Data DNA: The Next Generation of Statistical Metadata

Describes the components of a complete statistical metadata system and suggests ways to create and structure metadata for better access and understanding of data sets by diverse users

Adding Value to Statistics in the Data Revolution Age

As many statistical offices in accordance with the European Statistical System commitment to Vision 2020, since the second half of 2014 Istat has implemented its internal standardisation and industrialisation process within the framework of a common Business Architecture. Istat modernisation programme aims at building services and infrastructures within a plug-and-play framework to foster innovation, promote reuse and move towards full integration and interoperability of statistical process, consistent with a service-oriented architecture. This is expected to lead to higher effectiveness and productivity by improving the quality of statistical information and reducing the response burden. This paper addresses the strategy adopted by Istat which is focused on exploiting administrative data and new data sources in order to achieve its key goals enhancing value to users. The strategy is based on some priorities that consider services centred on users and stakeholders as well as Linked Open Data, to allow Machine-to-Machine data and metadata integration through definition of common statistical ontologies and semantics

e-Science Infrastructure for the Social Sciences

When the term „e-Science“ became popular, it frequently was referred to as “enhanced science” or “electronic science”. More telling is the definition ‘e-Science is about global collaboration in key areas of science and the next generation of infrastructure that will enable it’ (Taylor, 2001). The question arises to what extent can the social sciences profit from recent developments in e- Science infrastructure? While computing, storage and network capacities so far were sufficient to accommodate and access social science data bases, new capacities and technologies support new types of research, e.g. linking and analysing transactional or audio-visual data. Increasingly collaborative working by researchers in distributed networks is efficiently supported and new resources are available for e-learning. Whether these new developments become transformative or just helpful will very much depend on whether their full potential is recognized and creatively integrated into new research designs by theoretically innovative scientists. Progress in e-Science was very much linked to the vision of the Grid as “a software infrastructure that enables flexible, secure, coordinated resource sharing among dynamic collections of individuals, institutions and resources’ and virtually unlimited computing capacities (Foster et al. 2000). In the Social Sciences there has been considerable progress in using modern IT- technologies for multilingual access to virtual distributed research databases across Europe and beyond (e.g. NESSTAR, CESSDA – Portal), data portals for access to statistical offices and for linking access to data, literature, project, expert and other data bases (e.g. Digital Libraries, VASCODA/SOWIPORT). Whether future developments will need GRID enabling of social science databases or can be further developed using WEB 2.0 support is currently an open question. The challenges here are seamless integration and interoperability of data bases, a requirement that is also stipulated by internationalisation and trans-disciplinary research. This goes along with the need for standards and harmonisation of data and metadata. Progress powered by e- infrastructure is, among others, dependent on regulatory frameworks and human capital well trained in both, data science and research methods. It is also dependent on sufficient critical mass of the institutional infrastructure to efficiently support a dynamic research community that wants to “take the lead without catching up”.

Applied Research Through Partnership: the Experience of the Yorkshire and Humberside Regional Research Observatory

Paper presented at a seminar on ‘Los Observatorios Regionales de Políticas Públicas como Herramientas de Gestión de Información: Una Aproximación al Estudio del Rendimiento Autonómico, at the Centro de Estudios de Gestión, Análisis y Información, Campus de Somosaguas, La Universidad Complutense, Madrid, 23-24 November, 2000 Ten years ago, a Regional Research Observatory (ReRO) was established to provide ‘clients’ in Yorkshire and Humberside with a single point access to a region-wide data and analysis service. The Observatory’s portfolio covered activities relating to applied research and consultancy, intelligence, education and training, publications and networking. The first part of the paper explains the concept of the Observatory as it was initially conceived as a form of partnership across all the universities in the region, outlines the structure of the organization that was created, explains the arrangements for operating the Observatory as a partnership initiative, and exemplifies the outputs and achievements during the first half of the decade. In order to facilitate its regional monitoring activities, ReRO constructed a Regional Intelligence Centre (RIC), a customised geographical information system in which to store key data sets and generate a range of statistical indicators for the region as a whole or its constituent parts. The second part of the paper explains the structure of the RIC and its contents. It argues that the main advantage that derives from the construction of such a centre is the value that is added to raw information through data handling and integration, through skilled interpretation and through the provision of new information, maybe in the form of forecasts of what is likely to happen in the future, as well as analyses of what has happened in the past. The third and final part of the paper explores some of the key issues and difficulties relating to the operation of the Observatory and considers some of the reasons that have accounted for its loss of momentum in the last few years. This has occurred over a period of increased political attention to regional administration and planning in the UK, exemplified by the creation of Scottish and Welsh Assemblies and the emergence of Regional Development Agencies and Regional Assemblies across England. A retrospective evaluation demonstrates a number of lessons that have been learnt and provides a number of useful guidelines to those attempting to establish similar structures elsewhere in the developed world

