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Keynote Lectures

Knowledge Graphs: Theory, Applications and Challenges
Ian Horrocks, University of Oxford, United Kingdom

Knowledge Graphs: Empower AI with Knowledge
Dieter A. Fensel, University of Innsbruck, Austria

From Ontology Engineering to Ontology Governance Models
Oscar Corcho, Universidad Politécnica de Madrid, Spain


Knowledge Graphs: Theory, Applications and Challenges

Ian Horrocks
University of Oxford
United Kingdom

Brief Bio
Ian Horrocks is a full professor in the Oxford University Department of Computer Science, a visiting professor in the Department of Informatics at the University of Oslo and a co-founder of Oxford Semantic Technologies. He is also a Fellow of the Royal Society, a member of Academia Europaea, and a fellow of the European Association for Artificial Intelligence (EurAI). His research concerns the representation of knowledge, and the efficient manipulation of such knowledge by computers. He played a leading role in establishing the Semantic Web as a significant research field, pioneering many of the underlying logics, algorithms, optimization techniques, and reasoning systems. He was the leading researcher behind the description logic SROIQ, and he has driven its standardisation into the ontology language OWL. He has contributed to the development of several widely used reasoning systems including FaCT++, HermiT, Elk and RDFox. He has published more than 200 papers in major international conferences and journals, winning best paper prizes at KR-98, AAAI-2010, and IJCAI-2017, and a test of time awards at ISWC-2013 and KR-2020. He is one of the UK’s most highly cited computer scientists, with more than 66,000 citations, and an h-index of 98.

Knowledge Graphs have rapidly become a mainstream technology that combines features of databases and AI. In this talk I will introduce Knowledge Graphs, explaining their features and the theory behind them, and illustrating their use in a range of applications. I will then consider the challenges inherent in both the theory and implementation of Knowledge Graphs and present some solutions that have made possible the development of robust and high performance Knowledge Graph systems.



Knowledge Graphs: Empower AI with Knowledge

Dieter Fensel
University of Innsbruck

Brief Bio
Dieter Fensel is the chair of the STI Innsbruck research group at the University of Innsbruck’s Department of Computer Science. He has written over 300 scientific publications, including books, journals and conference papers, and workshop contributions. As one of the pioneers of research in the Semantic Web, he co-founded major scientific events such as the European Semantic Web Conference (ESWC) and the International Semantic Web Conference (ISWC). His research interests currently focus on the development of knowledge graphs and various aspects of the knowledge graph lifecycle. He has successfully applied his research in industry by co-founding companies like seekda (now part of Kognitiv) and Onlim, which are active in conversational interfaces and knowledge graphs.

Knowledge Graphs provide large amounts of semantically described and interlinked knowledge bases integrating various and heterogeneous data and information sources. Building and maintaining them is not an easy task, however, many important complementary trends require their development and usage.

●        Turning the web into a semantically-enabled query answering infrastructure by applying schema.org. Data, content, and services become semantically annotated allowing software agents, so-called bots, to search through the web understanding its content. The times where humans were browsing through a large number of websites and manually extracting and interpreting their information are passing by. Instead, players like Google want to provide answers on their website rather than link farms that make the user leave immediately. The aim is to provide an engine that helps to find, aggregate, and personalize information, to reserve, book, or buy products and services for him. In consequence, it becomes increasingly important for providers of information, products, and services to be highly hearable and visible in these and future new online channels to ensure their future economic maturity.

●        Providing dialogue-based interfaces to large and heterogeneous information by intelligent softbots. Smart speakers such as Alexa and later Google Home introduced Artificial Intelligence (AI) in millions soon billions of households making AI an everyday experience. We can now look for information, order products and services, without leaving the house or touching a computer. We just talk to a box and this thing will friendly perform the desired tasks for us. These new communication channels define new challenges for successful eMarketing and eCommerce. Just running a traditional website with many colorful pictures is no longer state of the art for successful eCommerce.

●        Producing AI-based autonomous systems acting in the physical world. Morphing intelligent agents from the virtual world into the physical one is still a great challenge. Meanwhile, they win every virtual game such as checkers, chess, go, or quiz but in physical games, they act still quite cumbersome. An area with increasing success is autonomous traffic. Here, autonomous cars provide a major challenge and potential break-through of this technology. Still, without proper world knowledge based on up-to-date knowledge graphs also come along with severe risk which may significantly hamper the uptake of this technology.


In our talk, we discuss methods and tools helping to achieve these goals. The core is the development and application of machine-processable (semantic) annotations of online resources as well as their aggregation in large Knowledge Graphs. Only this enables bots to not only understand a question but being able to answer a question knowledgeably and to organize a useful dialogue. We discuss the process of knowledge generation, hosting, curation, and deployment focusing on the usage of the knowledge graph to support dialog-based interfaces.




From Ontology Engineering to Ontology Governance Models

Oscar Corcho
Universidad Politécnica de Madrid

Brief Bio

Oscar Corcho is Full Professor at Universidad Politécnica de Madrid (UPM), and he belongs to the Ontology Engineering Group (OEG).

As part of his involvement in the Open Data Institute node in Madrid, Oscar leads the Spanish thematic network on Open Data for Smart Cities, where joint guidelines and vocabularies are being proposed for the harmonisation of datasets across open data portals in Spain. He has been also involved in the creation of the Spanish technical norm UNE178301:2015 on Open Data for Smart Cities, which proposes a maturity model to assess and improve the quality of open data implementations for cities, and on the ongoing OjoalData100 initiative for the identification of the 100 most relevant open datasets for cities. And he has advised on the implementation of the open data API for Zaragoza.

Furthermore, in 2013 Oscar co-founded Localidata, a company specialised on providing support on the implementation of open data strategies by cities.

Our research group has been working in the area of Ontology Engineering for more than two decades. Most of our initial work focused on the proposal of ontology engineering methodologies, methods, techniques and tools, which were normally applied for the development of single ontologies and for ontology networks for specific organisations or domains. This work has continued evolving with adapted methodologies and methods, with new tools and services that cover more parts of the ontology development lifecycle, and especially with the need to setup a more holistic view into how sustainable ontology development efforts need to be tackled and organised in those cases where multiple stakeholders are involved.

In this talk, I will describe our experiences in setting up ontology governance models in this context, with a special focus on our work in the Ciudades Abiertas (Open Cities) project, where we are developing a network of ontologies to homogenise the open data that cities are publishing so that they can create good quality knowledge graphs about their cities. I will reflect on the main challenges that we have faced, lessons learned (including good and bad practices) and our next steps for the proposal of ontology governance models for these types of contexts.