Lora Aroyo (VU University Amsterdam) 

Truth is Lie: Rules & Semantics from a Crowd Perspectives

Processing real-world data with the crowd leaves one thing absolutely clear - there is no single notion of truth, but rather a spectrum that has to account for context, opinions, perspectives and shades of grey. CrowdTruth is a new framework for processing of human semantics drawn more from the notion of consensus then from set theory.

[Slides]

Lora Aroyo is an associate professor of Computer Science at VU University in Amsterdam, the Netherlands, where she heads the Web & Media group. Dr. Aroyo is an internationally known expert in multimedia interaction. Her research work is focused on semantic technologies for modeling user and context in recommendation systems and personalized access of online multimedia collections, e.g. cultural heritage collections, multimedia archives and interactive TV. She has organized a numerous events on crowdsourcing, social web and cultural heritage. Lora is actively involved in the Semantic Web community as a program chair for the European and the International Semantic Web Conferences in 2009 and 2011, as conference chair for the ESWC 2010 Conference. She is also actively involved in the Personalization and User modeling community as vice-president of the User Modeling Inc. In 2012 and 2013 she won IBM Faculty Awards for her work on CrowdTruth: An approach to crowdsourcing for ground truth data, in the context of adapting IBM Watson system to medical domain.

Michael Genesereth (Stanford University)

The Herbrand Manifesto - Thinking Inside the Box

The traditional semantics for First Order Logic (sometimes called Tarskian semantics) is based on the notion of interpretations of constants.  Herbrand semantics is an alternative semantics based directly on truth assignments for ground sentences rather than interpretations of constants. Herbrand semantics is simpler and more intuitive than Tarskian semantics; and, consequently, it is easier to teach and learn.  Moreover, it is more expressive.  For example, while it is not possible to finitely axiomatize integer arithmetic with Tarskian semantics, this can be done easily with Herbrand Semantics.  The downside is a loss of some common logical properties, such as compactness and completeness.  However, there is no loss of inferential power.  Anything that can be proved according to Tarskian semantics can also be proved according to Herbrand semantics.  In this presentation, we define Herbrand semantics; we look at the implications for research on logic and rules systems and automated reasoning; and we assess teh potential for popularizing logic.

Michael Genesereth is an associate professor in the Computer Science Department at Stanford University. He received his Sc.B. in Physics from M.I.T. and his Ph.D. in Applied Mathematics from Harvard University. Genesereth is most known for his work on Computational Logic and applications of that work in Enterprise Management, Electronic Commerce, and Computational Law. He is one of the founders of Teknowledge, CommerceNet, and Mergent Systems. Genesereth is the current director of the Logic Group at Stanford and research director of CodeX (the Stanford Center for Computers and Law).

Benny Kimelfeld (Technion & LogicBlox)

Extending Datalog Intelligence

Prominent sources of Big Data include technological and social trends, such as mobile computing, blogging, and social networking. The means to analyse such data are becoming more accessible with the development of business models like cloud computing, open-source and crowd sourcing. But that data have characteristics that pose challenges to traditional database systems. Due to the uncontrolled nature by which data is produced, much of it is free text, often in informal natural language, leading to computing environments with high levels of uncertainty and error. In this talk I will discuss Datalog --- a well studied rule-based programming paradigm that offers an inherent integration with the database, and has a robust declarative semantics. I will describe extensions of Datalog that I have been exploring towards facing the above challenges. In particular, these extensions allow for incorporating information extraction from text, and for specifying statistical models by probabilistic programming. I will further offer a vision of a database system that aims to facilitate the development of modern data-centric applications, by naturally unifying key functionalities of databases, text analytics, machine learning and artificial intelligence.

[Slides]

Benny Kimelfeld is an Associate Professor of the Computer Science Faculty at Technion - Israel Institute of Technology. After receiving his Ph.D. from The Hebrew University of Jerusalem, he has been a Research Staff Member at IBM Research – Almaden, and a Computer Scientist at LogicBlox. Benny’s research spans a spectrum of both foundational and systems aspects of data management, such as probabilistic databases, information retrieval over structured data, view updates, semistructured data, graph mining, and infrastructure for text analytics. Benny was an invited tutorial speaker at PODS 2014, a co-chair of the first SIGMOD/PODS workshop on Big Uncertain Data (BUDA), and currently serves as an associate editor in the Journal of Computer and System Sciences (JCSS).

Riccardo Rosati (Sapienza Universita di Roma)

Analysis and debugging of ontology-based data access specifications - TALK SPONSORED BY ECCAI 

Ontology-based data access (OBDA) is a recent paradigm for accessing data sources through an ontology that acts as a conceptual, integrated view of the data, and declarative mappings that connect the ontology to the data sources. The framework of OBDA has received a lot of attention in the last years: many theoretical studies have paved the way for the construction of OBDA systems and the development of OBDA projects for enterprise data management in various domains.  One important aspect in OBDA concerns the construction of a system specification, i.e., defining the ontology and the mappings over an existing set of data sources. Mappings are indeed the most complex part of an OBDA specification, since they have to capture the semantics of the data sources and express such semantics in terms of the ontology. More precisely, a mapping is a set of assertions, each one associating a query over the source schema with a query over the ontology; the intuitive meaning of a mapping assertion is that all the tuples satisfying the query over the source schema also satisfy the query over the ontology.  The first experiences in the application of the OBDA framework in real-world scenarios have shown that the semantic distance between the conceptual and the data layer is often very large, because data sources are mostly application-oriented: this makes the definition, debugging, and maintenance of mappings a hard and complex task. Such experiences have clearly shown the need of tools for supporting the management of mappings. However, so far no specific approach has explicitly dealt with the problem of mapping analysis and evolution in the context of OBDA. The work on schema mappings in data exchange, probably the closest one to mapping management in OBDA, has considered the problem of analyzing the formal properties of mappings, but in a different framework and under different assumptions on the schema languages.  In this talk, we will present some recent results on mapping analysis and evolution in OBDA obtained in the context of the Optique European project. More precisely, we will first introduce basic notions of mapping inconsistency and mapping redundancy in an OBDA specification. Then, based on such notions, we will present a computational analysis of the problem of checking the above anomalies in an OBDA specification, for a wide range of ontology languages and for different mapping languages. Finally, we will focus on mapping evolution in OBDA, providing formal definitions and computational results for the basic forms of mapping update when the ontology is changed. This is joint work with Domenico Lembo, José Mora, Domenico Fabio Savo, and Evgenij Thorstensen.

Riccardo Rosati is an associate professor at Sapienza University of Rome, Italy. His main research interests are in the fields of knowledge representation, description logics, semantic technologies, and databases. He has authored more than 180 publications in the above areas. His current research mostly focuses on ontology-based data access. He is leading the Sapienza unit of the Optique European project, which focuses on the application of OBDA solutions to big data management.