2022, Rossenova, Lozana, Schubert, Zoe, Vock, Richard, Sohmen, Lucia, Günther, Lukas, Duchesne, Paul, Blümel, Ina, Aizawa, Akiko

A new FOSS (free and open source software) toolchain and associated workflow is being developed in the context of NFDI4Culture, a German consortium of research- and cultural heritage institutions working towards a shared infrastructure for research data that meets the needs of 21st century data creators, maintainers and end users across the broad spectrum of the digital libraries and archives field, and the digital humanities. This short paper and demo present how the integrated toolchain connects: 1) OpenRefine - for data reconciliation and batch upload; 2) Wikibase - for linked open data (LOD) storage; and 3) Kompakkt - for rendering and annotating 3D models. The presentation is aimed at librarians, digital curators and data managers interested in learning how to manage research datasets containing 3D media, and how to make them available within an open data environment with 3D-rendering and collaborative annotation features.

2022, Tavakoli, Mohammadreza, Faraji, Abdolali, Vrolijk, Jarno, Molavi, Mohammadreza, Mol, Stefan T., Kismihók, Gábor

Attaining those skills that match labor market demand is getting increasingly complicated, not in the last place in engineering education, as prerequisite knowledge, skills, and abilities are evolving dynamically through an uncontrollable and seemingly unpredictable process. Anticipating and addressing such dynamism is a fundamental challenge to twenty-first century education. The burgeoning availability of data, not only on the demand side but also on the supply side (in the form of open educational resources) coupled with smart technologies, may provide a fertile ground for addressing this challenge. In this paper, we propose a novel, Artificial Intelligence (AI) driven approach to the development of an open, personalized, and labor market oriented learning recommender system, called eDoer. We discuss the complete system development cycle starting with a systematic user requirements gathering, and followed by system design, implementation, and validation. Our recommender prototype (1) derives the skill requirements for particular occupations through an analysis of online job vacancy announcements

2022, Sohmen, Lucia, Rack, Fabian, Heuveline, Vincent, Bisheh, Nina

Die zunehmende Verfügbarkeit von Forschungsdaten eröffnet Forschenden neue Möglichkeiten, mit von Dritten erstellten Forschungsdaten zu arbeiten. Dieser Beitrag befasst sich mit der Frage, welche rechtlichen Rahmenbedingungen gelten, wenn diese nachgenutzten Forschungsdaten öffentlich verfügbar gemacht werden sollen. Im Speziellen geht der Artikel dabei auf Bildersuchmaschinen und das Veröffentlichen von Bildkorpora ein. Dabei wird dargestellt, dass es bei der öffentlichen Zugänglichmachung von unübersichtlichen Bildmengen keine hundertprozentige Sicherheit geben kann. Durch bestimmte Abwägungen und technische Mittel kann sich dieser aber angenähert werden.

2022, Kaliuzhna, Nataliia, Auhunas, Sabina

Development and implementation of Current Research Information Systems (CRIS) is one of the most transparent and practical approaches to curate research information on a national level. The process of building and implementing such systems is a complex and time consuming where successful results heavily depend on the established research information infrastructure of a country, the interoperability of the systems and the quality of the information which reside in them. The purpose of this paper is to analyse the existing Ukrainian Research Information Infrastructure and identify which databases could be reused and integrated with a national Ukrainian Current Research Information System (URIS). The analysis showed that there are functional databases and registries that collect data on research activities and could be used as a data sources for the URIS. In particular, the Unified State Electronic Database on Education is a potential data source on higher educational institutions, the National Repository of Academic Texts - on metadata on research output, internal database of the National Research Foundation of Ukraine and database on research projects maintained by Ukrainian Institute of Scientific Technical and Economic Information - on projects. Secondly, it was identified that Ukrainian research infrastructure lacks complete, up-to-date registry on researchers. Finally, we discussed the challenges and solutions for further steps in building national CRIS.

2022, Klünder, Jil, Karras, Oliver, Madeiral, Fernanda, Lassenius, Casper

[Background:] Teamwork, coordination, and communication are a prerequisite for the timely completion of a software project. Meetings as a facilitator for coordination and communication are an established medium for information exchange. Analyses of meetings in software projects have shown that certain interactions in these meetings, such as proactive statements followed by supportive ones, influence the mood and motivation of a team, which in turn affects its productivity. So far, however, research has focused only on certain interactions at a detailed level, requiring a complex and fine-grained analysis of a meeting itself. [Aim:] In this paper, we investigate meetings from a more abstract perspective, focusing on the polarity of the statements, i.e., whether they appear to be positive, negative, or neutral. [Method:] We analyze the relationship between the polarity of statements in meetings and different social aspects, including conflicts as well as the mood before and after a meeting. [Results:] Our results emerge from 21 student software project meetings and show some interesting insights: (1) Positive mood before a meeting is both related to the amount of positive statements in the beginning, as well as throughout the whole meeting, (2) negative mood before the meeting only influences the amount of negative statements in the first quarter of the meeting, but not the whole meeting, and (3) the amount of positive and negative statements during the meeting has no influence on the mood afterwards. [Conclusions:] We conclude that the behaviour in meetings might rather influence short-term emotional states (feelings) than long-term emotional states (mood), which are more important for the project.

