Researchers Collaboration: A waste of time?
Sooooory you won’t find any publication that praises individual research over collaboration : we haven’t found any ! Research collaboration boosts R&D efficiency but requires organizational changes and mobilizes specific resources.
Will you guess the conclusions of the following major publications on research collaboration?
Internationally, researchers tend to collaborate more, or less?
The answer depends on the country, according to Jonhatan Adams¹ and his article “Collaborations: The fourth age of research”. After studying 25 million scientific papers in the last 30 years, he found out that “international collaboration in [established economies has] increased more than ten-fold” while “domestic output has increased by only 50%”. On the contrary, “about 75% of the research output of China, Brazil, India and South Korea remains entirely domestic.” This is a good indicator of the disparity of research collaboration, and the general tendancy of more and more collaboration worldwide !
“in this age of big data […], the question will be who has the skills to exploit knowledge assets fastest […]. Shared knowledge and discovery sideline the idea of securing intellectual property” Johnatan Adams¹
Note 1: Collaborations: The fourth age of research by Jonathan Adams, Nature vol 497, 2013 https://www.nature.com/articles/497557a https://environment.uw.edu/wp-content/uploads/2014/01/International-Collaboration.pdf
Should researchers collaborate with product development?
The answer is Yes: Internal collaboration is the key to more efficient research, most of all with development teams and even marketing. After all R&D means Research AND Development, right? A must-read book on the subject has been written by Robin Williams², consultant in R&D management, research models, and processes. He notably explains that “technology should flow from the researchers to development, and marketplace and customer needs should flow to the researchers.”.
“Free flows of information, frequent visits and exchanges of people can contribute to such collaboration and successful innovation.” Robin Williams²
Is it worthy to invest in a research collaboration system?
A very recent publication from Barend Mons³ estimates research departments should at least “invest 5% of research funds in ensuring data are reusable”. This expert in research knowledge sharing and networking asserts the importance of FAIR data for “interdepartmental collaboration through data-sharing infrastructures. He estimates that implementing policies designed to render data findable, accessible, interoperable and reusable (FAIR) will require a "large cadre of professionals, about one for every 20 researchers."
“It is irresponsible to support research but not data stewardship. […] The key is to build capacity, enable groups to collaborate nationally and internationally and share good practices so that good data stewardship becomes the rule, not the exception.” Barend Mons³
Can a software support researchers’ collaboration?
At the heart of an R&D organization is its information system: a suite of software applications and collaborative databases designed to support researchers in their daily work and in decision-making to reach their objectives. Professional applications such as plant breeding software propose all-in-one tools to master processes, analysis, reporting and make the most of data. It needs to incorporate multidisciplinary and transversal research activities, to fully secure and valorize the handled information.
Research departments using RnDExperience™ benefit from the standardization of their data and methods. They particularly appreciate to work in real time securely on the same material from various locations and activities
1- Collaborations: The fourth age of research by Jonathan Adams, Nature vol 497, 2013
2- Robin Williams PhD, Managing Research, Innovation and Transformation, 4th edition, Lulu, 2008
3- NATURE - 25 FEBRUARY 2020 - Invest 5% of research funds in ensuring data are reusable, Barend Mons. https://www.nature.com/articles/d41586-020-00505-7
4- FAIR data are data which meet principles of findability, accessibility, interoperability, and reusability. https://en.wikipedia.org/wiki/FAIR_data