software, and scientific publications.

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arXiv2025

Research Knowledge Graphs: the Shifting Paradigm of Scholarly Information Representation

Sharing and reusing research artifacts, such as datasets, publications, or methods is a fundamental part of scientific activity, where heterogeneity of resources and metadata and the common practice of capturing information in unstructured publications pose crucial challenges. Reproducibility of research and finding state-of-the-art methods or data have become increasingly challenging. In this context, the concept of Research Knowledge Graphs (RKGs) has emerged, aiming at providing an easy to use and machine-actionable representation of research artifacts and their relations. That is facilitated through the use of established principles for data representation, the consistent adoption of globally unique persistent identifiers and the reuse and linking of vocabularies and data. This paper provides the first conceptualisation of the RKG vision, a categorisation of in-use RKGs together with a description of RKG building blocks and principles. We also survey real-world RKG implementations differing with respect to scale, schema, data, used vocabulary, and reliability of the contained data. We also characterise different RKG construction methodologies and provide a forward-looking perspective on the diverse applications, opportunities, and challenges associated with the RKG vision.

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arXiv2023

VADIS -- a VAriable Detection, Interlinking and Summarization system

The VADIS system addresses the demand of providing enhanced information access in the domain of the social sciences. This is achieved by allowing users to search and use survey variables in context of their underlying research data and scholarly publications which have been interlinked with each other.

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arXiv2022

Towards Automated Survey Variable Search and Summarization in Social Science Publications

Nowadays there is a growing trend in many scientific disciplines to support researchers by providing enhanced information access through linking of publications and underlying datasets, so as to support research with infrastructure to enhance reproducibility and reusability of research results. In this research note, we present an overview of an ongoing research project, named VADIS (VAriable Detection, Interlinking and Summarization), that aims at developing technology and infrastructure for enhanced information access in the Social Sciences via search and summarization of publications on the basis of automatic identification and indexing of survey variables in text. We provide an overview of the overarching vision underlying our project, its main components, and related challenges, as well as a thorough discussion of how these are meant to address the limitations of current information access systems for publications in the Social Sciences. We show how this goal can be concretely implemented in an end-user system by presenting a search prototype, which is based on user requirements collected from qualitative interviews with empirical Social Science researchers.

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arXiv2020

Investigating Software Usage in the Social Sciences: A Knowledge Graph Approach

Knowledge about the software used in scientific investigations is necessary for different reasons, including provenance of the results, measuring software impact to attribute developers, and bibliometric software citation analysis in general. Additionally, providing information about whether and how the software and the source code are available allows an assessment about the state and role of open source software in science in general. While such analyses can be done manually, large scale analyses require the application of automated methods of information extraction and linking. In this paper, we present SoftwareKG - a knowledge graph that contains information about software mentions from more than 51,000 scientific articles from the social sciences. A silver standard corpus, created by a distant and weak supervision approach, and a gold standard corpus, created by manual annotation, were used to train an LSTM based neural network to identify software mentions in scientific articles. The model achieves a recognition rate of .82 F-score in exact matches. As a result, we identified more than 133,000 software mentions. For entity disambiguation, we used the public domain knowledge base DBpedia. Furthermore, we linked the entities of the knowledge graph to other knowledge bases such as the Microsoft Academic Knowledge Graph, the Software Ontology, and Wikidata. Finally, we illustrate, how SoftwareKG can be used to assess the role of software in the social sciences.

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arXiv2019

A Digital Library for Research Data and Related Information in the Social Sciences

In the social sciences, researchers search for information on the Web, but this is most often distributed on different websites, search portals, digital libraries, data archives, and databases. In this work, we present an integrated search system for social science information that allows finding information around research data in a single digital library. Users can search for research data sets, publications, survey variables, questions from questionnaires, survey instruments, and tools. Information items are linked to each other so that users can see, for example, which publications contain data citations to research data. The integration and linking of different kinds of information increase their visibility so that it is easier for researchers to find information for re-use. In a log-based usage study, we found that users search across different information types, that search sessions contain a high rate of positive signals and that link information is often explored.

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arXiv2015

Evaluating the Quality of RDF Data Sets on Common Vocabularies in the Social, Behavioral, and Economic Sciences

From 2012 to 2015 together with other Linked Data community members and experts from the social, behavioral, and economic sciences (SBE), we developed diverse vocabularies to represent SBE metadata and tabular data in RDF. The DDI-RDF Discovery Vocabulary (DDI-RDF) is designed to support the dissemination, management, and reuse of unit-record data, i.e., data about individuals, households, and businesses, collected in form of responses to studies and archived for research purposes. The RDF Data Cube Vocabulary (QB) is a W3C recommendation for expressing data cubes, i.e. multi-dimensional aggregate data and its metadata. Physical Data Description (PHDD) is a vocabulary to model data in rectangular format, i.e., tabular data. The data could either be represented in records with character-separated values (CSV) or fixed length. The Simple Knowledge Organization System (SKOS) is a vocabulary to build knowledge organization systems such as thesauri, classification schemes, and taxonomies. XKOS is a SKOS extension to describe formal statistical classifications. To ensure high quality of and trust in both metadata and data, their representation in RDF must satisfy certain criteria - specified in terms of RDF constraints. In this paper, we evaluate the data quality of 15,694 data sets (4.26 billion triples) of research data for the social, behavioral, and economic sciences obtained from 33 SPARQL endpoints. We checked 115 constraints on three different and representative SBE vocabularies (DDI-RDF, QB, and SKOS) by means of the RDF Validator, a validation environment which is available at http://purl.org/net/rdfval-demo.