Access to and Documentation of Publicly Financed Survey Data

The topic of this paper is access to and documentation of survey data financed through public funds. We distinguish between four types of publicly financed survey data: (1) Academic survey data from the national or international research infrastructures; (2) data from DFG projects or similarly funded projects; (3) survey data collected in research projects funded by the Federal State and the Länder (Ressortforschung); (4) Population and Household surveys from national and international statistical agencies. For each of these types of data we describe the current situation and present recommendations for future developments.Survey data, data access, data documentation, data archive

Searching Data: A Review of Observational Data Retrieval Practices in Selected Disciplines

A cross-disciplinary examination of the user behaviours involved in seeking and evaluating data is surprisingly absent from the research data discussion. This review explores the data retrieval literature to identify commonalities in how users search for and evaluate observational research data. Two analytical frameworks rooted in information retrieval and science technology studies are used to identify key similarities in practices as a first step toward developing a model describing data retrieval

An Exploratory Sequential Mixed Methods Approach to Understanding Researchers’ Data Management Practices at UVM: Integrated Findings to Develop Research Data Services

This article reports on the integrated findings of an exploratory sequential mixed methods research design aimed to understand data management behaviors and challenges of faculty at the University of Vermont (UVM) in order to develop relevant research data services. The exploratory sequential mixed methods design is characterized by an initial qualitative phase of data collection and analysis, followed by a phase of quantitative data collection and analysis, with a final phase of integration or linking of data from the two separate strands of data. A joint display was used to integrate data focused on the three primary research questions: How do faculty at UVM manage their research data, in particular how do they share and preserve data in the long-term?; What challenges or barriers do UVM faculty face in effectively managing their research data?; and What institutional data management support or services are UVM faculty interested in? As a result of the analysis, this study suggests four major areas of research data services for UVM to address: infrastructure, metadata, data analysis and statistical support, and informational research data services. The implementation of these potential areas of research data services is underscored by the need for cross-campus collaboration and support

Developing a GIS-Database and Risk Index for Potentially Polluting Marine Sites

The increasing availability of geospatial marine data provides an opportunity for hydrographic offices to contribute to the identification of “Potentially Polluting Marine Sites” (PPMS). These include shipwrecks, oil rigs, pipelines, and dumping areas. To adequately assess the environmental risk of these sites, relevant information must be collected and converted into a multi-scale geodatabase suitable for site inventory and geo-spatial analysis. In addition, a Risk Index – representing an assessment of the magnitude of risk associated with any site – can be derived to determine the potential impacts of these PPMS. However, the successful collection and integration of PPMS information requires some effort to ‘normalize’ and standardize the data based on recognized international standards. In particular, there is benefit in structuring the data in conformance with the Universal Hydrographic Data Model (IHO S-100) recently adopted by the International Hydrographic Organization. In this paper, an S-100 compliant product specification for a PPMS geo-spatial database and associated Marine Site Risk Index is proposed which can be used by national hydrographic offices and marine protection agencies

Km4City Ontology Building vs Data Harvesting and Cleaning for Smart-city Services

Presently, a very large number of public and private data sets are available from local governments. In most cases, they are not semantically interoperable and a huge human effort would be needed to create integrated ontologies and knowledge base for smart city. Smart City ontology is not yet standardized, and a lot of research work is needed to identify models that can easily support the data reconciliation, the management of the complexity, to allow the data reasoning. In this paper, a system for data ingestion and reconciliation of smart cities related aspects as road graph, services available on the roads, traffic sensors etc., is proposed. The system allows managing a big data volume of data coming from a variety of sources considering both static and dynamic data. These data are mapped to a smart-city ontology, called KM4City (Knowledge Model for City), and stored into an RDF-Store where they are available for applications via SPARQL queries to provide new services to the users via specific applications of public administration and enterprises. The paper presents the process adopted to produce the ontology and the big data architecture for the knowledge base feeding on the basis of open and private data, and the mechanisms adopted for the data verification, reconciliation and validation. Some examples about the possible usage of the coherent big data knowledge base produced are also offered and are accessible from the RDF-Store and related services. The article also presented the work performed about reconciliation algorithms and their comparative assessment and selection