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More and more governments around the world are publishing tabular open data, mainly in formats such as CSV or XLS(X). These datasets are mostly individually published, i.e. each publisher exposes its data on the Web without considering potential relationships with other datasets (from its own or from other publishers). As a result, reusing several open datasets together is not a trivial task, thus requiring mechanisms that allow data consumers (as software developers or data scientists) to integrate and access tabular open data published on the Web. In this paper, we propose a model-driven approach to automatically generate Web APIs that homogeneously access multiple integrated tabular open datasets. This work focuses on data that can be integrated by means of join and union operations. As a first step, our approach detects unionable and joinable tabular open data by using a table similarity measure based on word embeddings. Then, an APIfication process is developed to create APIs that access the previously integrated datasets through a single endpoint. A running example is presented throughout the article, as well as a set of experiments for performance evaluation to show the feasibility of our approach. This work was supported by the National Foundation for Research, Technology and Development of the Spanish Ministry of Economy, Industry and Competitiveness under Project TIN2016-78103-C2-2-R and Project RTI2018-094653-B-C22. The work of César González-Mora was supported by a contract for predoctoral training with the Generalitat Valenciana and the European Social Fund under Grant ACIF/2019/044.

Public Sector Information is considered to play a fundamental role in the growth of the knowledge economy and improvements in society. Given the difficulty in publishing and maintaining all available data, due to budget constraints, institutions need to select which data to publish, giving priority to data most likely to generate social and economic impact. Priority of publication could become an even more significant problem in Smart Cities: as huge amounts of information are generated from different domains, the way data is prioritized and thus reused, could be a determining factor in promoting, among others, new and sustainable business opportunities for local entrepreneurs, and to improve citizen quality of life. However, people in charge of prioritizing which data to publish through open data portals (such as Chief Data Officers, or CDOs) do not have available any specific support in their decision-making process. In this work, a proposal of a framework for prioritization of open data publication as well as its application to Smart Cities is presented. This specific application of the framework relies on OSS (Open Source Software) indicators to help making decisions on the most relevant data to publish focused on developers and businesses operating within the Smart City context. This work was funded by (i) Ministerio de Economía e Innovación (Spain) TIN2015-69957-R (MINECO/ERDF, EU) project and TIN2016-78103-C2-2-R (MINECO/ERDF, EU) project, (ii) POCTEP 4IE project (0045-4IE-4-P), and (iii) Consejería de Economía e Infraestructuras/Junta de Extremadura (Spain) - European Regional Development Fund (ERDF)- GR18112 project and IB16055 project.

The ever-growing amount of information in today’s world has led to the publication of more and more open data, i.e., that which is available in a free and reusable manner, on the Web. Open data is considered highly valuable in situational scenarios, in which thematic data is required for a short life cycle by a small group of consumers with specific needs. In this context, data consumers (developers or data scientists) need mechanisms with which to easily assess whether the data is adequate for their purpose. SPARQL endpoints have become very useful for the consumption of open data, but we argue that its steep learning curve hampers open data reuse in situational scenarios. In order to overcome this pitfall, in this paper, we coin the term disposable Web APIs as an alternative mechanism for the consumption of open data in situational scenarios. Disposable Web APIs are created on-the-fly to be used temporarily by a user to consume open data. In this paper we specifically describe an approach with which to leverage semantic information from data sources so as to automatically generate easy-to-use disposable Web APIs that can be used to access open data in a situational scenario, thus avoiding the complexity and learning curve of SPARQL and the effort of manually processing the data. We have conducted several experiments to discover whether non-experienced users find it easier to use our disposable Web API or a SPARQL endpoint to access open data. The results of the experiments led us to conclude that, in a situational scenario, it is easier and faster to use the Web API than the corresponding SPARQL endpoint in order to consume open data. This work was supported in part by the Access@City coordinated Research Project through the Spanish Ministry of Science, Innovation and Universities under Grant TIN2016-78103-C2-1-R and Grant TIN2016-78103-C2-2-R; in part by the Plataforma intensiva en datos proveedora de servicios inteligentes de movilidad (MoviDA) Project through Rey Juan Carlos University; and in part by the Recolección y publicación de datos abiertos para la reactivación del sector turístico postCOVID-19 (UAPOSTCOVID19-10) Project through the Consejo Social of the University of Alicante. The work of César González-Mora was supported in part by the Generalitat Valenciana, and in part by the European Social Fund under Grant ACIF/2019/044.

Due to the large, heterogeneous audience of Web applications, and its rapidly changing expectations, holistic requirement analysis approaches are crucial to ensure the success of Web engineering projects. To increase the quality of resulting Web applications, non-functional requirements (NFRs) must be considered. Satisfying them is a non-trivial task that depends on making decisions about which functional requirements (FRs) to implement, and how to prioritize the NFRs. A satisfactory solution is a trade-off, where competing NFRs must be balanced. In this paper, we outline how the Pareto efficiency can complement a goal-oriented requirement analysis modelling to evaluate and select optimal configurations of requirements for a Web application, while NFRs are balanced and maximized according to a priority list. We hereby focus on an empirical evaluation to verify whether our Pareto method improves the accuracy of design decisions during the requirements analysis phase, and/or if it reduces the time needed by designers. Este trabajo ha sido parcialmente financiado por los siguientes proyectos: Open.Mind (GV/2014/098) de la Generalitat Valenciana; PROFAPI2012/002 y PROFAPI2013/002 de la Universidad Autónoma de Sinaloa, México y MANTRA (GRE09-17) de la Universidad de Alicante.

One of the most difficult problems that humanity currently faces is the sustainable development of our society, i.e. how to meet the needs of the present without compromising the ability of future generations to meet their own needs. Solving this challenge requires a multidisciplinary approach where researchers with different backgrounds combine their efforts. As software engineers, we can contribute to these efforts by offering existing software requirements modeling and analysis techniques as a means to integrate sustainability requirements in decision-making processes. In this paper, we use a popular language for modeling early requirements as a way to visualize the impact of alternative options on sustainability goals and to analyze the conflicts between sustainability and other problem-specific objectives. We apply this idea to the decision-making activities pertaining to the organization of the ICSE'09 conference itself. Cabot’s work was supported by the Catalan Government (Grant 2007 BP-A 00128). Mazón’s work was funded by the Spanish Ministry of Education & Science (FPU grant AP2005-1360). Additional funding was provided by NSERC.