Open Science in practice 4S EASST conference Barcelona, Sept 1st 2016

Open Science (OS) is currently regarded as the next ‘big thing’ in European science policy and elsewhere. It is defined as science that is transparent, accountable, and shareable, involving the participation of (all) relevant stakeholders in the scientific process. In practice, tensions are emerging in how OS is enacted by scientific communities, science policy organisations, funding bodies, the publishing industry, and science-related institutions, with diverse uptakes of commons, knowledge sharing, democratisation of technology, participatory design, hacking etc.

This conference stream invited STS scholars to explore OS from an STS perspective and to discuss what STS can bring into the broader discussion of OS, e.g. by studying institutionalizations of OS, appropriations of OS within prevailing traditional images of science, or how OS is co-shaped by negotiation processes promoted by different stakeholders. Presentations covered socio-technical dimensions of openness in sciences - including the social sciences and humanities - in general and Open Access, Open Research Data, Open Methods, Open Education, Open Evaluation, and Citizen Science in particular.

(Session reports by chairs)

Open Cultures and Open Innovation

This blog entry contains an assignment for the seminar Open Science: The Better Science, teached by Prof. Katja Mayer at the Department for Science and Technology Studies, University of Vienna. (November, 2015).

By Daniel Marante

- Summarize the Open Innovation model as described by Chesbrough, and locate the role of universities and other public research organization in this model. Reflect briefly in one paragraph potential obstacles, challenges or benefits from this model.


The author highlights the bond between Open Science and Open Innovation. He argues that business is the answer to this gap that currently exists between both ends. He sustains that an entrepreneurial risk-taking model is needed to define the most promising application of science and knowledge. He argues, too, that an Open Science and Open Innovation sustainable model should be based on Mertonian Norms, where CUDOS principles rule the normative standard of action. In particular, Chesbrough argues that open source software, is leading to a “citizen science” era, in which scientific contribution can be truly made, fulfilling at the same time Mertonian principles. Examples of this are to be found in organizations such as CERN. But, the author argues that Open Science does not necessarily imply Open Innovation, because institutions that promote the former sometimes do not work to promote the latter. That is why, different incentives and contexts are needed, but this could be hard since applying knowledge can be ambiguous, involve making judgments and taking risks in unexplored domains. Thus, private sector stood up to undertake knowledge application (instead of basic research) and therefore a model of closed innovation was established.

But nowadays the scenario has changed. The author argues that universities are not only interested in creating knowledge, but in applying it. This has torn down knowledge application monopolies created by industry, while opening a broad way to a better distribution of valuable information. This is clear when looking at patent distribution statistics, where the percentage of patents attributed to individuals and small firms has been increased in comparison to the ones attributed to big players in the industry.

To capitalize this modern era, in terms of a systematic open innovation environment, the author states that abundant knowledge is a must within the model, so inflows and outflows of this knowledge, accelerate internal innovation and expand the markets of application. Such a model also should combine internal and external ideas into platforms and architectures, where business models define the requirements for these systems.

There are two models of open innovation: Outside-in, which involves opening up a company’s innovation process to external inputs (CERN embodies this model) and Inside- out, which are less popular and requires organizations to allow un-explored ideas to go outside the organizations for other to use in their businesses. Such a model would require incentives like collaboration through markets, exchange of knowledge, intellectual property rights and startup formation, that would integrate technologies together into solutions and new systems. Alongside, Universities should function, as the locus for the discoveries and basic research, but within the system is important to delegate the application phase to other experienced actors with business models in mind.

As the author mentions, I wonder how such a model, and particularly the commercialization of ideas issue, would cope with the pervasive for-profit behavior the industry has. How competitiveness would work under such a model. How would it be for consulting industry, for which knowledge is actually their product?


References:
Chesbrough, H. (2015). From Open Science to Open Innovation. Science Business Publishing. 

Science? Yes, we can!

Science? Yes, we can!

This slogan was not only used by “Bob the Builder” or Barak Obama during his campaign, it implicit describes a new way of science. Everyone is able to do research. Citizen Science is obviously a new trend in research and is used and communicated as new way of science. We all can participate and contribute to science; it is no longer a very exclusive activity of some nerds in white coats. Science is open to people like you and me. But, to be honestly, is this really a new thing? Is it just an invention of some creative marketing guys and a relatively easy approach to distract attention from major problems of science and society? The overall title of this currently very popular phenomenon “Citizen Science” is used for programs, strategic papers and much more. This blog article summarizes some aspects of a discussion a class of STS scholars had in December 2015. How can we classify Citizen Science contributions and what is missing? What are the drivers and what motivates to participate and which problems can occur? I will put some spots on these questions and give my opinion on some aspects.

Skills for opening science (incl. social sciences and humanities)

www.lumaxart.com/

From his keynote presentation at "Open Science Jetzt!" one particular quote by Daniel Mietchen is still sticking in my mind. He said that opening scientific practices means to learn how to have an eye on the other/s.

I think this is one of the most important skills or capacities we need to train from the beginning of higher education, if not earlier on. This is what Pierre Bourdieu and others called for by establishing a reflexive scientific practice. This is what feminist STS would label "strong objectivity" or recognition of "partial perspectives". Besides reflecting one's own habitus and standpoints, we should widen our attention to all sorts of potential perceptions and impacts of our research, in all phases of research.

Thus, how could this reflexive capacity be better trained if not through exercises in cooperation, maybe even in interdisciplinary collaboration? In order to establish a sensitivity towards one's own and other (epistemic) cultures, we need to learn how to open up without fear of exposure, we need to learn what can be opened and what not. Moreover - thinking of the scientific meritocracy - we need to set up a reward system for such practices and the gathering of such experiences.