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The diffusion of Open Government Data (OGD) in recent years kept a very fast pace. However, evidence from practitioners shows that disclosing data without proper quality control may jeopardize datasets reuse and negatively affect civic participation. Current approaches to the problem in literature lack of a comprehensive theoretical framework. Moreover, most of the evaluations concentrate on open data platforms, rather than on datasets. In this work, we address these two limitations and set up a framework of indicators to measure the quality of Open Government Data on a series of data quality dimensions at most granular level of measurement. We validated the evaluation framework by applying it to compare two cases of Italian OGD datasets: an internationally recognized good example of OGD, with centralized disclosure and extensive data quality controls, and samples of OGD from decentralized data disclosure (municipalities level), with no possibility of extensive quality controls as in the former case, hence with supposed lower quality. Starting from measurements based on the quality framework, we were able to verify the difference in quality: the measures showed a few common acquired good practices and weaknesses, and a set of discriminating factors that pertain to the type of datasets and the overall approach. On the basis of this evaluation, we also provided technical and policy guidelines to overcome the weaknesses observed in the decentralized release policy, addressing specific quality aspects.

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The paper summarizes the results of several industrial surveys on issues related to the development of systems using Commercial-Off-The-Shelf and Open Source Software components. The results demonstrate the following. (1) There is a discrepancy between academic theory and industrial practices regarding the use of components. One reason is that researchers have empirically evaluated only a few theoretical methods; hence, industrial practitioners currently have no reason to adopt them. Another reason might be that researchers have specified the contexts of application of only a small number of theories in sufficient detail to avoid misleading users. (2) Academic researchers often hold false assumptions about industry. For example, research on requirement negotiations often assumes that a client will be interested in, and be capable of, discussing the technical details of a project. However, in practice this is usually not true. In addition, the quality of a component in the final system is often attributed solely to component quality before integration, ignoring quality improvements by integrators during component integration.

Context: Claimed benefits of software modelling and Model Driven techniques are improvements in productivity, portability, maintainability and interoperability. However, little effort has been devoted at collecting evidence to evaluate their actual relevance, benefits and usage complications.Goal: The main goals of this paper are: (1) assess the diffusion and relevance of software modelling and MD techniques in the Italian industry, (2) understand the expected and achieved benefits, and (3) identify which problems limit/prevent their diffusion.Method: We conducted an exploratory personal opinion survey with a sample of 155 Italian software professionals by means of a web-based questionnaire on-line from February to April 2011.Results: Software modelling and MD techniques are very relevant in the Italian industry. The adoption of simple modelling brings common benefits (better design support, documentation improvement, better maintenance, and higher software quality), while MD techniques make it easier to achieve: improved standardization, higher productivity, and platform independence. We identified problems, some hindering adoption (too much effort required and limited usefulness) others preventing it (lack of competencies and supporting tools).Conclusions: The relevance represents an important objective motivation for researchers in this area. The relationship between techniques and attainable benefits represents an instrument for practitioners planning the adoption of such techniques. In addition the findings may provide hints for companies and universities.

In recent years, several design notations have been proposed to model domain-specific applications or reference architectures. In particular, Conallen has proposed the UML Web Application Extension (WAE): a UML extension to model Web applications. The aim of our empirical investigation is to test whether the usage of the Conallen notation supports comprehension and maintenance activities with significant benefits, and whether such benefits depend on developers ability and experience. This paper reports and discusses the results of a series of four experiments performed in different locations and with subjects possessing different experience-namely, undergraduate students, graduate students, and research associates-and different ability levels. The experiments aim at comparing performances of subjects in comprehension tasks where they have the source code complemented either by standard UML diagrams or by diagrams stereotyped using the Conallen notation. Results indicate that, although, in general, it is not possible to observe any significant benefit associated with the usage of stereotyped diagrams, the availability of stereotypes reduces the gap between subjects with low skill or experience and highly skilled or experienced subjects. Results suggest that organizations employing developers with low experience can achieve a significant performance improvement by adopting stereotyped UML diagrams for Web applications.

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Proponents of design notations tailored for specific application domains or reference architectures, often available in the form of UML stereotypes, motivate them by improved understandability and modifiability. However, empirical studies that tested such claims report contradictory results, where the most intuitive notations are not always the best performing ones. This indicates the possible existence of relevant influencing factors, other than the design notation itself. In this work we report the results of a family of three experiments performed at different locations and with different subjects, in which we assessed the effectiveness of UML stereotypes for Web design in support to comprehension tasks. Replications with different subjects allowed us to investigate whether subjects' ability and experience play any role in the comprehension of stereotyped diagrams. We observed different behaviors of users with different degrees of ability and experience, which suggests alternative comprehension strategies of (and tool support for) different categories of user