Many scientific experiments produce an enormous amount of data that needs to be explored. Scientific workflows and tools for managing workflows have been designed to streamline the computational processes that manipulate this data, from acquisition to analysis. However, the fact that each system has its own workflow format has greatly hampered efficient sharing and re-use. To address this problem, we propose a general model for workflows, based on OPM, which combines features from popular scientific workflow systems. We use this model to build infrastructure that supports system-agnostic workflow repositories. We describe the implementation of the infrastructure and present an experimental evaluation of its performance. We show that the proposed model and its implementation provide efficient support for queries over large repositories.

Provenance is essential in scientific experiments. It contains information that is key to preserving the data and to determine it's quality and authorship. In complex experiments and analyses, where multiple tools are used to derive data products, provenance captured by these tools must be combined in order to determine the complete lineage of the derived products. We propose a mediator-based architecture to integrate provenance information from multiple sources, which contains two key components: a global mediated schema that is general and capable of representing provenance information represented in different models; and an expressive query interface that supports complex queries over provenance information spread over multiple different sources. We also present a case study where we show how this model was applied to integrate provenance from three provenance-enabled systems.

One important aim within systems biology is to integrate disparate pieces of information, leading to discovery of higher-level knowledge about important functionality within living organisms. This makes standards for representation of data and technology for exchange and integration of data important key points for development within the area. In this article, we focus on the recent developments within the field. We compare the recent updates to the three standard representations for exchange of data SBML, PSI MI and BioPAX. In addition, we give an overview of available tools for these three standards and a discussion on how these developments support possibilities for data exchange and integration.

MOTIVATION: Analysis and simulation of pathway data is of high importance in bioinformatics. Standards for representation of information about pathways are necessary for integration and analysis of data from various sources. Recently, a number of representation formats for pathway data, SBML, PSI MI and BioPAX, have been proposed. RESULTS: In this paper we compare these formats and evaluate them with respect to their underlying models, information content and possibilities for easy creation of tools. The evaluation shows that the main structure of the formats is similar. However, SBML is tuned towards simulation models of molecular pathways while PSI MI is more suitable for representing details about particular interactions and experiments. BioPAX is the most general and expressive of the formats. These differences are apparent in allowed information and the structure for representation of interactions. We discuss the impact of these differences both with respect to information content in existing databases and computational properties for import and analysis of data.

Share it! is a European project with a focus on developing concepts and solutions for interconnecting digital TV set top boxes that enable users to share TV-programmes. One important goal of the project is to set future standards, e.g. in content management and rights management, for broadband connected digital television. We introduce the project objectives and the consortium, and then focus on how P2P technology and JXTA platform are used in solving various important issues that help to achieve the project goals.

Spoken dialogue systems must allow for robust and efficient interpretation of user utterances. This can be achieved by using shallow and partial interpretation. Partial interpretation is feasible together with a dialogue manager which provides information to guide the analysis. In this paper we present results on developing interfaces for information retrieval applications utilizing partial and information directed interpretation with unification-based formalisms, traditionally used for deep and complete analysis. The major advantage with our approach is that the time to develop the interpretation modules is reduced. Furthermore, the system will be fairly robust as large parts of the knowledge bases containing knowledge on ways in which a user can express a domain concept can be generated automatically or semi-automatically. 1. INTRODUCTION Traditionally, computational linguistics has developed formalisms for providing deep and complete analysis of natural language. In a spoken dialo...

A common feature of recent unification-based grammar formalisms is that they give the user the ability to define his own structures. However, this possibility is mostly limited and does not include nonmonotonic operations. In this paper we show how nonmonotonic operations can also be user-defined by applying default logic (Reiter, 1980) and generalizing previous results on nonmonotonic sorts (Young and Rounds, 1993).