Podcast: Most of the kind of AI that gets the spotlight these days revolves around machine learning. But there actually are many approaches, or tribes, in AI. What is the role of knowledge representation and reasoning, or symbolic AI, today? 

How can more traditional, knowledge-based approaches connect with, and contribute to, machine learning for better AI? And what's graph got to do with it? This panel will discuss how to bridge the gap among the AI tribes.

Sebastian Riedel  -Researcher, Facebook AI Research
Christos Hadjinikolis - Senior ML Engineer, Data Reply UK
Andy Jefferson - Neural Networks and Graph AI Researcher, Octavian
Jon McLoone - Director of Technical Services, Communication and Strategy, Wolfram

Podcast: AI Tribes and Interconnections: What's Graph Got to Do With It?

As the interest in, and hype around, Knowledge Graphs is growing, there is also a growing need for sharing experience and best practices around them. Let's talk about definitions, best practices, hype, and reality. 

What is a Knowledge Graph? How can I use a Knowledge Graph & how do i start building one? This panel is an opportunity to hear from industry experts using these technologies & approaches to discuss best practices, common pitfalls and where this space is headed next.

Moderator: Paul Groth. Featuring:

Panos Alexopoulos
Head of Ontology, Textkernel BV

Panos Alexopoulos has been working at the intersection of data, semantics, language and software for years, and is leading a team at Textkernel developing a large cross-lingual Knowledge Graph for HR and Recruitment. Alexopoulos holds a PhD in Knowledge Engineering and Management from the National Technical University of Athens, and has published 60 papers at international conferences, journals and books.

Sebastian Hellmann
dbpedia.org

Sebastian is a senior member of the “Agile Knowledge Engineering and Semantic Web” AKSW research center, focusing on semantic technology research – often in combination with other areas such as machine learning, databases, and natural language processing. 

Sebastian is head of the “Knowledge Integration and Language Technologies (KILT)” Competence Center at InfAI. He also is the executive director and board member of the non-profit DBpedia Association. 

Sebastian is also a contributor to various open-source projects and communities such as DBpedia, NLP2RDF, DL-Learner and OWLG, and has been involved in numerous EU research projects.

Katariina Kari
Research Engineer, Zalando Tech-Hub

Katariina Kari (née Nyberg) is a research engineer at the Zalando Tech-Hub in Helsinki. Katariina holds a Master in Science and Master in Music and is specialised in semantic web and guiding the art business to the digital age. At Zalando she is modelling the Fashion Knowledge Graph, a common vocabulary for fashion with which Zalando improves is customer experience. Katariina also consults art institutions to embrace the digital age in their business and see its opportunities.

Natasa Varytimou
Information Architect, Refinitiv

Natasa has been working as a Linked Data architect in various industry sectors for many years. She believes data will become the strongest asset in any organization and that Semantic Web technologies are the perfect fit to integrate it from different data sources, describe its meaning with flexible and lightweight models, and create new information based on rules. She queries data with their models directly with SPARQL, transforms them to different models driven from business needs and utilizes SHACL to validate and create high-quality data based on business rules.

2019

Podcast: Building Knowledge Graphs in the Real World

The computational fabric that underpins our world is connected to every aspect of modern life; from health to education, transport to energy, finance to defence. There is a dawning recognition that the data this fabric consumes, generates and transfers is a vital asset. 

Data once considered dry, dull and boring is at the heart of our digital society. This talk demonstrates that data is a vital infrastructure; a vital infrastructure for individuals, organisations and nation states. It is an infrastructure that needs to be engineered, curated and cared for. 

It is an infrastructure that demands particular skills within our society. It is an infrastructure that becomes much more effective if rooted in the standards and technology of linked data.

Podcast: Linked Data as Critical Infrastructure. Sir Nigel Shadbolt, Connected Data London 2018

Due to the fact that almost all business-critical data inherently is more like a graph than a table, many companies have begun to transform their data into property graphs. To furthermore foster linkage as well as meaningful querying or processing they often consider to enrich their graph data by means of a semantic model and RDF/OWL reasoning. 

In this talk, I will report on industry projects that have successfully deployed applications that implement processes and tools to transform relational data into graph data, semantically enrich graph data as well as use reasoning to better exploit and utilize relevant knowledge within this data. 

Next to use cases from different domains I will also describe tools for modeling, reasoning and visually exploring graph data that were used to make this projects happen. 

About the speaker: As part of his responsibilities at derivo, Thorsten helps companies and organizations to use the knowledge in their data by means of semantic technologies. This covers property resp. knowledge graph modelling and establishing industry-ready software solutions including reasoning about – as well as exploring and utilizing – large knowledge graphs. When not dealing with knowledge graphs, he enjoys Italian coffee and cycling.

Podcast: Powering Graph Data with Reasoning, Visual Analytics. Thorsten Liebig,

Podcasts from Connected Data London: the leading conference for those who use the relationships, meaning and context in Data to achieve great things.