Vojtěch Svátek – författare

The two-volume set of LNCS 11778 and 11779 constitutes the refereed proceedings of the 18th International Semantic Web Conference, ISWC 2019, held in Auckland, New Zealand, in October 2019. The ISWC conference is the premier international forum for the Semantic Web / Linked Data Community.The total of 74 full papers included in this volume was selected from 283 submissions. The conference is organized in three tracks: for the Research Track 42 full papers were selected from 194 submissions; the Resource Track contains 21 full papers, selected from 64 submissions; and the In-Use Track features 11 full papers which were selected from 25 submissions to this track.

The two-volume set of LNCS 11778 and 11779 constitutes the refereed proceedings of the 18th International Semantic Web Conference, ISWC 2019, held in Auckland, New Zealand, in October 2019. The ISWC conference is the premier international forum for the Semantic Web / Linked Data Community.

The total of 74 full papers included in this volume was selected from 283 submissions. The conference is organized in three tracks: for the Research Track 42 full papers were selected from 194 submissions; the Resource Track contains 21 full papers, selected from 64 submissions; and the In-Use Track features 11 full papers which were selected from 25 submissions to this track.

The two-volume set of LNCS 11778 and 11779 constitutes the refereed proceedings of the 18th International Semantic Web Conference, ISWC 2019, held in Auckland, New Zealand, in October 2019. The ISWC conference is the premier international forum for the Semantic Web / Linked Data Community.The total of 74 full papers included in this volume was selected from 283 submissions. The conference is organized in three tracks: for the Research Track 42 full papers were selected from 194 submissions; the Resource Track contains 21 full papers, selected from 64 submissions; and the In-Use Track features 11 full papers which were selected from 25 submissions to this track.The chapter "The SEPSES knowledge graph: An integrated resource for cybersecurity" is open access under a CC BY 4.0 license at link.springer.com.

The two-volume set of LNCS 11778 and 11779 constitutes the refereed proceedings of the 18th International Semantic Web Conference, ISWC 2019, held in Auckland, New Zealand, in October 2019. The ISWC conference is the premier international forum for the Semantic Web / Linked Data Community.

The total of 74 full papers included in this volume was selected from 283 submissions. The conference is organized in three tracks: for the Research Track 42 full papers were selected from 194 submissions; the Resource Track contains 21 full papers, selected from 64 submissions; and the In-Use Track features 11 full papers which were selected from 25 submissions to this track.

The chapter "The SEPSES knowledge graph: An integrated resource for cybersecurity" is open access under a CC BY 4.0 license at link.springer.com.

th The 15 International Conference on Knowledge Engineering and Knowledge Management (2006), held on October 6-10, 2006 in Pod? ebrady,Czech Republic, followed a long tradition of European Knowledge Acquisition Workshops (from 1987),whicheventuallyacquiredtheformatofconference(in2000)whilekeeping their open-minded and interactive spirit. During the nearly 20 year lifespan of the series, the discipline of knowledge engineering (KE) evolved greatly. While knowledge acquisition (KA) techniques dominated in the very ?rst years, formal approaches to knowledge-based inf- ence and variousnew streamssuch as knowledgediscoveryfrom data/textslater cameinto play. During thelate1990sandafterwards,EKAWbecamea founding community for ontology and Semantic Web Research, which was also re?ected in the sub-titles of the 2002 and 2004 editions: “Ontologies and the Semantic Web” and “Engineering Knowledge in the Age of the Semantic Web,” resp- tively. The 2006 edition, in turn, only slightly refocussed this trend. Its sub-title is “Managing Knowledge in a World of Networks,” which re?ects the fact that semantics typically arises not only as a result of explicit engineering activities (as in Semantic Web) but also emerges from interaction of a high number of interconnected documents, ontological concepts, software applications and — especially — human users. The importance given to the interconnection of - man users in a sense loops back to the knowledge acquisition roots of EKAW and its ‘holistic’ view of knowledge engineering.

