Semantics 2016 - Keynote

Harald Sack

semantics_admin — Wed, 10 Aug 2016 15:06:55 +0000

Senior Researcher

Hasso-Plattner-Institut für Softwaresystemtechnik GmbH

The dwerft Project - DBpedia and Linked Data for the Media Value Chain

Metadata plays an essential role in film and TV production as well as in the entire media value chain ranging from the idea of a script, followed by production planning, production and post-production, up to distribution and archival . Unfortunately, lots of information gets lost in the fragmented processes, especially when multiple companies are involved. Often, metadata needs to be reconstructed manually at the end, which is an expensive and sometimes error prone task. Dwerft, a national funded research initiative, aims to cope with this problem based on the deployment of Linked Data principles, resulting in Linked Production Data for the complete film and TV value chain. DBpedia serves as the reference data set in this huge data integration approach, and as such problems of synchronization, versioning, or access management have to be addressed on an industrial level to enable high efficiency. One of the many applications addressed in the course of the dwerft project are intelligent recommender services for movie recommendations as well as for advertisements and product recommendations based on Linked Production Data.

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Harald Sack is Senior Researcher at the Hasso Plattner-Institute for IT-Systems Engineering (HPI) at the University of Potsdam and head of the research group 'Semantic Technologies and Multimedia Retrieval'. After graduating in computer science at the University of the Federal Forces Munich Campus, he worked as network engineer and project manager in the signal intelligence corps of the German federal forces. In 1997 he became an associated member of the graduate program ‘mathematical optimization’ at the University of Trier and obtained a PhD in theoretical computer science in 2002. From 2002–2008 he worked as postdoc at the Friedrich-Schiller-University in Jena. From 2009 to 2016 he was working as Senior Researcher at HPI. In October 2016 he takes over the lead of the Information Service Engineering group at FIZ Karlsruhe - Leibniz Institute for Information Infrastructure and corresponding professorship at Karlsruhe Institute of Technology. His current areas of research include semantic technologies, knowledge discovery as well as multimedia analysis & retrieval. He has served as Chair, Senior PC member or PC member of numerous international conferences and workshops. Harald Sack has published more than 130 scientific papers in international journals and conferences including several standard textbooks, three of which have also been translated to Chinese. He is founding member of the German IPv6 council and serves as its general secretary since 2009. He has initiated the academic video search engine yovisto.com and is CEO at yovisto.

Lydia Pintscher

semantics_admin — Wed, 15 Jun 2016 14:15:44 +0000

Product Manager for Wikidata

Wikidata

Keynote

Wikidata: bringing structured data to Wikipedia with 16000 volunteers

Wikidata is Wikimedia's knowledge base that provides structured data about the world for Wikipedia, its sister projects and the world. It was started 4 years ago and has grown into a significant player in the open data and Wikimedia ecosystem. This talk will give
you insights into the current state of the project. It will go into the successes as well as struggles the project still has and share lessons learned from bringing structured data to Wikipedia.

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Lydia Pintscher studied computer science at the University of Karlsruhe. She started doing marketing, and later community and release management for Amarok. She has since moved on to community management and running mentoring programs for all of KDE. She is on the board of directors of KDE e.V. since 2011. Since 2013 she's Product Manager for Wikidata.

For more information please have a look at her resume and this collection of links to various other websites like social networks, whishlists, code repositories and more.

Cathy Dolbear

blumauera — Tue, 03 May 2016 11:54:02 +0000

Senior Link Architect

Oxford University Press

Keynote

Enriching Content with User Data and Semantic Information

Oxford University Press, a department of the University of Oxford, has been developing semantic enrichment capabilities over a number of years, to improve the management and usage of our books, journals and dictionary content.

This talk is about how we’re combining human-authored semantic information with semantic tags and taxonomy classifications automatically extracted from our content. I’ll touch on the requirements we have as a user of text mining applications and cover our learning experiences of implementing schema.org markup on our sites.

I’ll also introduce the Oxford Global Languages project, which links lexical information from multiple global and also digitally under-represented languages such as isiZulu and Urdu in a triple store. The strong community involvement allows users who are native speakers of those languages to contribute to the dictionaries, building up a better interlinking of all languages which can then be accessed via an API, to be publicly launched this autumn.

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Cathy Dolbear is currently a Senior Link Architect at Oxford University Press, working on the semantic enrichment of journals and book content, for linking, search and SEO. She is interested in the intersection between semantic, content, product and user data and how linked data paradigms can support their management. She holds a DPhil in Information Engineering from the University of Oxford, is the author of the book “Linked Data: A geographic perspective”, and holds several patents in personalisation and multimedia technologies. She previously worked as a research scientist investigating geospatial semantics and geographical linked data at Ordnance Survey, and has held roles in multimedia applications research at Motorola and Sharp Labs.

Volker Tresp

semantics_admin — Tue, 22 Mar 2016 12:38:53 +0000

Principal Research Scientist Siemens, Professor @ LMU

SIEMENS

Keynote

Learning with Memory Embeddings and its Application in the Digitalization of Healthcare

Embedding learning, a.k.a. representation learning, has been shown to be able to model large-scale semantic knowledge graphs. A key concept is a mapping of the knowledge graph to a tensor representation whose entries are predicted by models using latent representations of generalized entities. Latent variable models are well suited to deal with the high dimensionality and sparsity of typical knowledge graphs and have successfully been employed in knowledge graph completion and fact extraction from the Web. We have extended the approach to also consider temporal evolutions, temporal patterns and subsymbolic representations, which permits us to model medical decision processes. In addition, we consider embedding approaches to be a possible basis for modeling cognitive memory functions, in particular semantic and concept memory, episodic memory, sensory memory, short-term memory, and working memory.

