We’re looking for a model that enables us to describe the changes in the research process brought by Science.2.0. First, we have proposed division between open science, citizen science and data-intensive science.
Now, we have focused on the research cycle trying to capture different applications on different stages of research process. The inner cycle on the diagram below represents stages of the research process from the conceptualisation to the publication of a peer-reviewed article.
In the science.2.0 model the openness, principles of sharing and collaboration are (can be) present on every stage of the research process whereas in the traditional model, only result that is shared is the peer-reviewed article (often behind a paywall).
At the conceptualisation stage open discussions around ideas (blogs, fora) and knowledge sharing is important (open annotation, open bibliographies). Subsequently we have the stage of gathering data where data and research praxis can be shared in real-time (open data, open lab notebooks) and gathered in collaboration with citizens. In order to deposit data to enable further analysis we need eInfrastructures. Also in many instances the data can be analysed with the help of volunteers (citizen science) and open collaboration (collaborative analysis) . The analysis of data can be facilitated by sharing the open software. The outcome of analysis can be published as an article or a book chapter (which can be updated in an instance – liquid publications) but also as a statement accompanied with metadata that is linked with other statements (nanopublications). The article can be published in an open access journal or submitted to an institutional repository allowing wider accessibility. Data can be published and linked to the article. Finally, publications are subject of the review by the academic community to establish the importance of the findings and filter the increasing number of scientific literature according to their relevance and significance for the field. Publications can be opened to post-peer reviews when the community openly discusses the importance of the discovery. Also other reputation systems, distinct from peer-review can be used to measure scientific excellence and author/publication impact (e.g. altmetrics).
What’s missing in our diagram? What should be added/changed in order to better capture the Science2.0 phenomenon?