th The 15 International Conference on Knowledge Engineering and Knowledge Management (2006), held on October 6-10, 2006 in Pod? ebrady,Czech Republic, followed a long tradition of European Knowledge Acquisition Workshops (from 1987),whicheventuallyacquiredtheformatofconference(in2000)whilekeeping their open-minded and interactive spirit. During the nearly 20 year lifespan of the series, the discipline of knowledge engineering (KE) evolved greatly. While knowledge acquisition (KA) techniques dominated in the very ?rst years, formal approaches to knowledge-based inf- ence and variousnew streamssuch as knowledgediscoveryfrom data/textslater cameinto play. During thelate1990sandafterwards,EKAWbecamea founding community for ontology and Semantic Web Research, which was also re?ected in the sub-titles of the 2002 and 2004 editions: “Ontologies and the Semantic Web” and “Engineering Knowledge in the Age of the Semantic Web,” resp- tively. The 2006 edition, in turn, only slightly refocussed this trend. Its sub-title is “Managing Knowledge in a World of Networks,” which re?ects the fact that semantics typically arises not only as a result of explicit engineering activities (as in Semantic Web) but also emerges from interaction of a high number of interconnected documents, ontological concepts, software applications and — especially — human users. The importance given to the interconnection of - man users in a sense loops back to the knowledge acquisition roots of EKAW and its ‘holistic’ view of knowledge engineering.

Finding knowledge – or meaning – in data is the goal of every knowledge d- covery e?ort. Subsequent goals and questions regarding this knowledge di?er amongknowledgediscovery(KD) projectsandapproaches. Onecentralquestion is whether and to what extent the meaning extracted from the data is expressed in a formal way that allows not only humans but also machines to understand and re-use it, i. e. , whether the semantics are formal semantics. Conversely, the input to KD processes di?ers between KD projects and approaches. One central questioniswhetherthebackgroundknowledge,businessunderstanding,etc. that the analyst employs to improve the results of KD is a set of natural-language statements, a theory in a formal language, or somewhere in between. Also, the data that are being mined can be more or less structured and/or accompanied by formal semantics. These questions must be asked in every KD e?ort. Nowhere may they be more pertinent, however, than in KD from Web data (“Web mining”). Thisis due especially to the vast amounts and heterogeneity of data and ba- ground knowledge available for Web mining (content, link structure, and - age), and to the re-use of background knowledge and KD results over the Web as a global knowledge repository and activity space. In addition, the (Sem- tic) Web can serve as a publishing space for the results of knowledge discovery from other resources, especially if the whole process is underpinned by common ontologies.

Finding knowledge – or meaning – in data is the goal of every knowledge d- covery e?ort. Subsequent goals and questions regarding this knowledge di?er amongknowledgediscovery(KD) projectsandapproaches. Onecentralquestion is whether and to what extent the meaning extracted from the data is expressed in a formal way that allows not only humans but also machines to understand and re-use it, i. e. , whether the semantics are formal semantics. Conversely, the input to KD processes di?ers between KD projects and approaches. One central questioniswhetherthebackgroundknowledge,businessunderstanding,etc. that the analyst employs to improve the results of KD is a set of natural-language statements, a theory in a formal language, or somewhere in between. Also, the data that are being mined can be more or less structured and/or accompanied by formal semantics. These questions must be asked in every KD e?ort. Nowhere may they be more pertinent, however, than in KD from Web data (“Web mining”). Thisis due especially to the vast amounts and heterogeneity of data and ba- ground knowledge available for Web mining (content, link structure, and - age), and to the re-use of background knowledge and KD results over the Web as a global knowledge repository and activity space. In addition, the (Sem- tic) Web can serve as a publishing space for the results of knowledge discovery from other resources, especially if the whole process is underpinned by common ontologies.

