Free software/free science | Kelty | First Monday

Over the last few years, as the Open Source/Free Software movement has become a constant in the business and technology press, generating conferences, spawning academic investigations and business ventures alike, one single question seems to have beguiled nearly everyone: “how do you make money with free software?”

If the question isn’t answered with a business plan, it is inevitably directed towards some notion of “reputation”. The answer goes: Free Software programmers do what they love, for whatever reason, and if they do it well enough they gain a reputation for being a good coder, or at least a loud one. Throughout the discussions, reputation functions as a kind of metaphorical substitute for money – it can spill over into real economies, be converted via better jobs or consulting gigs, or be used to make decisions about software projects or influence other coders. Like money, it is a form of remuneration for work done, where the work done is measured solely by the individual, each person his or her own price for creating something. Unlike money, however, it is also often seen as a kind of property. Reputation is communicated by naming, and the names that count are those of software projects and the people who contribute to them. This sits uneasily beside the knowledge that free software is in fact a kind of real (or legal) property (i.e. copyrighted intellectual property). The existence of free software relies on intellectual property and licensing law (Kelty, forthcoming; Lessig, 1999).

In considering the issue, most commentators seem to have been led rather directly to similar questions about the sciences. After all, this economy of reputation sounds extraordinairily familiar to most participants [1]. In particular two claims are often made: 1) That free software is somehow ‘like’ science, and therefore good; and, 2) That free software is – like science – a well-functioning ‘gift economy’ (a form of meta-market with its own currency) and that the currency of payment in this economy is reputation. These claims usually serve the purpose of countering the assumption that nothing good can come of system where individuals are not paid to produce. The assumption it hides is that science is naturally and essentially an open process – one in which truth always prevails.

The balance of this paper examines these claims, first through a brief tour of some works in the history and social study of science that have encountered remarkably similar problems, and second by comparing the two realms with respect to their “currencies” and “intellectual property” both metaphorical and actual….”

The Future of Science | Michael Nielsen

“We should aim to create an open scientific culture where as much information as possible is moved out of people’s heads and labs, onto the network, and into tools which can help us structure and filter the information. This means everything – data, scientific opinions, questions, ideas, folk knowledge, workflows, and everything else – the works. Information not on the network can’t do any good….”

The African Open Science Platform: The Future of Science and Science for the Future

“The challenge for Africa. National science systems worldwide are struggling to adapt to this new paradigm. The alternatives are to do so or risk stagnating in a scientific backwater, isolated from creative streams of social, cultural and economic opportunity. Africa should adapt, but in its own way, and as a leader not a follower, with its own broader, more societally-engaged priorities. It should seize the challenge with boldness and resolution by creating an African Open Science Platform, with the potential to be a powerful lever of social, cultural and scientific vitality and of economic development.

The African Open Science Platform. The Platform’s mission is to put African scientists at the cutting edge of contemporary, data-intensive science as a fundamental resource for a modern society. Its building blocks are:

? a federated hardware, communications and software infrastructure, including policies and enabling practices to support open science in the digital era;

? a network of excellence in open science that supports scientists and other societal actors in accumulating and using modern data resources to maximise scientific, social and economic benefit.

These objectives will be realised through six related strands of activity:

Strand 1: A federated network of computational facilities and services.

Strand 2: Software tools and advice on policies and practices of research data management.

Strand 3: A Data Science and AI Institute at the cutting edge of data analytics.

Strand 4: Priority application programmes: e.g. cities, disease, biosphere, agriculture.

Strand 5: A Network for Education and Skills in data and information.

Strand 6: A Network for Open Science Access and Dialogue.

The document also outlines the proposed governance, membership and management structure of the Platform, the approach to initial funding, immediate priorities and targets for 3-5 year horizons.”

Open Access—or Open Science? | The EMBO Journal

“Open Access mandates in Europe raise the question if the priority is to reduce publishing costs, or the overdue conversion to Open Science communication. At risk are not only high?quality journals, but also community institutions and international research collaboration….”

