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- ItemDifferentialgeometrie im Grossen (hybrid meeting)(Zürich : EMS Publ. House, 2021) Hamenstädt, Ursula; Lang, Urs; Weinkove, BenThe field of classical differential geometry has expanded enormously over the last several decades, helped by the development of tools from neighboring fields such as partial differential equations, complex analysis and geometric topology. In the spirit of the previous meetings in the series, this meeting will bring together researchers from apparently separate subfields of differential geometry, but whose work is linked by common themes. In particular, this meeting will emphasize intrinsic geometric questions motivated by the classification and rigidity of global geometric structures and the interaction of curvature with the underlying geometry and topology.
- ItemDDB-KG: The German Bibliographic Heritage in a Knowledge Graph(Aachen, Germany : RWTH Aachen, 2021) Tan, Mary Ann; Tietz, Tabea; Bruns, Oleksandra; Oppenlaender, Jonas; Dessì, Danilo; Harald, Sack; Sumikawa, Yasunobu; Ikejiri, Ryohei; Doucet, Antoine; Pfanzelter, Eva; Hasanuzzaman, Mohammed; Dias, Gaël; Milligan, Ian; Jatowt, AdamUnder the German government’s initiative “NEUSTART Kultur”, the German Digital Library or Deutsche Digitale Bibliothek (DDB) is undergoing improvements to enhance user-experience. As an initial step, emphasis is placed on creating a knowledge graph from the bibliographic record collection of the DDB. This paper discusses the challenges facing the DDB in terms of retrieval and the solutions in addressing them. In particular, limitations of the current data model or ontology to represent bibliographic metadata is analyzed through concrete examples. This study presents the complete ontological mapping from DDB-Europeana Data Model (DDB-EDM) to FaBiO, and a prototype of the DDB-KG made available as a SPARQL endpoint. The suitabiliy of the target ontology is demonstrated with SPARQL queries formulated from competency questions.
- ItemUnveiling Relations in the Industry 4.0 Standards Landscape Based on Knowledge Graph Embeddings(Cham : Springer, 2020) Rivas, Ariam; Grangel-González, Irlán; Collarana, Diego; Lehmann, Jens; Vidal, Maria-Esther; Hartmann, Sven; Küng, Josef; Kotsis, Gabriele; Tjoa, A Min; Khalil, IsmailIndustry 4.0 (I4.0) standards and standardization frameworks have been proposed with the goal of empowering interoperability in smart factories. These standards enable the description and interaction of the main components, systems, and processes inside of a smart factory. Due to the growing number of frameworks and standards, there is an increasing need for approaches that automatically analyze the landscape of I4.0 standards. Standardization frameworks classify standards according to their functions into layers and dimensions. However, similar standards can be classified differently across the frameworks, producing, thus, interoperability conflicts among them. Semantic-based approaches that rely on ontologies and knowledge graphs, have been proposed to represent standards, known relations among them, as well as their classification according to existing frameworks. Albeit informative, the structured modeling of the I4.0 landscape only provides the foundations for detecting interoperability issues. Thus, graph-based analytical methods able to exploit knowledge encoded by these approaches, are required to uncover alignments among standards. We study the relatedness among standards and frameworks based on community analysis to discover knowledge that helps to cope with interoperability conflicts between standards. We use knowledge graph embeddings to automatically create these communities exploiting the meaning of the existing relationships. In particular, we focus on the identification of similar standards, i.e., communities of standards, and analyze their properties to detect unknown relations. We empirically evaluate our approach on a knowledge graph of I4.0 standards using the Trans∗ family of embedding models for knowledge graph entities. Our results are promising and suggest that relations among standards can be detected accurately.
- ItemIPAL: Breaking up Silos of Protocol-dependent and Domain-specific Industrial Intrusion Detection Systems(New York City : Association for Computing Machinery, 2022-10-26) Wolsing, Konrad; Wagner, Eric; Saillard, Antoine; Henze, MartinThe increasing interconnection of industrial networks exposes them to an ever-growing risk of cyber attacks. To reveal such attacks early and prevent any damage, industrial intrusion detection searches for anomalies in otherwise predictable communication or process behavior. However, current efforts mostly focus on specific domains and protocols, leading to a research landscape broken up into isolated silos. Thus, existing approaches cannot be applied to other industries that would equally benefit from powerful detection. To better understand this issue, we survey 53 detection systems and find no fundamental reason for their narrow focus. Although they are often coupled to specific industrial protocols in practice, many approaches could generalize to new industrial scenarios in theory. To unlock this potential, we propose IPAL, our industrial protocol abstraction layer, to decouple intrusion detection from domain-specific industrial protocols. After proving IPAL's correctness in a reproducibility study of related work, we showcase its unique benefits by studying the generalizability of existing approaches to new datasets and conclude that they are indeed not restricted to specific domains or protocols and can perform outside their restricted silos.
- ItemConvex Geometry and its Applications (hybrid meeting)(Zürich : EMS Publ. House, 2021) Barthe, Franck; Ludwig, MonikaThe geometry of convex domains in Euclidean space plays a central role in several branches of mathematics: functional and harmonic analysis, the theory of PDE, linear programming and, increasingly, in the study of algorithms in computer science. The purpose of this meeting was to bring together researchers from the analytic, geometric and probabilistic groups who have contributed to these developments.
