Auflistung nach Forschungsgruppen "Digitalisierung und Öffnung der Wissenschaft"

Gerade angezeigt 1 - 11 von 11
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    A Decentralized Provenance Network for Linked Open Data
    (2019) Kirstein, Fabian; Qiao, Miao; Dragoni, Mauro
    With the growing availability of Linked Open Data (LOD) and the consequential generation of derived and aggregated data, the need for trustworthy, reproducible and accessible provenance informa- tion has increased. Yet, no consistent mechanism has been established to manage provenance data of LOD on a global dataset-level. Decentralized networks and peer-to-peer mechanisms have made their revival in the last years with blockchain and similar distributed ledger technologies. We propose a novel approach to track and store provenance information for LOD on a dataset-level by sharing an immutable, common state between data providers. The basic architecture will not disrupt existing methodologies and standards for publishing LOD, but will be transparently integrated into existing ecosystems as an additional layer to foster broad acceptance. We will investigate the application of emerging blockchain technologies and established Linked Data specifications for building this decentralized anchor of truth. We are actively involved in the design and implementation of LOD and Open Data platforms and will evaluate our approach in real-world scenarios regarding feasibility, governance, scalability and usability.
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    A Translation Service for Open Data Portals
    (2022) Urbanek, Sebastian; Schimmler, Sonja
    There exists a huge variety of Open Data portals, some of them providing just a handful, and others tens of thousands of datasets. The datasets they provide are expected to be supplied with metadata describing them. However, this metadata is typically available in one or two languages only, and, if translations exist, they are usually added manually. To build an inclusive data infrastructure, metadata should be available in as many languages as possible. The paper presents an approach for automatic translation of metadata within Open Data portals, based on Semantic Web technologies and using the metadata standard DCAT-AP. Based on this approach, new functionalities are possible, such as enabling users to search for datasets in their native language. The approach was implemented for and tested within a practical application in a production environment.
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    Editorial: Volume 2, Issue 1
    (Weizenbaum Institute, 2022) Emmer, Martin; Krasnova, Hanna; Krzywdzinski, Martin; Metzger, Axel; Schimmler, Sonja; Ulbricht, Lena
    This second issue of the Weizenbaum Journal of the Digital Society brings together four contributions that examine the role of actors and regulation in processes of digitalization from the perspective of different disciplines. The topics include the role of the Silicon Valley discourse on entrepreneurship in legitimizing a specific model of work in the IT industry, the particularities of the European platform regulation approach, the development and enforcement problems of copyright liability regulation in Germany, and the development and regulation of automation processes in the workplace.
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    Exploring Prompt Generation Utilizing Graph Search Algorithms for Ontology Matching
    (IOS Press, 2024) Sampels, Julian; Efeoglu, Sefika; Schimmler, Sonja; Salatino, Angelo; Alam, Mehwish; Ongenae, Femke; Vahdati, Sahar; Gentile, Anna-Lisa; Pellegrini, Tassilo; Jiang, Shufan
    The interoperability of domain ontologies, developed by domain experts, necessitates their alignment before attempting to match them. Within these ontologies, defined concepts often encounter an ambiguity problem stemming from the use of natural language. This interoperability issue raises the underlying ontology matching (OM) challenge. OM might be defined as the identification of correspondences or relationships between two or more entities, such as classes or properties among two or more ontologies. Rule-based ontology matching approaches, e.g., LogMap and AML have not outperformed machine learning based matchers on the Ontology Alignment Evaluation Initiative (OAEI) benchmark datasets, especially on the OAEI Conference track since 2020. Supervised machine or deep learning approaches produce the best results but require labeled training datasets. In the era of Large Language Models (LLMs), robust zero-shot prompting of LLMs can also return convincing responses. While prompt generation requires prompt template engineering by domain experts, contextual information about the concepts to be aligned can be retrieved by leveraging graph search algorithms. In this work, we explore how graph search algorithms, namely (i) Random Walk and (ii) Tree Traversal can be utilized to retrieve the contextual information to be incorporated into prompt templates. Through these algorithms, our approach refrains from considering all triples connected with a concept to be aligned in its contextual information creation. Our experiments show that including the retrieved contextual information in prompt templates improves the matcher’s performance. Additionally, our approach outperforms previous works leveraging zero-shot prompting.
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    FAIREST: A Framework for Assessing Research Repositories
    (2022) d’Aquin, Mathieu; Kirstein, Fabian; Oliveira, Daniela; Schimmler, Sonja; Urbanek, Sebastian
    The open science movement has gained significant momentum within the last few years. This comes along with the need to store and share research artefacts, such as publications and research data. For this purpose, research repositories need to be established. A variety of solutions exist for implementing such repositories, covering diverse features, ranging from custom depositing workflows to social media-like functions. In this article, we introduce the FAIREST principles, a framework inspired by the well-known FAIR principles, but designed to provide a set of metrics for assessing and selecting solutions for creating digital repositories for research artefacts. The goal is to support decision makers in choosing such a solution when planning for a repository, especially at an institutional level. The metrics included are therefore based on two pillars: (1) an analysis of established features and functionalities, drawn from existing dedicated, general purpose and commonly used solutions, and (2) a literature review on general requirements for digital repositories for research artefacts and related systems. We further describe an assessment of 11 widespread solutions, with the goal to provide an overview of the current landscape of research data repository solutions, identifying gaps and research challenges to be addressed.
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    How Research Data Management Plans Can Help in Harmonizing Open Science and Approaches in the Digital Economy
    (2022) Salazar, Abel; Wentzel, Bianca; Schimmler, Sonja; Gläser, Roger; Hanf, Schirin; Schunk, Stephan A.
    Within this perspective article, we intend to summarise definitions and terms that are often used in the context of open science and data-driven R&D and we discuss upcoming European regulations concerning data, data sharing and handling. With this background in hand, we take a closer look at the potential connections and permeable interfaces of open science and digital economy, in which data and resulting immaterial goods can become vital pieces as tradeable items. We believe that both science and the digital economy can profit from a seamless transition and foresee that the scientific outcomes of publicly funded research can be better exploited. To close the gap between open science and the digital economy, and to serve for a balancing of the interests of data producers, data consumers, and an economy around services and the public, we introduce the concept of generic research data management plans (RDMs), which have in part been developed through a community effort and which have been evaluated by academic and industry members of the NFDI4Cat consortium. We are of the opinion that in data-driven research, RDMs do need to become a vital element in publicly funded projects
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    Navigating Through Changes of a Digital World
    (Springer International Publishing, 2022) Hauk, Nathalie; Hauswirth, Manfred; Werthner, Hannes; Prem, Erich; Lee, Edward A.; Ghezzi, Carlo
    In this chapter, we address the question of how trust in technological development can be increased. The use of information technologies can potentially enable humanity, social justice, and the democratic process. At the same time, there are concerns that the deployment of certain technologies, e.g., AI technologies, can have unintended consequences or can even be used for malicious purposes. In this chapter, we discuss these conflicting positions.
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    Open 5G campus networks: key drivers for 6G innovations
    (2022) Emmelmann, Marc; Corici, Marius; Eichhorn, Fabian; Hauswirth, Manfred; Magedanz, Thomas
    5G was designed to enable and unify Industrial Internet communication. Emerging 5G campus networks, in particular, provide a flexible communication infrastructure option addressing the specific needs of industry verticals regarding low latency, resilience, security, and operation models. Network Function Virtualization (NFV) and Edge Computing have paved the way for vendor-independent, customized, and scalable network designs for the past decade. Today, Open Radio Access Network (Open RAN) principles extend this architectural thinking toward an innovative and open 5G end-to-end infrastructure. 5G campus networks, in particular, might benefit from this envisaged openness. One key driver for boosting the global interest in private campus networks was the allocation of a dedicated 5G spectrum in Germany in 2019. In addition to permanent spectrum allocations for static campus network deployments, nomadic ad hoc campus network deployments using novel mechanisms, such as dynamic spectrum access and trading, also emerge. Both network types are enabled by the inherent flexibility of combining or disaggregating the desired open 5G RAN and core components in appropriate network deployments. Building upon years of experience in developing and operating 5G network cores and 5G testbeds, the authors provide an overview of the emerging global campus network market, available spectrum options, use cases for nomadic campus network deployments, and the need for open campus networks and open end-to-end technology testbeds. Utilizing the Fraunhofer FOKUS Open5GCore, the 5G Playground testbed, and the 5G+ Nomadic Node as examples, the paper sketches a blueprint for campus networks for international, applied research and development. Ending with an outlook on the evolution of campus networks, namely the transition toward higher spectrums and the integration of non-terrestrial networks, but also the adoption of more agile software principles and the deeper integration of AI/ML technologies for network control and management, it will become obvious that open campus network innovations will pave the way toward 6G.
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    Ronda. Real-Time Data Provision, Processing and Publication for Open Data
    (Springer International Publishing, 2021) Kirstein, Fabian; Bacher, Dario; Bohlen, Vincent; Schimmler, Sonja; Scholl, Hans Jochen; Gil-Garcia, J. Ramon; Janssen, Marijn; Kalampokis, Evangelos; Lindgren, Ida; Rodríguez Bolívar, Manuel Pedro
    The provision and dissemination of Open Data is a flourishing concept, which is highly recognized and established in the government and public administrations domains. Typically, the actual data is served as static file downloads, such as CSV or PDF, and the established software solutions for Open Data are mostly designed to manage this kind of data. However, the rising popularity of the Internet of things and smart devices in the public and private domain leads to an increase of available real-time data, like public transportation schedules, weather forecasts, or power grid data. Such timely and extensive data cannot be used to its full potential when published in a static, file-based fashion. Therefore, we designed and developed Ronda - an open source platform for gathering, processing and publishing real-time Open Data based on industry-proven and established big data and data processing tools. Our solution easily enables Open Data publishers to provide real-time interfaces for heterogeneous data sources, fostering more sophisticated and advanced Open Data use cases. We have evaluated our work through a practical application in a production environment.
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    Stellungnahme zum BMBF-Eckpunktepapier für ein Forschungsdatengesetz
    (Weizenbaum Institute, 2024-05-23) Kammerer, Dietmar; Schimmler, Sonja; Shala, Kaltrina; Vuorimäki, Julian
    Das Weizenbaum-Institut begrüßt das vom Bundesministerium für Bildung und Forschung (BMBF) vorgelegte Eckpunktepapier zum Forschungsdatengesetz. Damit es zum Wohle der Allgemeinheit wirksam werden kann, sollte es den Bedarfen der öffentlich geförderten Forschung angemessen sein. Das Weizenbaum-Institut möchte mit der vorliegenden Stellungnahme hierzu einen Beitrag leisten. Im Folgenden wird deshalb zu den Datenbedarfen der Forschung, der Auffindbarkeit von Forschungsdaten, dem Zugang zu und die Verknüpfung von Forschungsdaten, den Ressourcen und der Anerkennung für die Forschung sowie Verbesserungen im Datenschutzrecht Stellung genommen.
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    Using Metaphorical Design to Reveal New Perspectives in Systems Design – Insights From a Participatory Design Workshop for Research Data Platforms
    (Association for Computing Machinery, 2022) Weiß, Veronika; Schimmler, Sonja; Preim, Bernhard; Müller-Birn, Claudia
    Metaphorical design is a Participatory Design technique suitable for problem setting and concept development. The technique can be particularly constructive when designing (computer) systems in an already digitalized environment. In such contexts, designers might be tempted to draw on readily available technical solutions, thus hampering the discovery of new perspectives. Our use case is the development of a research data platform that aims to provide innovative functionality, especially for assessing and exploring digital resources. We developed a participatory workshop format adapting metaphorical design that first creates a shared understanding of the context and then guides participants to generate metaphors using a projective technique. We show how we used these metaphors to understand the participants’ model of the research data platform, to identify possible domains of activities, and to stimulate new viewpoints on the research data platform and its functionality. With this paper, we provide an application example of the adapted metaphorical design process, propose a metaphor evaluation matrix, and discuss the findings.