Small update: Please note that the defense will be held remotely. You can participate in person (see below) or via Zoom: https://rwth.zoom-x.de/j/69475511246?pwd=MTG1YTMzmDZ2p1I9Zc3QiP33gMFs23.1
From: Theissen-Lipp, Johannes Sent: Donnerstag, 12. September 2024 11:59 To: 'assistenten@informatik.rwth-aachen.de' assistenten@informatik.rwth-aachen.de; 'infprof@informatik.rwth-aachen.de' infprof@informatik.rwth-aachen.de; 'vortraege@informatik.rwth-aachen.de' vortraege@informatik.rwth-aachen.de; 'sekretariate@informatik.rwth-aachen.de' sekretariate@informatik.rwth-aachen.de; 'webteam@informatik.rwth-aachen.de' webteam@informatik.rwth-aachen.de; 'biblio@informatik.rwth-aachen.de' biblio@informatik.rwth-aachen.de Subject: Einladung: Informatik-Oberseminar Johannes Theissen-Lipp geb. Lipp
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* Einladung
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* Informatik-Oberseminar
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Zeit: Mittwoch, 25. September 2024, 11.00 Uhr
Ort: COMSYS E3/ Raum 9222, Ahornstraße 55, 52074 Aachen (2359/222, 2.OG)
Referent: Johannes Theissen-Lipp M.Sc.
Computer Science 5 – Information Systems and Databases
Thema: Semantic Foundations of Dataspaces
Abstract:
Digital transformation is rapidly reshaping industries, organizations, and societies around the world, driven by the exponential growth of data from the Internet and the Web. This data, encompassing both open and closed resources, drives innovation and provides competitive advantages. However, there is a growing demand for data sovereignty, where individuals and organizations control their data throughout its lifecycle. Initiatives such as dataspaces, funded with €4-6 billion in Europe, and the Internet of Production focus on data autonomy and integration, but interoperability and common understanding remain critical challenges. The fields of Semantic Web technologies and FAIR data provide frameworks for addressing these challenges. These semantic technologies enable seamless data exchange and meaningful interpretation to maximize the potential of data, yet they are not sufficiently utilized in dataspaces.
This thesis explores the semantic foundations of dataspaces, aiming to integrate semantic technologies to improve data interoperability and facilitate common understanding among stakeholders. It also advances semantic technologies to enhance their impact. This work proposes new concepts, principles, best practices, and solutions to improve data management in dataspaces.
The key contributions of this thesis include:
- A Tailored Data Lifecycle Model for Dataspaces: This model addresses the unique challenges and requirements of dataspaces, ensuring a streamlined and structured approach to managing data and metadata throughout their lifecycle.
- Principles of Information Models: These models define a common core in dataspaces, providing a structured representation of data, services, participants, and interactions, and serving as a foundation for data sovereignty and interoperability mechanisms.
- Extended Data Access Principles: These principles cover various types of heterogeneity, improving data accessibility by managing resource constraints, handling dynamic data changes, and providing rich metadata to increase the quantity and quality of information in dataspaces.
- Methods for Improving Common Domain Understanding: This includes techniques for identification, best practices for vocabulary development, involvement of non-experts, effective recommendation systems, evolution of semantic information over time, and improved validation techniques to enhance data interoperability and (re)use in dataspaces.
By combining these contributions, this thesis confidently integrates semantic technologies into dataspaces. This integration enhances data and service interoperability and facilitates common understanding within these environments, promoting proper data management and reuse throughout the data lifecycle. Our work provides valuable insights into the effective management of information within the digital ecosystem of dataspaces, contributing to the advancement of knowledge in today's data-driven digital transformation.
Es laden ein: die Dozentinnen und Dozenten der Informatik