1,721,007 research outputs found
Organizing for the Digital World: An Overview of Current IT Solutions to Support Individuals, Communities and Societies
No full textItAIS is an established forum for scholars, researchers and practitioners involved in the Information Systems (IS) field and akin scholarly disciplines where both Italian researchers and scholars from all over the world gather to present and discuss the most important trends in their domain of studies and applications. More precisely, this books collects the revised and extended version of the papers that were selected for their contribution to the more technological and IT-oriented side of the broader conference theme, which was: “Organizing for Digital Economy: societies, communities and individuals”. This main theme, which this book inflects along the IT dimension, acknowledges the opportunity
Putting open data to the test of life: conceptual schemas as a means to compare and measure social value
No full textIn a previous paper, we have investigated the different di- mensions of a classificatory framework suitable to support the assess- ment and benchmarking of the social value of open data initiatives. In this paper, we propose a methodology that compares and evaluates open data social value, and we apply it to the specific domain of hospital care. Through this case study we advocate that social value can be analyzed within a spectrum of measures going from intensional completeness to subjective meaning. We first suggest that open data made available on- line by an organization can be modelled in terms of the corresponding integrated conceptual schema, as a uniform construct. Then, a global schema is created with the integrated schemas, and intensional as well as extensional social value on data can be defined. Valuable information is then extracted from queries based on such constructs, and which may result useful in the different contexts and related needs that users may experience in the domain of health. Finally, we propose a psycho-metric questionnaire to assess the perceived value of the information extracted from open data schemas through the above queries, and applied to dif- ferent scenarios. In this way, we propose to compare and measure the social value of different open data initiatives, as it results from the anal- ysis of the information that can be modelled and extracted from their conceptual schemas, from the quality of their instances, and from the subjective perception of their valuable information in different contexts and for different needs
GovQual: A quality driven methodology for E-Government project planning
No full textWe present a multidisciplinary methodology for E-Government project planning. The set of expertise needed for the design of E-Government systems includes social, juridical, economic, organizational, and technological perspectives. To properly address such a broad range of influences requires a unique vision. Our long-term aim is to use an integrated approach to examine a number of issues which currently present challenges in many E-Government projects. This paper in particular focuses on social and technological aspects of E-Government. The methodology has four phases: (1) state reconstruction, (2) quality assessment, (3) new quality targets definition, and (4) preliminary operational planning. A case study provides evidence of the feasibility and effectiveness of the methodology.</p
On the Meaningfulness of “Big Data Quality” (Invited Paper)
Full text linkIn this paper, we discuss the application of concept of data quality to big data by highlighting how much complex is to define it in a general way. Already data quality is a multidimensional concept, difficult to characterize in precise definitions even in the case of well-structured data. Big data add two further dimensions of complexity: (i) being “very” source specific, and for this we adopt the interesting UNECE classification, and (ii) being highly unstructured and schema-less, often without golden standards to refer to or very difficult to access. After providing a tutorial on data quality in traditional contexts, we analyze big data by providing insights into the UNECE classification, and then, for each type of data source, we choose a specific instance of such a type (notably deep Web data, sensor-generated data, and Twitters/short texts) and discuss how quality dimensions can be defined in these cases. The overall aim of the paper is therefore to identify further research directions in the area of big data quality, by providing at the same time an up-to-date state of the art on data quality. © 2015, The Author(s)
From Data Quality to Big Data Quality
Full text linkThis article investigates the evolution of data quality issues from traditional structured data managed in relational databases to Big Data. In particular, the paper examines the nature of the relationship between Data Quality and several research coordinates that are relevant in Big Data, such as the variety of data types, data sources and application domains, focusing on maps, semi-structured texts, linked open data, sensor & sensor networks and official statistics. Consequently a set of structural characteristics is identified and a systematization of the a posteriori correlation between them and quality dimensions is provided. Finally, Big Data quality issues are considered in a conceptual framework suitable to map the evolution of the quality paradigm according to three core coordinates that are significant in the context of the Big Data phenomenon: the data type considered, the source of data, and the application domain. Thus, the framework allows ascertaining the relevant changes in data quality emerging with the Big Data phenomenon, through an integrative and theoretical literature review.CS
A similarity-based framework for service repository integration
No full textNowadays, repositories of services are becoming increasingly useful in the management of many public and private service provider organizations. In order to make a repository an integrated representation of all services delivered in an organization, a unified representation is desirable. Since several repositories of services, each potentially characterized by heterogeneous and conflicting representations, may coexist in the same organization or in cooperating organizations, the need for service repository integration techniques is emerging. In this paper, we investigate the problem of integrating heterogeneous service repositories. We first provide a conceptual model for describing services and semantic relationships among them. Then, we define a multi-level similarity function that is able to discover similarities between services belonging to different repositories, and to suggest candidate relationships among services. The proposed function combines a simple keyword-based matching with a more complex semantic matching that exploits the Explicit Semantic Analysis technique for generating a representation of services based on Wikipedia concepts. These combined techniques are implemented in the SCAn (Service Correspondence Analyzer) framework that supports the hunian expert during the repository integration process. The framework has been evaluated in a real-life scenario and the results demonstrate the effectiveness of the proposed approach
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