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P095


Interrogating openness and equity in the data-centric life sciences 
Convenors:
Paola Castano (University of Exeter)
Sabina Leonelli (University of Exeter)
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Format:
Traditional Open Panel

Short Abstract:

With a focus on data practices in the life sciences, this panel invites contributions that scrutinize the principles of openness and equity in diverse research settings.

Long Abstract:

With a focus on data practices in the life sciences, this panel invites contributions that scrutinize the principles of openness and equity in diverse research settings. We build on three organizing ideas that contributors are invited to discuss and assess conceptually and empirically: (1) a conceptualization of openness in science not only in terms of sharing data resources, but of communication and connections between systems of practice within and beyond research (Leonelli 2023); (2) an understanding of data, databases, and data infrastructures not only as “material, numerical or technical” objects, but as “a result of social processes at work before, during, and after the data production” (Louafi et al. 2022, 274); (3) an acknowledgment that those systems of practice, social processes, and their communities are shaped by resources unequally available to institutions and individuals in different socioeconomic, geographical, and demographic positions (Bezuidenhout et al. 2017, Bezuidenhou and Chakauya 2018, Ross-Hellauer 2022, Goldstein and Nost 2022). From these organizing ideas, we challenge the notion that making science ‘open’ is sufficient to address those inequalities.

Some questions we will address include: How do different modalities of work with data in the life sciences build particular types of communities of practice? What are possible ways to assess community-building efforts around data sharing in the life sciences considering systemic inequities regarding minoritized groups and funding allocation structures? What are possibilities and limitations in efforts to engage underrepresented communities in these fields in open science? What do representation of underrepresented communities and participatory models mean and imply in these efforts? How are indicators of community-building, openness and equity assembled and turned into metrics in some settings in the life sciences and with which implications? What policy developments in data sharing in these fields may, or may not, help to address issues of inequity?

Accepted papers: