A Sustainability Catalogue for Software Modelling

Sustainable development is the development that meets the needs of the present without compromising the needs of our future generations. It covers five different dimensions: environmental, economic, social, technical, and individual. Such dimensions are also of interest for software. For example, memory and power efficiency have an impact on the environmental dimension, the reduction of costs in software development and evolution relates to the economic dimension, the use of software for general improvement of people’s lives affects the social dimension, the software’s ability to cooperate with other systems impacts the technical dimension, and the improvement of well-being of individuals relates to the individual dimension. These various dimensions and their properties impact on each other and on the base requirements of a system. Therefore, well-informed design decisions require improved support to reason on such intra- and inter-relationships and impacts, early in development. The objective of this dissertation is to propose a catalog of sustainability requirements for later reuse during the software development process. The envisioned solution involves using requirement engineering activities to address sustainability in the early stages of the software development. The first step towards a solution was to perform a (agile) systematic mapping study in order to gain a complete and profound knowledge about the existing sustainability and requirement engineering techniques. This study was the base of our work. Our final artifact is a sustainability catalogue. This catalogue addresses four out of the five dimensions of sustainability, as well as their qualities and relationships. We did not treat the individual dimension, for sake of simplicity and time constraints, although we consider that some of its properties are included in the social dimension. The catalogue was developed using the iStar framework, and it was implemented in the piStar Tool. Such catalogue offers a generic approach that can be instantiated for particular application domains, and for any combination of dimensions. Hence, this work will contribute to the field of sustainable software development

A Survey on Important Aspects of Information Retrieval

Information retrieval has become an important field of study and research under computer science due to the explosive growth of information available in the form of full text, hypertext, administrative text, directory, numeric or bibliographic text. The research work is going on various aspects of information retrieval systems so as to improve its efficiency and reliability. This paper presents a comprehensive survey discussing not only the emergence and evolution of information retrieval but also include different information retrieval models and some important aspects such as document representation, similarity measure and query expansion

Overview of the CLEF 2016 Social Book Search Lab

The Social Book Search (SBS) Lab investigates book search in scenarios where users search with more than just a query, and look for more than objective metadata. Real-world information needs are generally complex, yet almost all research focuses instead on either relatively simple search based on queries, or on profile-based recommendation. The goal is to research and develop techniques to support users in complex book search tasks. The SBS Lab has three tracks. The aim of the Suggestion Track is to develop test collections for evaluating ranking effectiveness of book retrieval and recommender systems. The aim of the Interactive Track is to develop user interfaces that support users through each stage during complex search tasks and to investigate how users exploit professional metadata and user-generated content. The Mining Track focuses on detecting and linking book titles in online book discussion forums, as well as detecting book search research in forum posts for automatic book recommendation.Peer Reviewe

Explorative search of distributed bio-data to answer complex biomedical questions

Background The huge amount of biomedical-molecular data increasingly produced is providing scientists with potentially valuable information. Yet, such data quantity makes difficult to find and extract those data that are most reliable and most related to the biomedical questions to be answered, which are increasingly complex and often involve many different biomedical-molecular aspects. Such questions can be addressed only by comprehensively searching and exploring different types of data, which frequently are ordered and provided by different data sources. Search Computing has been proposed for the management and integration of ranked results from heterogeneous search services. Here, we present its novel application to the explorative search of distributed biomedical-molecular data and the integration of the search results to answer complex biomedical questions. Results A set of available bioinformatics search services has been modelled and registered in the Search Computing framework, and a Bioinformatics Search Computing application (Bio-SeCo) using such services has been created and made publicly available at http://www.bioinformatics.deib.polimi.it/bio-seco/seco/. It offers an integrated environment which eases search, exploration and ranking-aware combination of heterogeneous data provided by the available registered services, and supplies global results that can support answering complex multi-topic biomedical questions. Conclusions By using Bio-SeCo, scientists can explore the very large and very heterogeneous biomedical-molecular data available. They can easily make different explorative search attempts, inspect obtained results, select the most appropriate, expand or refine them and move forward and backward in the construction of a global complex biomedical query on multiple distributed sources that could eventually find the most relevant results. Thus, it provides an extremely useful automated support for exploratory integrated bio search, which is fundamental for Life Science data driven knowledge discovery

Building high-quality merged ontologies from multiple sources with requirements customization

Ontologies are the prime way of organizing data in the Semantic Web. Often, it is necessary to combine several, independently developed ontologies to obtain a knowledge graph fully representing a domain of interest. Existing approaches scale rather poorly to the merging of multiple ontologies due to using a binary merge strategy. Thus, we aim to investigate the extent to which the n-ary strategy can solve the scalability problem. This thesis contributes to the following important aspects: 1. Our n-ary merge strategy takes as input a set of source ontologies and their mappings and generates a merged ontology. For efficient processing, rather than successively merging complete ontologies pairwise, we group related concepts across ontologies into partitions and merge first within and then across those partitions. 2. We take a step towards parameterizable merge methods. We have identified a set of Generic Merge Requirements (GMRs) that merged ontologies might be expected to meet. We have investigated and developed compatibilities of the GMRs by a graph-based method. 3. When multiple ontologies are merged, inconsistencies can occur due to different world views encoded in the source ontologies To this end, we propose a novel Subjective Logic-based method to handling the inconsistency occurring while merging ontologies. We apply this logic to rank and estimate the trustworthiness of conflicting axioms that cause inconsistencies within a merged ontology. 4. To assess the quality of the merged ontologies systematically, we provide a comprehensive set of criteria in an evaluation framework. The proposed criteria cover a variety of characteristics of each individual aspect of the merged ontology in structural, functional, and usability dimensions. 5. The final contribution of this research is the development of the CoMerger tool that implements all aforementioned aspects accessible via a unified interface