Papers were invited based on their quality, relevance and significance, and the - ability of extending their results. Extended versions prepared by authors were subject to the traditional two-round scholarly review process, and the authors were required to respond to all concerns expressed by the reviewers before papers were accepted. Eight papers were eventually accepted for publication in this issue. The selection of SWESE best papers eventually resulted in the acceptance of two papers. The first paper “Experiences in the Design of Semantic Services Using Web En- neering Methods and Tools,” by Brambilla, Ceri, Celino, Cerizza, Della Valle, Facca, Turati, and Tzviskou, shows how classical software engineering methods (such as formal business process development and automatic code generation) combine with semantic methods and tools (i.e., ontology engineering, semantic service annotation and discovery) to forge a new approach to software development for the Semantic Web. In the paper, the authors present their experience in the participation to the - mantic Web Service Challenge 2006, where the proposed approach achieved very good results in solving the proposed problems. The second paper “Automatically Generated Model Transformations Using Ont- ogy Engineering Space,” by Roser and Bauer, presents an approach to using the - mantic technologies to improve cross-organizational modeling by automated gene- tion of model transformations. By automated generation of mappings it offers new possibilities for the integration of domain specific languages and ‘legacy’ models in a plug&play manner, making it easier for new organizations to join collaborations.

Papers were invited based on their quality, relevance and significance, and the - ability of extending their results. Extended versions prepared by authors were subject to the traditional two-round scholarly review process, and the authors were required to respond to all concerns expressed by the reviewers before papers were accepted. Eight papers were eventually accepted for publication in this issue. The selection of SWESE best papers eventually resulted in the acceptance of two papers. The first paper “Experiences in the Design of Semantic Services Using Web En- neering Methods and Tools,” by Brambilla, Ceri, Celino, Cerizza, Della Valle, Facca, Turati, and Tzviskou, shows how classical software engineering methods (such as formal business process development and automatic code generation) combine with semantic methods and tools (i.e., ontology engineering, semantic service annotation and discovery) to forge a new approach to software development for the Semantic Web. In the paper, the authors present their experience in the participation to the - mantic Web Service Challenge 2006, where the proposed approach achieved very good results in solving the proposed problems. The second paper “Automatically Generated Model Transformations Using Ont- ogy Engineering Space,” by Roser and Bauer, presents an approach to using the - mantic technologies to improve cross-organizational modeling by automated gene- tion of model transformations. By automated generation of mappings it offers new possibilities for the integration of domain specific languages and ‘legacy’ models in a plug&play manner, making it easier for new organizations to join collaborations.

There is generalagreementthat the quality of Machine Learning and Kno- edgeDiscoveryoutputstronglydependsnotonlyonthequalityofsourcedata andsophisticationoflearningalgorithms,butalsoonadditional,task/domain speci?c input provided by domain experts for the particular session. There is however less agreement on whether, when and how such input can and should e?ectively be formalized and reused as explicit prior knowledge. In the ?rst ofthe two parts into which the book is divided, we aimed to - vestigate current developments and new insights on learning techniques that exploit prior knowledge and on promising application areas. With respect to application areas, experiments on bio-informatics / medical and Web data environments are described. This part comprises a selection of extended c- tributionstothe workshopPrior Conceptual Knowledge inMachine Learning and Knowledge Discovery (PriCKL), held at ECML/PKDD 2007 18th - ropean Conference on Machine Learning and 11th European Conference on PrinciplesandPracticeofKnowledgeDiscoveryinDatabases).Theworkshop is part of the activities of the "SEVENPRO - Semantic Virtual Engineering for Product Design" project of the European 6th Framework Programme.The second part of the book has been motivated by the speci?cation of Web 2.0. We observe Web 2.0 as a powerful means of promoting the Web as a social medium, stimulating interpersonal communication and fostering the sharing of content, information, semantics and knowledge among people. Chapters are authored by participants to the workshop Web Mining 2.0, heldatECML/PKDD2007.Theworkshophostedresearchontheroleofweb mininginandfortheWeb2.0.Itispartoftheactivitiesoftheworkinggroups "UbiquitousData-InteractionandDataCollection"and"HumanComputer Interaction and Cognitive Modelling" of the Coordination Action "KDubiq - Knowledge Discovery in Ubiquitous Environments" of the European 6th Framework Programme.