Why linked data is not enough for scientists

Bechhofer, Sean; Buchan, Iain; Roure, David De; Missier, Paolo; Ainsworth, John; Bhagat, Jiten; Couch, Philip; Cruickshank, Don; Delderfield, Mark; Dunlop, Ian; Gamble, Matthew; Michaelides, Danius T.; Owen, Stuart; Newman, David; Sufi, Shoaib; Goble, Carole

doi:10.1016/j.future.2011.08.004

Cited by 271 publications

(177 citation statements)

References 21 publications

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“…Data sharing is a condition for enabling data discovery and data reuse, as well as one of the main factors for the success of the Linked Data paradigm in the scientific context. To this end, Bechhofer et al (2013) highlighted that Linked Data is a compelling approach for sharing and disseminating scientific data, but in order to be effective for data reuse and discovery it has to be connected to the research methodology and respect the rights and the reputation of the researchers. 5.…”

Section: Why Data Citation: Motivationsmentioning

confidence: 99%

Theory and practice of data citation

Silvello

2017

Asso for Info Science & Tech

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Citations are the cornerstone of knowledge propagation and the primary means of assessing the quality of research, as well as directing investments in science. Science is increasingly becoming "data-intensive," where large volumes of data are collected and analyzed to discover complex patterns through simulations and experiments, and most scientific reference works have been replaced by online curated data sets. Yet, given a data set, there is no quantitative, consistent, and established way of knowing how it has been used over time, who contributed to its curation, what results have been yielded, or what value it has. The development of a theory and practice of data citation is fundamental for considering data as first-class research objects with the same relevance and centrality of traditional scientific products. Many works in recent years have discussed data citation from different viewpoints: illustrating why data citation is needed, defining the principles and outlining recommendations for data citation systems, and providing computational methods for addressing specific issues of data citation. The current panorama is many-faceted and an overall view that brings together diverse aspects of this topic is still missing. Therefore, this paper aims to describe the lay of the land for data citation, both from the theoretical (the why and what) and the practical (the how) angle.

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Section: Why Data Citation: Motivationsmentioning

confidence: 99%

Theory and practice of data citation

Silvello

2017

Asso for Info Science & Tech

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“…These allow users to share publications and data and provide social networking features but do not provide an execution environment. Research Objects proposed by Bechhofer et al (2013) are containers which aggregate essential information relating to scientific experiments including data and metadata describing the methods used to produce and analyse the data and the people involved in the investigation. They can be used in conjunction with the myExperiment website (Goble et al, 2010).…”

Section: Background and Overviewmentioning

confidence: 99%

A Digital Repository and Execution Platform for Interactive Scholarly Publications in Neuroscience

et al. 2015

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Abstract:The CARMEN Virtual Laboratory (VL) is a cloud-based platform which allows neuroscientists to store, share, develop, execute, reproduce and publicise their work. This paper describes new functionality in the CARMEN VL: an interactive publications repository. This new facility allows users to link data and software to publications. This enables other users to examine data and software associated with the publication and execute the associated software within the VL using the same data as the authors used in the publication. The cloud-based architecture and SaaS (Software as a Service) framework allows vast data sets to be uploaded and analysed using software services. Thus, this new interactive publications facility allows others to build on research results through reuse. This aligns with recent developments by funding agencies, institutions, and publishers with a move to open access research. Open access provides reproducibility and verification of research resources and results. Publications and their associated data and software will be assured of long-term preservation and curation in the repository. Further, analysing research data and the evaluations described in publications frequently requires a number of execution stages many of which are iterative. The VL provides a scientific workflow environment to combine software services into a processing tree. These workflows can also be associated with publications and executed by users. The VL also provides a secure environment where users can decide the access rights for each resource to ensure copyright and privacy restrictions are met.

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“…With the rapid developments of e-Science, the possibility of making interactive digital publications with more comprehensive information embedded within them has attracted interest from both academics and science publishers [4]. Bechhofer et al [5] proposed the notion of Research Object (RO), which is defined as an aggregation of essential resources and information relating to experiments and investigations that helps other people to reproduce and reuse research results. One of the key motivations of such RO notion is its potential in supporting "rich publication".…”

Section: Related Workmentioning

confidence: 99%