- ItemUnderstanding Class Representations: An Intrinsic Evaluation of Zero-Shot Text Classification(Aachen, Germany : RWTH Aachen, 2021) Hoppe, Fabian; Dessì, Danilo; Sack, Harald; Alam, Mehwish; Buscaldi, Davide; Cochez, Michael; Osborne, Francesco; Reforgiato Recupero, Diego; Sack, HaraldFrequently, Text Classification is limited by insufficient training data. This problem is addressed by Zero-Shot Classification through the inclusion of external class definitions and then exploiting the relations between classes seen during training and unseen classes (Zero-shot). However, it requires a class embedding space capable of accurately representing the semantic relatedness between classes. This work defines an intrinsic evaluation based on greater-than constraints to provide a better understanding of this relatedness. The results imply that textual embeddings are able to capture more semantics than Knowledge Graph embeddings, but combining both modalities yields the best performance.
- ItemDynamics of Waves and Patterns (hybrid meeting)(Zürich : EMS Publ. House, 2021) Chirilus-Bruckner, Martina; Kühn, Christian; Rademacher, JensThe dynamics of waves and patterns play a significant role in the sciences, especially in fluid mechanics, material science, neuroscience and ecology. The mathematical treatment interconnects several areas, ranging from evolution equations and functional analysis to dynamical systems, geometry, topology, and stochastic as well as numerical analysis. This workshop has specifically focussed on dynamic stability on extended domains, bifurcations of waves and patterns, effects of stochastic driving, and spatio-temporal inhomogenities. During the workshop, multiple new directions, collaborations, and very interesting scientific conversations arose across the entire field.
- ItemA Data-Driven Approach for Analyzing Healthcare Services Extracted from Clinical Records(Piscataway, NJ : IEEE, 2020) Scurti, Manuel; Menasalvas-Ruiz, Ernestina; Vidal, Maria-Esther; Torrente, Maria; Vogiatzis, Dimitrios; Paliouras, George; Provencio, Mariano; Rodríguez-González, Alejandro; Seco de Herrera, Alba García; Rodríguez González, Alejandro; Santosh, K.C.; Temesgen, Zelalem; Soda, PaoloCancer remains one of the major public health challenges worldwide. After cardiovascular diseases, cancer is one of the first causes of death and morbidity in Europe, with more than 4 million new cases and 1.9 million deaths per year. The suboptimal management of cancer patients during treatment and subsequent follows up are major obstacles in achieving better outcomes of the patients and especially regarding cost and quality of life In this paper, we present an initial data-driven approach to analyze the resources and services that are used more frequently by lung-cancer patients with the aim of identifying where the care process can be improved by paying a special attention on services before diagnosis to being able to identify possible lung-cancer patients before they are diagnosed and by reducing the length of stay in the hospital. Our approach has been built by analyzing the clinical notes of those oncological patients to extract this information and their relationships with other variables of the patient. Although the approach shown in this manuscript is very preliminary, it shows that quite interesting outcomes can be derived from further analysis. © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
- ItemGeometric Structures in Group Theory (hybrid meeting)(Zürich : EMS Publ. House, 2020) Drutu, Cornelia; Kramer, Linus; Rémy, BertrandThe conference focused on the use of geometric methods to study infinite groups and the interplay of group theory with other areas. One of the central techniques in geometric group theory is to study infinite discrete groups by their actions on nice, suitable spaces. These spaces often carry an interesting large-scale geometry, such as non-positive curvature or hyperbolicity in the sense of Gromov, or are equipped with rich geometric or combinatorial structure. From these actions one can investigate structural properties of the groups. This connection has become very prominent during the last years. In this context non-discrete topological groups, such as profinite groups or locally compact groups appear quite naturally. Likewise, analytic methods and operator theory play an increasing role in the area.
- ItemOntology Design for Pharmaceutical Research Outcomes(Cham : Springer, 2020) Say, Zeynep; Fathalla, Said; Vahdati, Sahar; Lehmann, Jens; Auer, Sören; Hall, Mark; Merčun, Tanja; Risse, Thomas; Duchateau, FabienThe network of scholarly publishing involves generating and exchanging ideas, certifying research, publishing in order to disseminate findings, and preserving outputs. Despite enormous efforts in providing support for each of those steps in scholarly communication, identifying knowledge fragments is still a big challenge. This is due to the heterogeneous nature of the scholarly data and the current paradigm of distribution by publishing (mostly document-based) over journal articles, numerous repositories, and libraries. Therefore, transforming this paradigm to knowledge-based representation is expected to reform the knowledge sharing in the scholarly world. Although many movements have been initiated in recent years, non-technical scientific communities suffer from transforming document-based publishing to knowledge-based publishing. In this paper, we present a model (PharmSci) for scholarly publishing in the pharmaceutical research domain with the goal of facilitating knowledge discovery through effective ontology-based data integration. PharmSci provides machine-interpretable information to the knowledge discovery process. The principles and guidelines of the ontological engineering have been followed. Reasoning-based techniques are also presented in the design of the ontology to improve the quality of targeted tasks for data integration. The developed ontology is evaluated with a validation process and also a quality verification method.