Accelerating Scientific Discovery by Formulating Grand Scientific Challenges

One important question for science and society is how to best promote scientific progress. Inspired by the great success of Hilbert's famous set of problems, the FuturICT project tries to stimulate and focus the efforts of many scientists by formulating Grand Challenges, i.e. a set of fundamental, relevant and hardly solvable scientific questions.Comment: To appear in EPJ Special Topics. For related work see http://www.futurict.eu and http://www.soms.ethz.c

Streaming the Web: Reasoning over dynamic data.

In the last few years a new research area, called stream reasoning, emerged to bridge the gap between reasoning and stream processing. While current reasoning approaches are designed to work on mainly static data, the Web is, on the other hand, extremely dynamic: information is frequently changed and updated, and new data is continuously generated from a huge number of sources, often at high rate. In other words, fresh information is constantly made available in the form of streams of new data and updates. Despite some promising investigations in the area, stream reasoning is still in its infancy, both from the perspective of models and theories development, and from the perspective of systems and tools design and implementation. The aim of this paper is threefold: (i) we identify the requirements coming from different application scenarios, and we isolate the problems they pose; (ii) we survey existing approaches and proposals in the area of stream reasoning, highlighting their strengths and limitations; (iii) we draw a research agenda to guide the future research and development of stream reasoning. In doing so, we also analyze related research fields to extract algorithms, models, techniques, and solutions that could be useful in the area of stream reasoning. © 2014 Elsevier B.V. All rights reserved

An Infrastructure for acquiring high quality semantic metadata

Because metadata that underlies semantic web applications is gathered from distributed and heterogeneous data sources, it is important to ensure its quality (i.e., reduce duplicates, spelling errors, ambiguities). However, current infrastructures that acquire and integrate semantic data have only marginally addressed the issue of metadata quality. In this paper we present our metadata acquisition infrastructure, ASDI, which pays special attention to ensuring that high quality metadata is derived. Central to the architecture of ASDI is a erification engine that relies on several semantic web tools to check the quality of the derived data. We tested our prototype in the context of building a semantic web portal for our lab, KMi. An experimental evaluation omparing the automatically extracted data against manual annotations indicates that the verification engine enhances the quality of the extracted semantic metadata

Knowledge representation on the web

Exploiting the full potential of the World Wide Web will require semantic as well as syntactic interoperability. This can best be achieved by providing a further representation and inference layer that builds on existing and proposed web standards. The OIL language extends the RDF schema standard to provide just such a layer. It combines the most attractive features of frame based languages with the expressive power, formal rigour and reasoning services of a very expressive description logic.

A wide-spectrum approach to modelling and analysis of organisation for machine-assisted decision-making

This paper describes a modeling approach that helps to represent necessary aspects of complex socio-technical systems, such as organization, in an integrated form and provides a simulation technique for analyzing these organisations. An actor-based language is introduced and compared to a conventional simulation approach (Stock-and-Flow) by simulating aspects of a software services company

On the emergent Semantic Web and overlooked issues

The emergent Semantic Web, despite being in its infancy, has already received a lotof attention from academia and industry. This resulted in an abundance of prototype systems and discussion most of which are centred around the underlying infrastructure. However, when we critically review the work done to date we realise that there is little discussion with respect to the vision of the Semantic Web. In particular, there is an observed dearth of discussion on how to deliver knowledge sharing in an environment such as the Semantic Web in effective and efficient manners. There are a lot of overlooked issues, associated with agents and trust to hidden assumptions made with respect to knowledge representation and robust reasoning in a distributed environment. These issues could potentially hinder further development if not considered at the early stages of designing Semantic Web systems. In this perspectives paper, we aim to help engineers and practitioners of the Semantic Web by raising awareness of these issues