Research and technology

Open Digital Science Study

27 Nov , 2015  

ODS is embedded in today’s context of scientific practices which are undergoing significant changes:3

  • Increased fragmentation: new stakeholders, new regions
  • Data-orientation
  • Application context, capitalisation of knowledge, entrepreneurial science
  • Cooperation: interdisciplinarity, citizens
  • Open data movement
  • Impact orientation: indicators, accountability, grand challenges
  • Internationalization
  • Innovation: open innovation
  • Re-contextualizing science: participatory turn, RRI, questioning science and anti-science, career path challenges

The synthesis of the arguments presented below may lead the reader to better understand what is and what is not ODS:

  • process of transforming (opening up/democratizing) science thanks to digital technologies.
  • intensive exchange environment of transparency (for transmit open knowledge to everybody) and participations Involving computers and brains at the same time, in real time. In this convergence, human focus on difficult tasks and automated tasks are left to the machines that need contents available and reachable. Some argue that ODS is semantics.

Currently it is expanding very rapidly and every day we see very exciting things. That is one of the reasons why there is no agreement on the terminology, even Open and Digital are concepts themselves with many meanings which are subject of epistemological discussions. ODS ecosystem is formed by elements of heterogeneous nature (such us technologies, practices, or players…) around topics with multiple layers, different origins and intentions. These new virtual spaces can be powerful digital infrastructures but also researchers blogs, online experiments, open labs, intranets, virtual research environments or social networks (like Researchgate or even Facebook). It is pertinent to mention that several experts highlighted that EU commission gives some clues, some explicitly mentioned the definition presented in the Digital Science concept paper.

Regarding what is not ODS, discussions came more practical and less theoretical regarding issues like accesibility, ownership, engagement of social actors or the actual capacity of building up or disseminating any knowledge. Scientists don’t produce good ODS outputs yet. Published results may be complete, and understandable by both humans and machines allowing to see the real outcomes and the whole workflow. Examples of bad practices are articles who nobody read or analogue papers digitalized, also hybrid proprietary models. Other important topic are the social factors are not involved or are mere subjects without opinion.

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