To share or not to share: Publication and quality assurance of research data outputs. A report commissioned by the Research Information Network

A study on current practices with respect to data creation, use, sharing and publication in eight research disciplines (systems biology, genomics, astronomy, chemical crystallography, rural economy and land use, classics, climate science and social and public health science). The study looked at data creation and care, motivations for sharing data, discovery, access and usability of datasets and quality assurance of data in each discipline

Design of the shared Environmental Information System (SEIS) and development of a web-based GIS interface

Chapter 5The Shared Environmental Information System (SEIS) is a collaborative initiative of the European Commission (EC) and the European Environment Agency (EEA) aimed to establish an integrated and shared EU-wide environmental information system together with the Member States. SEIS presents the European vision on environmental information interoperability. It is a set of high-level principles & workflow-processes that organize the collection, exchange, and use of environmental data & information aimed to: • Modernise the way in which information required by environmental legislation is made available to member states or EC instruments; • Streamline reporting processes and repeal overlaps or obsolete reporting obligations; • Stimulate similar developments at international conventions; • Standardise according to INSPIRE when possible; and • Introduce the SDI (spatial database infrastructure) principle EU-wide. SEIS is a system and workflow of operations that offers technical capabilities geared to meet concept expectations. In that respect, SEIS shows the way and sets up the workflow effectively in a standardise way (e.g, INSPIRE) to: • Collect Data from Spatial Databases, in situ sensors, statistical databases, earth observation readings (e.g., EOS, GMES), marine observation using standard data transfer protocols (ODBC, SOS, ft p, etc). • Harmonise collected data (including data check/data integrity) according to best practices proven to perform well, according to the INSPIRE Directive 2007/2/EC (1) Annexes I: II: III: plus INSPIRE Implementation Rules for data not specified in above mentioned Annexes. • Harmonise collected data according to WISE (Water Information System from Europe) or Ozone-web. • Process, aggregate harmonise data so to extract information in a format understandable by wider audiences (e.g., Eurostat, enviro-indicators). • Document information to fulfi l national reporting obligations towards EU bodies (e.g., the JRC, EEA, DGENV, Eurostat) • Store and publish information for authorised end-users (e.g., citizens, institutions). This paper presents the development and integration of the SEIS-Malta Geoportal. The first section outlines EU Regulations on INSPIRE and Aarhus Directives. The second covers the architecture and the implementation of SEIS-Malta Geoportal. The third discusses the results and successful implementation of the Geoportal.peer-reviewe

Design and Evaluation of a Collective IO Model for Loosely Coupled Petascale Programming

Loosely coupled programming is a powerful paradigm for rapidly creating higher-level applications from scientific programs on petascale systems, typically using scripting languages. This paradigm is a form of many-task computing (MTC) which focuses on the passing of data between programs as ordinary files rather than messages. While it has the significant benefits of decoupling producer and consumer and allowing existing application programs to be executed in parallel with no recoding, its typical implementation using shared file systems places a high performance burden on the overall system and on the user who will analyze and consume the downstream data. Previous efforts have achieved great speedups with loosely coupled programs, but have done so with careful manual tuning of all shared file system access. In this work, we evaluate a prototype collective IO model for file-based MTC. The model enables efficient and easy distribution of input data files to computing nodes and gathering of output results from them. It eliminates the need for such manual tuning and makes the programming of large-scale clusters using a loosely coupled model easier. Our approach, inspired by in-memory approaches to collective operations for parallel programming, builds on fast local file systems to provide high-speed local file caches for parallel scripts, uses a broadcast approach to handle distribution of common input data, and uses efficient scatter/gather and caching techniques for input and output. We describe the design of the prototype model, its implementation on the Blue Gene/P supercomputer, and present preliminary measurements of its performance on synthetic benchmarks and on a large-scale molecular dynamics application.Comment: IEEE Many-Task Computing on Grids and Supercomputers (MTAGS08) 200

Benefits and challenges of applying Semantic Web Services in the e-Government domain

Joining up services in e-Government usually implies governmental agencies acting in concert without a central control regime. This requires the sharing of scattered and heterogeneous data. Semantic Web Service (SWS) technology can help to integrate, mediate and reason between these datasets. However, since few real-world applications have been developed, it is still unclear which are the actual benefits and issues of adopting such a technology in the e-Government domain. In this paper, we contribute to raising awareness of the potential benefits in the e-Government community by analyzing motivations, requirements, and expected results, before proposing a reusable SWS-based framework. We demonstrate the application of this framework by a compelling use case: a GIS-based emergency planning system. We illustrate the obtained benefits and the key challenges which remain to be addressed

Illinois Digital Scholarship: Preserving and Accessing the Digital Past, Present, and Future

Since the University's establishment in 1867, its scholarly output has been issued primarily in print, and the University Library and Archives have been readily able to collect, preserve, and to provide access to that output. Today, technological, economic, political and social forces are buffeting all means of scholarly communication. Scholars, academic institutions and publishers are engaged in debate about the impact of digital scholarship and open access publishing on the promotion and tenure process. The upsurge in digital scholarship affects many aspects of the academic enterprise, including how we record, evaluate, preserve, organize and disseminate scholarly work. The result has left the Library with no ready means by which to archive digitally produced publications, reports, presentations, and learning objects, much of which cannot be adequately represented in print form. In this incredibly fluid environment of digital scholarship, the critical question of how we will collect, preserve, and manage access to this important part of the University scholarly record demands a rational and forward-looking plan - one that includes perspectives from diverse scholarly disciplines, incorporates significant research breakthroughs in information science and computer science, and makes effective projections for future integration within the Library and computing services as a part of the campus infrastructure.Prepared jointly by the University of Illinois Library and CITES at the University of Illinois at Urbana-Champaig