Frontiers | Open Science for private Interests? How the Logic of Open Science Contributes to the Commercialization of Research | Research Metrics and Analytics

Abstract:  Financial conflicts of interest, several cases of scientific fraud, and research limitations from strong intellectual property laws have all led to questioning the epistemic and social justice appropriateness of industry-funded research. At first sight, the ideal of Open Science, which promotes transparency, sharing, collaboration, and accountability, seems to target precisely the type of limitations uncovered in commercially-driven research. The Open Science movement, however, has primarily focused on publicly funded research, has actively encouraged liaisons with the private sector, and has also created new strategies for commercializing science. As a consequence, I argue that Open Science ends up contributing to the commercialization of science, instead of overcoming its limitations. I use the examples of research publications and citizen science to illustrate this point. Accordingly, the asymmetry between private and public science, present in the current plea to open science, ends up compromising the values of transparency, democracy, and accountability. | open and citizen science – active learning approaches – higher education


Learn about the social impact of Universities as knowledge creation, sharing and (re-) use ecosystems in the digital economy. Our report on this topic will identify how universities can better meet demand for civic engagement, public participation and societal impact.
Find out when we publish our learning-design framework: a guide for designing open and citizen science activities in a pedagogically sound way.
Join one of our 12 Open Knowledge events. Through datathons, service jams, Dotmocracy workshops, knowledge cafés and other formats, we’ll teach academic and library staff and students about contemporary trends in open and citizen science.
Come innovate with us! We’ll connect open and citizen science with innovation inside and outside universities through eight events, including hackathons, fablabs, game labs, innovation sprints and Futurefactories.
Upgrade your university’s curriculum. We’re supporting universities to include open and citizen science in teaching practices by creating teaching, learning and training resources based on active learning….”

INOS Workshop Outcomes – Open and Citizen Science in Higher Education: Co-Creating a Shared Vision  – LIBER Europe

“On the 16th of March 2021, we held the first of our two-part vision-building workshop series titled ‘Open and Citizen Science in Higher Education: Co-Creating a Shared Vision’. The workshop was designed to inspire participants to think systematically, share their experiences, challenges, and to jointly find solutions to the commonly identified obstacles when it comes to implementing Open and Citizen Science. 37 staff/faculty members and students from libraries and universities attended and discussed citizen science practices at their institutions and how these practices could be possibly adopted to serve as models practices for other Higher Education Institutions (HEI). …”

Citizen science is booming during the Covid-19 pandemic – Vox

“The pandemic has driven a huge increase in participation in citizen science, where people without specialized training collect data out in the world or perform simple analyses of data online to help out scientists.

Stuck at home with time on their hands, millions of amateurs around the world are gathering information on everything from birds to plants to Covid-19 at the request of institutional researchers. And while quarantine is mostly a nightmare for us, it’s been a great accelerant for science….”

University approaches to Citizen Science in the transition to Open Science – Institutional opportunities and challenges for creating an open and inclusive environment for Research – OpenAIRE Blog

“EUA and OpenAIRE organized the two-day, online workshop “University approaches to Citizen Science in the transition to Open Science” on December 9th and 10th. It provided a place to discuss Citizen Science in an era of Open Science (OS) and showcased a range of Citizen Science (SC) projects combining the two movements. A particular focus was on support and opportunities for CS in universities and institutions, with ample attention to the analysis of current practice and the challenges for institutions and projects….”

Transparency and secrecy in citizen science: Lessons from herping – ScienceDirect

Abstract:  In this paper I will outline a worry that citizen science can promote a kind of transparency that is harmful. I argue for the value of secrecy in citizen science. My argument will consist of analysis of a particular community (herpers), a particular citizen science platform (iNaturalist, drawing contrasts with other platforms), and my own travels in citizen science. I aim to avoid a simple distinction between science versus non-science, and instead analyze herping as a rich practice [MacIntyre, 2007]. Herping exemplifies citizen science as functioning simultaneously within and outside the sphere of science. I show that herpers have developed communal systems of transmitting and protecting knowledge. Ethical concerns about secrecy are inherently linked to these systems of knowledge. My over-arching aim is to urge caution in the drive to transparency, as the concepts of transparency and secrecy merit close scrutiny. The concerns I raise are complementary to those suggested by previous philosophical work, and (I argue) resist straightforward solutions.


The rise of citizen science: can the public help solve our biggest problems? | Universities | The Guardian

“For instance, in Kenya, University College London (UCL) scientists and their local partners are working with the Maasai to protect their environment against the climate crisis.

The researchers are co-developing a smartphone app that will help the community map the location of vital medicinal plant species and, as a result, better manage them. The app will allow the Maasai to upload the location of the plants, analyse the results and display them using icons like a thumbs up, an ant, and a red no entry sign next to invasive species, as well as pictures of the plants they want to protect….

Despite its obvious merits, citizen science still faces challenges. Researchers have a reputation for arriving in a community, exploiting it for data, and leaving it without giving any credit for its contribution….

In the end, citizen science is about shifting power from scientists to the public. A new £1.3m project called Engaging Environments led by the University of Reading, which is running in its own city as well as Birmingham and Newcastle, aims to do just that by training researchers to work with a wide range of communities to address their concerns about issues like pollution, climate change and air quality. This might be through getting sixth formers to monitor wildlife, or mosques encouraging their congregation to develop environmentally friendly practices such as avoiding single-use plastics during festivals.

This project is needed because of the social divide that exists between the public and many scientists. …

It doesn’t benefit scientists to isolate themselves from the public, either….”

citizenscience, Twitter, 11/5/2020 4:27:37 AM, 239488

“The graph represents a network of 3,914 Twitter users whose tweets in the requested range contained “citizenscience”, or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Thursday, 05 November 2020 at 04:07 UTC.

The requested start date was Thursday, 05 November 2020 at 01:01 UTC and the maximum number of days (going backward) was 14.

The maximum number of tweets collected was 7,500.

The tweets in the network were tweeted over the 13-day, 18-hour, 29-minute period from Thursday, 22 October 2020 at 01:42 UTC to Wednesday, 04 November 2020 at 20:11 UTC.

Additional tweets that were mentioned in this data set were also collected from prior time periods. These tweets may expand the complete time period of the data.

There is an edge for each “replies-to” relationship in a tweet, an edge for each “mentions” relationship in a tweet, and a self-loop edge for each tweet that is not a “replies-to” or “mentions”.

The graph is directed.

The graph’s vertices were grouped by cluster using the Clauset-Newman-Moore cluster algorithm.

The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm….”