DORA, Plan S and the (open) future of research evaluation

“Slides from a talk [by Stephen Curry] given to the general assembly of Science Europe in Brussels on 22 Nov 2018. Gives an overview of the problems of over-metricised research evaluation and how this might be tackled, in part through initiatives driven by DORA, and how they are linked with drives such as Plan S to promote open science….”

Socializing Infrastructures #infraQA

“These are some of the questions that GenR has been formulating to explore how Open Science infrastructures can become ‘the new normal’….


  1. What are the forms of governance, ownership, coordination, and communication needed for Open Science infrastructures?
  2. What tools and infrastructures available at hand to researchers now will become part of the new systems?
  3. What are the skills and practices needed by researchers, that can be passed onto colleagues and follower that will enable sustainability? (Hammitzsch and Wächter 2015)
  4. What is meant by ‘software as infrastructure’ and what impact will the adoption of the idea have on science and scholarly practices, and quality and types of research results?
  5. What are the business and economic models, and economic impacts of new formulations of systems guided by the ideas of ‘Socializing Infrastructures’? And what can be learned from other sectors such as the push back against the commercial sharing economy platforms of the likes of Uber, or Airbnb, such as in the movement of Platform Cooperativism to provide an alternative model to Platform Capitalism? (Scholz 2016) (Scholz and Schneider 2017)
  6. What can speed up the pace of change in moving to Open Science infrastructures? Is it: scholarly activism; technological changes and practices, like automation and ‘Infrastructure-as-code’ reducing costs and increasing development cycles; or/and mandates and policies; or government nationalization and/or big investment; new skills and practices; or better communications?
  7. What’s missing in infrastructures? What are ‘the known unknowns’, and how do we find ‘the unknown, unknowns’? (Rumsfeld 1992)
  8. A perplexing question. Why is the realization and implementation of Open Science infrastructures happening so slowly? When there is so much, almost frenzied, activity going on in Open Science from top-down institutional programmes and bottom-up initiatives, almost to the point of bursting. What is holding back the work? …”

Tipping Points, For-Profit Scientific Publishing, and Closed Science

“Here’s the thing. How can I support a textbook that students will need $214 dollars to buy?  I cannot.  Not as a scientist committed to the tenet that information should be available to all, an educator who believes education is a right not a privilege, a mentor who needs to remove barriers for my students, and lastly someone who came from a lower socioeconomic family, struggled to purchase textbooks, and is now committed to reaching back and pulling others up.  I. CAN. NOT….”

An Open Toolkit for Tracking Open Science Partnership Implementation and Impact – F1000Research

The article and associated documents present a toolkit for tracking the implementation and impact of open science (OS) partnerships. OS partnerships take on a variety of forms with different levels of openness, sharing and absence of intellectual property rights. As the article describes, OS partnerships hold the promise of lowering costs and increasing productivity of both research and innovation. The article describes the need for and the collaborative process used to develop the toolkit while the associated documents contain the toolkit itself. We are now seeking comments and suggestions on both the article and toolkit from the larger community. We specifically seek comments from those studying, working with, or engaged in OS and OS-related projects. In particular, we welcome comments relating to the comprehensiveness of our measures and what may be missing. We also seek comments on whether the breadth of the toolkit is too ambitious to be effectively implemented and, if so, what measures should be eliminated. We further invite the community to identify any projects – OS or otherwise – that may be amenable to collecting and sharing data based on the toolkit indicators. The present toolkit will need to be translated into open source tools that, to the extent possible, collect the data automatically. Any assistance in developing these tools would be most appreciated. Comments will be accepted online on GoogleDocs until January 31st, 2019. After the comment period closes, our team will revise the article and toolkit, taking into account proposed edits. We then propose to submit the article and toolkit to the Gates Open Platform for publication.