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Data intensive projects are inefficient since in science and industry it is known from surveys that 80 % of the time is wasted for data wrangling. We suffer from fragmentation at all levels from data organisation up to semantics which lets many data projects fail and prohibiits the participation of many researchers and companies. The concept of Digital Objects is now broadly accepted as a new level of commodity to overcome the fragmentation at data organisation level and to facilitate interoperability at other levels and to open the way to automatic processing which will be the only way to scale up data intensive work. The C2CAMP initiative as a GO FAIR implementation network is now working on specifying and implementing key components of a DO centric data infrastructure in close collaboration with the Research Data Alliance and organisations such as DONA and ITU.
\n\nFull abstract: https://doi.org/10.5281/zenodo.1310621
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Research Object publication, archiving and curation
Research Object creation and manipulation
Research Object exploration and visualization
Research Object evolution, derivation and provenance
Handling Big Data in Research Objects
Data Archive packaging and formats
Rich metadata of research data and software
Alignments with community efforts
Citation and attribution of research data and software
Annotation and peer review of research data
Distributed data publication (blockchain, nanopublication)
Driving adoption within current scholarly communications ecosystem
Research Object model domain extensions
Research Object granular access control approaches
Research Object social impact metrics
Self-contained executable Research Objects (i.e., including execution environment description)
Submissions must use an open license, if you are not sure use Creative Commons Attribution 4.0 (for text, figures, data, metadata) or Apache License 2.0 (for software, workflows, scripts).
", "description": "For and about Research Objects using the RO-Crate standard, classic RO ontologies and other related work on scholarly communication.", "organizations": [ { "id": "027m9bs27" }, { "id": "00rqy9422" } ], "page": "Scholarly Communication has evolved significantly in recent years, with an increasing focus on Open Research, data sharing and community-developed open source methods. The concepts of authorship and citation are changing, as researchers are increasingly reusing and evolving common software tools and datasets. Yet with a growing amount of cloud compute power and open platforms available, reproducibility of computational analyses becomes more challenging, and often overlooked in peer review. While recent advances in scientific workflows and provenance capture systems have improved on this situation, a question remains on how to publish, archive and explore digital research outputs, as academic authors and publishers remain focused on PDFs and the occasional CSV file, with the Web and Open Research often left to \"best effort\" rather than being the expected norm.
To this mean the community initiative Research Object (RO) have been proposed as a way to package and describe research outputs, data, methods, workflows, provenance and structured metadata, reusing existing Web standards and formats.