Search Results
TinyGenius: Intertwining natural language processing with microtask crowdsourcing for scholarly knowledge graph creation
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.
Diving into Knowledge Graphs for Patents: Open Challenges and Benefits
Textual documents are the means of sharing information and preserving knowledge for a large variety of domains. The patent domain is also using such a paradigm which is becoming difficult to maintain and is limiting the potentialities of using advanced AI systems for domain analysis. To overcome this issue, it is more and more frequent to find approaches to transform textual representations into Knowledge Graphs (KGs). In this position paper, we discuss KGs within the patent domain, present its challenges, and envision the benefits of such technologies for this domain. In addition, this paper provides insights of such KGs by reproducing an existing pipeline to create KGs and applying it to patents in the computer science domain.
Isn't a number and a URL enough? Why PIDs matter and technical solutions alone are not sufficient
In the presentation, we introduce the two projects PID4NFDI and PID Network Germany that deal with PIDs at the national level, present some initial findings and highlight their benefit for NFDI. PIDs are used and needed along the entire lifecycle of research data: from enabling to connecting. However, a particular focus for the presentation will be laid on harmonising and connecting.
Easy Semantification of Bioassays
Biological data and knowledge bases increasingly rely on Semantic Web technologies and the use of knowledge graphs for data integration, retrieval and federated queries. We propose a solution for automatically semantifying biological assays. Our solution contrasts the problem of automated semantification as labeling versus clustering where the two methods are on opposite ends of the method complexity spectrum. Characteristically modeling our problem, we find the clustering solution significantly outperforms a deep neural network state-of-the-art labeling approach. This novel contribution is based on two factors: 1) a learning objective closely modeled after the data outperforms an alternative approach with sophisticated semantic modeling; 2) automatically semantifying biological assays achieves a high performance F1 of nearly 83%, which to our knowledge is the first reported standardized evaluation of the task offering a strong benchmark model.
A Data Model for Linked Stage Graph and the Historical Performing Arts Domain
The performing arts are complex, dynamic and embedded into societal and political systems. Providing means to research historical performing arts data is therefore crucial for understanding our history and culture. However, currently no commonly accepted ontology for historical performing arts data exists. On the example of the Linked Stage Graph, this position paper presents the ongoing process of creating an application-driven and efficient data model by leveraging and building upon existing standards and ontologies like CIDOC-CRM, FRBR, and FRBRoo.
Workshop on PIDs within NFDI: Report of the Working Group “Persistent Identifiers (PID)” of the Section Common Infrastructures of the NFDI
In order to gain an overview of the current state of the discussion on PIDs and for the identification of use cases for the initiation phase of a PID service within the NFDI basic services, the working group Persistent Identifier of the Section Common Infrastructures of the NFDI hosted an online workshop in January 2023. In the course of the workshop, members of nine different NFDI consortia presented the current application of PIDs in their consortia.
Electronic Preservation Project for Ukrainian Open Access Journals (EPP UA) to Safeguard Research Content during the War
This conference paper presents an overview of the ongoing initiative EPP UA — Electronic Preservation Project for Ukrainian Open Access Journals, initiated by TIB – Leibniz Information Centre for Science and Technology and University Library. The EPP UA aims to address the pressing need for preservation of open access journals published and hosted by academic institutions in Ukraine. The heightened risk of destruction from the Russian military invasion jeopardizes both the physical infrastructure of academic institutions and the scholarly knowledge stored within their servers. Given that Ukrainian OA journals rarely utilize long-term preservation services, this initiative emphasizes the urgency to ensure accessibility to research content for future generations of scientists and readers.
An Approach to Evaluate User Interfaces in a Scholarly Knowledge Communication Domain
The amount of research articles produced every day is overwhelming: scholarly knowledge is getting harder to communicate and easier to get lost. A possible solution is to represent the information in knowledge graphs: structures representing knowledge in networks of entities, their semantic types, and relationships between them. But this solution has its own drawback: given its very specific task, it requires new methods for designing and evaluating user interfaces. In this paper, we propose an approach for user interface evaluation in the knowledge communication domain. We base our methodology on the well-established Cognitive Walkthough approach but employ a different set of questions, tailoring the method towards domain-specific needs. We demonstrate our approach on a scholarly knowledge graph implementation called Open Research Knowledge Graph (ORKG).
Shaping Digital Transformation for a Sustainable Society: Contributions from Bits & Bäume
The second ‹Bits & Bäume› conference took place in Berlin in 2022. Once again, it provided a space for critical tech and sustainability communities to share ideas and collaborate towards the common goal of shaping digitalisation to foster sustainability. This companion book compiles the insights, work, research and opinions of more than 65 authors with a ‹Bits & Bäume› background, including practitioners, researchers and activists. The articles included in this journal demonstrate the progress made in merging ‹Bits› and ‹Bäume› (Trees) topics since our first publication in 2019 by addressing different sub-areas of the intersections between digitalisation and sustainability. Encompassing a wide range of topics, the articles delve into pressing challenges such as the resource consumption, power implications and democratic governance of digital infrastructures, AI, blockchains, mobile apps, and other software applications, as well as the need to address the unsustainable practices and paradigms of e.g., the platform economy. Offering not only transparency but also solutions, the journal presents practical approaches and concepts related to the necessary transformation, such as the Computer Science for Future programme. It also contains articles commenting on current political developments, such as the EU legislation on sustainability and freedom-related aspects of ICT devices. Further articles highlight the power of and need for an active civil society, aiming to inspire activism. This journal caters for everyone: Are you just getting into the topics around Bits & Bäume? Have you been involved in this field for many years, or are you an expert in one of the areas touched on here? In this journal you will find both introductory topics, such as illustrations on the challenges of today's digitalised society, and also advanced topics, such as conceptual and regulatory discussions. Whatever your background, we think you’ll enjoy the read, learn something new on the way, and get inspired. Ultimately, we are all united by the overarching goal of shaping digitalisation as part of a necessary socio-ecological change; one which contributes to a sustainable and just society.
Clustering Semantic Predicates in the Open Research Knowledge Graph
When semantically describing knowledge graphs (KGs), users have to make a critical choice of a vocabulary (i.e. predicates and resources). The success of KG building is determined by the convergence of shared vocabularies so that meaning can be established. The typical lifecycle for a new KG construction can be defined as follows: nascent phases of graph construction experience terminology divergence, while later phases of graph construction experience terminology convergence and reuse. In this paper, we describe our approach tailoring two AI-based clustering algorithms for recommending predicates (in RDF statements) about resources in the Open Research Knowledge Graph (ORKG) https://orkg.org/. Such a service to recommend existing predicates to semantify new incoming data of scholarly publications is of paramount importance for fostering terminology convergence in the ORKG. Our experiments show very promising results: a high precision with relatively high recall in linear runtime performance. Furthermore, this work offers novel insights into the predicate groups that automatically accrue loosely as generic semantification patterns for semantification of scholarly knowledge spanning 44 research fields.