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arXiv2015

Constraints to Validate RDF Data Quality on Common Vocabularies in the Social, Behavioral, and Economic Sciences

To ensure high quality of and trust in both metadata and data, their representation in RDF must satisfy certain criteria - specified in terms of RDF constraints. From 2012 to 2015 together with other Linked Data community members and experts from the social, behavioral, and economic sciences (SBE), we developed diverse vocabularies to represent SBE metadata and rectangular data in RDF. The DDI-RDF Discovery Vocabulary (DDI-RDF) is designed to support the dissemination, management, and reuse of unit-record data, i.e., data about individuals, households, and businesses, collected in form of responses to studies and archived for research purposes. The RDF Data Cube Vocabulary (QB) is a W3C recommendation for expressing data cubes, i.e. multi-dimensional aggregate data and its metadata. Physical Data Description (PHDD) is a vocabulary to model data in rectangular format, i.e., tabular data. The data could either be represented in records with character-separated values (CSV) or fixed length. The Simple Knowledge Organization System (SKOS) is a vocabulary to build knowledge organization systems such as thesauri, classification schemes, and taxonomies. XKOS is a SKOS extension to describe formal statistical classifications. In this paper, we describe RDF constraints to validate metadata on unit-record data (DDI-RDF), aggregated data (QB), thesauri (SKOS), and statistical classifications (XKOS) and to validate tabular data (PHDD) - all of them represented in RDF. We classified these constraints according to the severity of occurring constraint violations. This technical report is updated continuously as modifying, adding, and deleting constraints remains ongoing work.

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arXiv2012

TheSoz: A SKOS Representation of the Thesaurus for the Social Sciences

The Thesaurus for the Social Sciences (TheSoz) is a Linked Dataset in SKOS format, which serves as a crucial instrument for information retrieval based on e.g. document indexing or search term recommendation. Thesauri and similar controlled vocabularies build a linking bridge for other datasets from the Linked Open Data cloud - even between different domains. The information and knowledge, which is exposed by such links, can be processed by Semantic Web applications. In this article the conversion process of the TheSoz to SKOS is described including the analysis of the original dataset and its structure, the mapping to adequate SKOS classes and properties, and the technical conversion. Furthermore mappings to other datasets and the appliance of the TheSoz are presented. Finally, limitations and modeling issues encountered during the creation process are discussed.

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arXiv2011

Web-Based Multi-View Visualizations for Aggregated Statistics

With the rise of the open data movement a lot of statistical data has been made publicly available by governments, statistical offices and other organizations. First efforts to visualize are made by the data providers themselves. Data aggregators go a step beyond: they collect data from different open data repositories and make them comparable by providing data sets from different providers and showing different statistics in the same chart. Another approach is to visualize two different indicators in a scatter plot or on a map. The integration of several data sets in one graph can have several drawbacks: different scales and units are mixed, the graph gets visually cluttered and one cannot easily distinguish between different indicators. Our approach marks a combination of (1) the integration of live data from different data sources, (2) presenting different indicators in coordinated visualizations and (3) allows adding user visualizations to enrich official statistics with personal data. Each indicator gets its own visualization, which fits best for the individual indicator in case of visualization type, scale, unit etc. The different visualizations are linked, so that related items can easily be identified by using mouse over effects on data items.

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arXiv2011

VIZGR: Combining Data on a Visual Level

In this paper we present a novel method to connect data on the visualization level. In general, visualizations are a dead end, when it comes to reusability. Yet, users prefer to work with visualizations as evidenced by WYSIWYG editors. To enable users to work with their data in a way that is intuitive to them, we have created Vizgr. Vizgr.com offers basic visualization methods, like graphs, tag clouds, maps and time lines. But unlike normal data visualizations, these can be re-used, connected to each other and to web sites. We offer a simple opportunity to combine diverse data structures, such as geo-locations and networks, with each other by a mouse click. In an evaluation, we found that over 85 % of the participants were able to use and understand this technology without any training or explicit instructions.

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arXiv2010

Establishing a Multi-Thesauri-Scenario based on SKOS and Cross-Concordances

This case study proposes a scenario with three topic-related thesauri, which have been connected with bilateral cross-concordances as part of a major terminology mapping initiative in the project KoMoHe (Mayr & Petras, 2008). The thesauri have already been or will be converted to SKOS and in order to not omit the relevant crosswalks, the mapping properties of SKOS will be used for modeling them adequately.

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