Software preservation has not had detailed consideration as a research topic or in practical application. In this paper, we present a conceptual framework to capture and organise the main notions of software preservation, which are required for a coherent and comprehensive approach. This framework has three main aspects. Firstly a discussion of what it means to preserve software via a performance model which considers how a software artefact can be rebuilt from preserved components and can then be seen to be representative of the original software product. Secondly the development of a model of software artefacts, describing the basic components of all software, loosely based on the FRBR model for representing digital artefacts and their history within a library context. Finally, the definition and categorisation of the properties of software artefacts which are required to ensure that the software product has been adequately preserved. These are broken down into a number of categories and related to the concepts defined in the OAIS standard. We also discuss our experience of recording these preservation properties for a number of BADC software products, which arose from a series of case studies conducted to evaluate the software preservation framework, and also briefly describe the SPEQS toolkit, a tool to capture software preservation properties within a software development.
SOA (Service Oriented Architecture), workflow, the Semantic Web, and Grid computing are key enabling information technologies in the development of increasingly sophisticated e-Science infrastructures and application platforms. While the emergence of Cloud computing as a new computing paradigm has provided new directions and opportunities for e-Science infrastructure development, it also presents some challenges. Scientific research is increasingly finding that it is difficult to handle "big data" using traditional data processing techniques. Such challenges demonstrate the need for a comprehensive analysis on using the above mentioned informatics techniques to develop appropriate e-Science infrastructure and platforms in the context of Cloud computing. This survey paper describes recent research advances in applying informatics techniques to facilitate scientific research particularly from the Cloud computing perspective. Our particular contributions include identifying associated research challenges and opportunities, presenting lessons learned, and describing our future vision for applying Cloud computing to e-Science. We believe our research findings can help indicate the future trend of e-Science, and can inform funding and research directions in how to more appropriately employ computing technologies in scientific research. We point out the open research issues hoping to spark new development and innovation in the e-Science field.
Traditionally, the formal scientific output in most fields of natural science has been limited to peer-reviewed academic journal publications, with less attention paid to the chain of intermediate data results and their associated metadata, including provenance. In effect, this has constrained the representation and verification of the data provenance to the confines of the related publications. Detailed knowledge of a dataset’s provenance is essential to establish the pedigree of the data for its effective re-use, and to avoid redundant re-enactment of the experiment or computation involved. It is increasingly important for open-access data to determine their authenticity and quality, especially considering the growing volumes of datasets appearing in the public domain. To address these issues, we present an approach that combines the Digital Object Identifier (DOI) – a widely adopted citation technique – with existing, widely adopted climate science data standards to formally publish detailed provenance of a climate research dataset as an associated scientific workflow. This is integrated with linked-data compliant data re-use standards (e.g. OAI-ORE) to enable a seamless link between a publication and the complete trail of lineage of the corresponding dataset, including the dataset itself.
Past data management practices in many fields of natural science, including climate research, have focused primarily on the final research output -the research publication -with less attention paid to the chain of intermediate data results and their associated metadata, including provenance. Data were often regarded merely as an adjunct to the publication, rather than a scientific resource in their own right. In this paper, we attempt to address the issues of capturing and publishing detailed workflows associated with the climate/research datasets held by the Climatic Research Unit (CRU) at the University of East Anglia. To this end, we present a customisable approach to exposing climate research workflows for the effective re-use of the associated data, through the adoption of linked-data principles, existing widely adopted citation techniques (Digital Object Identifier) and data exchange mechanisms (Open Archives Initiative Object Reuse and Exchange).
Over the past decade, Qatar has been making considerable progress towards developing a sustainable research culture for the nation. The main driver behind Qatar’s progress in research and innovation is Qatar Foundation for Education, Science, and Community Development (QF), a private, non-profit organization that aims to utilise research as a catalyst for expanding, diversifying and improving the country’s economy, health and environment. While this has resulted in a significant growth in the number of research publications produced by Qatari researchers in recent years, a nationally co-ordinated approach is needed to address some of the emerging but increasingly important aspects of research data curation, such as management and publication of research data as important outputs, and their long-term digital preservation. Qatar National Library (QNL), launched in November 2012 under the umbrella of QF, aims to establish itself as a centre of excellence in Qatar for research data management, curation and publishing to address the research data-related needs of Qatari researchers and academics. This paper describes QNL’s approach towards establishing a national research data curation service for Qatar, highlighting the associated opportunities and key challenges.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.