International Journal of Software Engineering and Knowledge Engineering

Thanks to Open Data initiatives the amount of data available on the Web is rapidly increasing. Unfortunately, most of these initiatives only publish raw tabular data, which makes its analysis and reuse very difficult. Linked Data principles allow for a more sophisticated approach by making explicit both the structure and semantics of the data. However, from the user experience viewpoint, published datasets continue to be monolithic files which are completely opaque or difficult to explore by making complex semantic queries. Our objective is to facilitate the user to grasp what kind of entities are in the dataset, how they are interrelated, which are their main properties and values, etc. Rhizomer is a data publishing tool whose interface provides a set of components borrowed from Information Architecture (IA) that facilitate getting an insight of the dataset at hand. Rhizomer automatically generates navigation menus and facets based on the kinds of things in the dataset and how they are described through metadata properties and values. This tool is currently being evaluated with end users that discover a whole new perspective of the Web of Data.

Research Information Systems (RIS) play a critical role in the sharing of scientific information and provide researchers, professionals and decision makers with the required data for their activities. Existing RIS standards have proposed data models to represent the main entities for storage and exchange. These account for the needs of multiple stakeholders through a high flexibility based on a formal syntax and declared semantics, but for techno-historical reasons they assume the completeness of information within system boundaries. The distributed nature of research information across systems calls for a mechanism to link the local entities from the closed world of concrete RISs with other possibly underspecified entities exposed through other means, as for example, the Linked Open Data Web. By transformation of a relational model into an open graph model, differences between the two system paradigms are revealed. The main principles and techniques for exposing CERIF-driven relational data as linked data will be provided as a first step demonstrating effective RISs interconnection through the linked open data (LOD) Web.

This paper aims to describe a public procurement information platform which provides a unified pan-European system that exploits the aggregation of tender notices using linking open data and semantic web technologies. This platform requires a step-based method to deal with the requirements of the public procurement sector and the open government data initiative: (1) modeling the unstructured information included in public procurement notices (contracting authorities, organizations, contracts awarded, etc.); (2) enriching that information with the existing product classification systems and the linked data vocabularies; (3) publishing relevant information extracted out of the notices following the linking open data approach; (4) implementing enhanced services based on advanced algorithms and techniques like query expansion methods to exploit the information in a semantic way. Taking into account that public procurement notices contain different kinds of data like types of contract, region, duration, total amount, target enterprise, etc., various methods can be applied to expand user queries easing the access to the information and providing a more accurate information retrieval system. Nevertheless expanded user queries can involve an extra-time in the process of retrieving notices. That is why a performance evaluation is outlined to tune up the semantic methods and the generated queries providing a scalable and time-efficient system. Moreover, this platform is supposed to be especially relevant for SMEs that want to tender in the European Union (EU), easing their access to the information of the notices and fostering their participation in cross-border public procurement processes across Europe. Finally an example of use is provided to evaluate and compare the goodness and the improvement of the proposed platform with regard to the existing ones.

Requirements traceability enables software engineers to trace a requirement from its emergence to its fulfillment. In this paper we examine requirements traceability definitions, challenges, tools and techniques, by the use of a systematic review performing an exhaustive search through the years 1997–2007. We present a number of common definitions, challenges, available tools and techniques (presenting empirical evidence when found), while complementing the results and analysis with a static validation in industry through a series of interviews.

Software cost estimation (SCE) is one of the critical activities in software project management. During the past decades various models have been proposed for SCE. However, developing accurate and useful models is limited in practice despite the considerable financial gain they could offer to software stakeholders. Traditional techniques, such as regression, by-analogy and machine learning, face the difficulty of handling the dynamic nature of the software process and the problematic nature of the public data available. This paper addresses the issue of SCE proposing an alternative approach that combines robust decision tree structures with fuzzy logic. Fuzzy decision trees are generated using the CHAID and CART algorithms in a systematic manner, while development effort is treated as the dependent variable against two subsets of factors: The first contains selected attributes from the ISBSG, COCOMO and DESHARNAIS datasets and the second contains a subset of the available factors that can be measured early in the development cycle. The association rules obtained from the trees are then merged and defuzzified through a Fuzzy Implication System (FIS). The fuzzy framework is utilized to perform effort estimations. Experimental results indicate that the proposed approach is promising as it yields quite accurate estimations in most dataset cases considered. Finally, our evaluation suggests that accurate estimations may be produced, even when using only a small set of factors that can be measured early in the development cycle, thus increasing the practical value of the proposed cost model.