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Volker Tresp received a Diploma degree from the University of Goettingen, Germany, in 1984 and the M.Sc. and Ph.D. degrees from Yale University, New Haven, CT, in 1986 and 1989 respectively. Since 1989 he is the head of various research teams in machine learning at Siemens, Research and Technology. He filed more than 70 patent applications and was inventor of the year of Siemens in 1996. He has published more than 100 scientific articles and administered over 20 Ph.D. theses. The company Panoratio is a spin-off out of his team. His research focus in recent years has been „Machine Learning in Information Networks“ for modelling Knowledge Graphs, medical decision processes and sensor networks. He is the coordinator of one of the first nationally funded Big Data projects for the realization of „Precision Medicine“. Since 2011 he is also a Professor at the Ludwig Maximilian University of Munich where he teaches an annual course on Machine Learning.

Michele Pasin

semantics_admin — Tue, 22 Mar 2016 12:27:57 +0000

Lead data architect

Springer Nature

Keynote

Linked data experience at Springer Nature

Building discovery services for scientific and scholarly content on top of a semantic data model

This talk provides a summary and reflection on how we think that Semantic Technologies are an effective way to do enterprise metadata management at web scale – essentially, being able to bring some order to the chaos resulting from multiple applications working on similar data domains.

Springer Nature is a leading publisher the Science & Scholarly area, which includes flagship journals like Nature and Scientific American, several titles under the Nature and Nature Reviews brands, plus several other products such as the Springer Book collections, Springer Journals and Springer Corporate Databases. It's a very diversified scenario which includes more than 3000 journals plus of course many other publication types like books, blogs or podcasts.

As a result of the digital revolution and the internet, new products are being created at a much faster rate than it has ever happened before - which has led the company in the last years to recognize the need to develop an integration layer that can bring together data from any of the applications that power the specific products we have on offer. In particular, we need interoperability both at the level of naming conventions - so to facilitate communication within the enterprise when people talk about articles or subject areas - and at a more formal semantic level, via a shared metadata model implemented as a set of ontologies.

To this end, we have been using Semantic and Linked Data technologies since 2012, when we lauched a prototype open platform called data.nature.com. Subsequently, we have been working on various other projects including the nature ontologies portal (http://www.nature.com/ontologies, 2015) and the springer conferences portal (http://lod.springer.com, 2015). More generally, our focus has increasingly shifted from external data publishing to our internal systems – in particular we aimed at creating an architecture where RDF is core to the publishing workflow as much as XML is. In this talk we would like to provide an overview of this exciting and interesting journey, which is now taking us to the creation of a new platform that combines content, science and people data from across Springer Nature and that will be launched in late 2016.

The challenges and lessons learned we will touch on include:

how to build knowledge models and data architectures which aim at leveraging sem tech within a traditionally XML-based publishing workflow: in other words, how to introduce these new technologies in such a way that the solve real problems without disrupting established workflows?
the importance a coherent metadata management and semantic integration solution can have for any enterprise looking at maintaining their competitive advantage in the knowledge society.
the value of making available open data to the scientific community (and the larger public), as a way to promote innovation and making it easier for scientists to do reseach. At the same time, the difficulties encountered in getting non data specialists involved with data which are instead encoded using Linked data standards.
challenges involved in identifying, indexing and transforming data coming from heterogeneous sources into a flexible yet coherent web-scalable metadata management layer.

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Michele Pasin is an information and data architect with a focus on enterprise metadata management and semantic technologies. Michele currently works for Springer Nature, a publishing company resulting from the May 2015 merger of Springer Science+Business Media and Holtzbrinck Publishing Group's Nature Publishing Group, Palgrave Macmillan, and Macmillan Education.

He has recently taken up the role of lead data architect for the knowledge graph project, an initiative whose goal is to bring together various preexisting linked data repositories, plus a number of other structured and unstructured data sources, into a unified, highly integrated knowledge discovery platform. Before that, he worked on projects like nature.com’s subject pages (a dynamic section of the website that allow users to navigate content by topic) and the nature.com ontologies portal (a public repository of linked open data).

He holds a PhD in semantic web technologies from the Knowledge Media Institute (The Open University, UK) and advanced degrees in logic and philosophy of language from the University of Venice (Italy). Previously, he was a research associate at King's College Department of Digital Humanities (London), where he developed on a number of cultural informatics projects such as the People of Medieval Scotland and the Art of Making in Antiquity.

Online Portfolio: http://www.michelepasin.org/projects/

Marie Wallace

semantics_admin — Tue, 22 Mar 2016 09:30:07 +0000

Analytics Strategist, IBM

IBM

Keynote

The Semantics of the Human Network

Turning Chaos into Clarity

With the advent of social media and the rise of mobile as the platform of choice for end-user applications, people data is becoming the most valuable commodity in town where we now have an opportunity to capture human context, at a global level and as its happening, and generate insights that will completely transform the human digital experience. However, this assumes that we can effectively model and analyse this data. This is frequently not the case where we are faced with social silos that speak a completely different language both in terms of the APIs they expose and the semantics of the underlying network. If we want to truly leverage the data that is being laid down by these new generation of people-centric applications and services, then we need to address these interoperability issues, not least of all the semantics of human interaction.

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Marie is currently an analytics strategist for IBM, having spent  more than a decade in the research and development division building content, semantic and social analytics technologies which today underpin such solutions as IBM Watson. In recent years her primary focus has been on the analysis of people networks to deliver smarter, personalized and contextualized solutions for individuals and organizations.

Marie sit on advisory boards for the Digital Repository of Ireland at the Royal Irish Academy, and the Digital Arts & Humanities PhD Program at Trinity College Dublin.

She is a globally recognized thought leader, with an active social media presence and popular blog, AllThingsAnalytics.com.