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Tag: OS

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Preservation, Sustainability, and Regaining Control – Echoes of the OPERAS 2026 & SCIROS Conference

It’s been more than two months since the OPERAS 2026 & SCIROS Conference, but the discussions we had during those four intense days are still echoing through our meetings, and influencing our strategic plans and actions. As a community, we observe that open science has matured into a well-established set of values, practices, and policies, while still keeping its diversity and openness to change and adaptation. The creative ferment that arises from encountering different perspectives is what enables us to innovate and move forward. At the same time, the sustainability of the open science infrastructure has come under strain as both misinformation and the predatory appropriation of the products of science proliferate, undermining trust and equity, which are its constitutive values, and as larger policy trends of securitisation and data sovereignty question its very purpose. In this context, AI technologies represent one of the most significant and rapidly evolving areas concerning both opportunity and risk for open science. 

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Network Analysis – How to Get Your Data Ready with the Help of ChatGPT?

Magdalena Wnuk

Open science is a social construct and set of practices which has evolved over time and played multiple roles in scholarly communication. As such, it can be studied, becoming an object of research itself. One method which is particularly useful for understanding the growth of the open science movement is network analysis, which captures how academic communication develops and theorises this evolving set of practices and underlying ideas. In the SCIROS project, we approach ‘open science’ as a distinct paradigm, which emerged in the latter half of the 20th century, though it draws on much older intellectual traditions (Leonelli 2023; David 2008). As a paradigm, open science encompasses a specific constellation of concepts, methods, and ways of framing research questions. It is continuously reshaped through both theoretical reflection and practical application. Therefore, we employ social network analysis to explore open science as a paradigm – mapping the circulation of key concepts related to openness, identifying clusters of collaboration, and detecting the most influential actors in the field. For this analysis, we utilise data from three sources: Scopus and Web of Science (both commercial), and  OpenAlex (free). The creation of our dataset has been described in a previous blog post, which can be found here. 

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