2022, Sakor, Ahmad, Singh, Kuldeep, Vidal, Maria-Esther

Social media networks have become a prime source for sharing news, opinions, and research accomplishments in various domains, and hundreds of millions of posts are announced daily. Given this wealth of information in social media, finding related announcements has become a relevant task, particularly in trending news (e.g., COVID-19 or lung cancer). To facilitate the search of connected posts, social networks enable users to annotate their posts, e.g., with hashtags in tweets. Albeit effective, an annotation-based search is limited because results will only include the posts that share the same annotations. This paper focuses on retrieving context-related posts based on a specific topic, and presents PINYON, a knowledge-driven framework, that retrieves associated posts effectively. PINYON implements a two-fold pipeline. First, it encodes, in a graph, a CORPUS of posts and an input post; posts are annotated with entities for existing knowledge graphs and connected based on the similarity of their entities. In a decoding phase, the encoded graph is used to discover communities of related posts. We cast this problem into the Vertex Coloring Problem, where communities of similar posts include the posts annotated with entities colored with the same colors. Built on results reported in the graph theory, PINYON implements the decoding phase guided by a heuristic-based method that determines relatedness among posts based on contextual knowledge, and efficiently groups the most similar posts in the same communities. PINYON is empirically evaluated on various datasets and compared with state-of-the-art implementations of the decoding phase. The quality of the generated communities is also analyzed based on multiple metrics. The observed outcomes indicate that PINYON accurately identifies semantically related posts in different contexts. Moreover, the reported results put in perspective the impact of known properties about the optimality of existing heuristics for vertex graph coloring and their implications on PINYON scalability.

2022, Hoppe, Anett, Yu, Ran, Liu, Jiqun, Amigo, Enrique

Since its inception, the World Wide Web has become a major information source, consulted for a diversity of informational tasks. With an abundance of information available online, Web search engines have been a main entry point, supporting users in finding suitable Web content for ever more complex information needs. The IWILDS workshop series invites research on complex search activities related to human learning. It provides an interdisciplinary platform for the presentation and discussion of recent research on human learning on the Web, welcoming perspectives from computer & information science, education and psychology.

2022, Oelen, Allard, Stocker, Markus, Auer, Sören, Aizawa, Akiko

As the number of published scholarly articles grows steadily each year, new methods are needed to organize scholarly knowledge so that it can be more efficiently discovered and used. Natural Language Processing (NLP) techniques are able to autonomously process scholarly articles at scale and to create machine readable representations of the article content. However, autonomous NLP methods are by far not sufficiently accurate to create a high-quality knowledge graph. Yet quality is crucial for the graph to be useful in practice. We present TinyGenius, a methodology to validate NLP-extracted scholarly knowledge statements using microtasks performed with crowdsourcing. The scholarly context in which the crowd workers operate has multiple challenges. The explainability of the employed NLP methods is crucial to provide context in order to support the decision process of crowd workers. We employed TinyGenius to populate a paper-centric knowledge graph, using five distinct NLP methods. In the end, the resulting knowledge graph serves as a digital library for scholarly articles.

2022, Entrup, Elias, Eppelin, Anita, Ewerth, Ralph, Hartwig, Josephine, Tullney, Marco, Wohlgemuth, Michael, Hoppe, Anett, Nugent, Ronan

Finding a suitable open access journal to publish scientific work is a complex task: Researchers have to navigate a constantly growing number of journals, institutional agreements with publishers, funders’ conditions and the risk of Predatory Publishers. To help with these challenges, we introduce a web-based journal recommendation system called B!SON. It is developed based on a systematic requirements analysis, built on open data, gives publisher-independent recommendations and works across domains. It suggests open access journals based on title, abstract and references provided by the user. The recommendation quality has been evaluated using a large test set of 10,000 articles. Development by two German scientific libraries ensures the longevity of the project.

2022, Huang, Hao, Al Hasan, Mohammad, Xiong, Li

Causality has been discussed for centuries, and the theory of causal inference over tabular data has been broadly studied and utilized in multiple disciplines. However, only a few works attempt to infer the causality while exploiting the meaning of the data represented in a data structure like knowledge graph. These works offer a glance at the possibilities of causal inference over knowledge graphs, but do not yet consider the metadata, e.g., cardinalities, class subsumption and overlap, and integrity constraints. We propose CareKG, a new formalism to express causal relationships among concepts, i.e., classes and relations, and enable causal queries over knowledge graphs using semantics of metadata. We empirically evaluate the expressiveness of CareKG in a synthetic knowledge graph concerning cardinalities, class subsumption and overlap, integrity constraints. Our initial results indicate that CareKG can represent and measure causal relations with some semantics which are uncovered by state-of-the-art approaches.