Portugal

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.

WEBIST 2021

From Ontology Engineering to Ontology Governance Models

2021 Annual Conference of the North American Chapter of the Association for Computational Linguistics.

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NAACL 2021

keynote

The purpose of the International Conference on Web Information Systems and Technologies (WEBIST) is to bring together researchers, engineers and practitioners interested in the technological advances and business applications of web-based information systems. Fve main tracks cover different aspects of Web Information Systems, namely Internet Technology, Web Interfaces and Applications, Society, e-Communities, e-Business, Web Intelligence and Mobile Information Systems. WEBIST focuses on real world applications; therefore authors should highlight the benefits of Web Information Systems and Technologies for industry and services, in addition to academic applications. <br><br>
CONFERENCE AREAS<br>
1 . INTERNET TECHNOLOGY<br>
2 . WEB INTELLIGENCE and SEMANTIC WEB<br>
3 . SOCIAL NETWORK ANALYTICS<br>
4 . HCI in MOBILE SYSTEMS and WEB INTERFACES

The purpose of the International Conference on Web Information Systems and Technologies (WEBIST) is to bring together researchers, engineers and practitioners interested in the technological advances and business applications of web-based information systems.

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.

Knowledge Graphs: Empower AI with Knowledge

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.

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