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Short abstract:

EU Open Science (OS) policies are currently implemented nationally and locally. Three dimensions of openness are conceptualised (as democratisation, institutional response, for pluralism). Now it’s vital to consider all dimensions and principles identified to ensure OS aligns with democratic values.

Long abstract:

Currently, we are experiencing a crucial moment in the development of Open Science (OS) policies in the EU: European OS policies are being implemented both at national level (i.e., Member States) and at local level (i.e., universities and research centres) (Paseri 2022). Insofar as OS is emphasized by institutions, the philosophy of law can guide in understanding the new context and provide a blueprint for change. Therefore, this contribution proposes three senses of the concept of openness:

(i) Openness as the democratisation of knowledge fostered by new digital technologies, which emerged between the late 1990s and the beginning of the new Century, resulting in the principles of access and collaboration.

(ii) Openness as an institutional response to the demands of the various actors, public and private, which emerged around 2015, conveying the principles of transparency, integrity and sharing.

(iii) Finally, openness for pluralism, a fundamental dimension that complements the previous ones, introducing the principle of epistemic equality (Fricker, 2007) and inclusiveness in OS (Leonelli, 2023). If the first two meanings of openness describe the evolution of the phenomenon, the third dimension is prescriptive and is the one we need to focus on in this complex current context.

The contribution argues that in the current phase of development of OS policies, it is essential to consider all three dimensions of openness identified and especially the entire set of principles (i.e., access, collaboration, transparency, integrity, sharing, epistemic equality, inclusiveness) to ensure OS in a deliberative, participatory, pluralist, and inclusive democracy (Landemore, 2020).

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Long abstract:

Agricultural science is a highly interdisciplinary endeavour requiring coordination between highly specialized subfields that often don't share common practices, language or worldview. So how is collaboration possible, and especially the kind needed to flexibly address urgent agroecological issues at a transnational scale?

Based on insights from my ethnographic observations of local agricultural research practices in Southern Greece, I propose a framework for thinking about interdisciplinarity in its situated and dynamic dimension as an ongoing process of finding complementarity, driven by a mutual understanding of lack of knowledge, skilfulness or resources. In my case study, a foundational scaffold that enables this multifaceted form of complementarity is the institutional lab organisation, which distinguishes between crops-specific and supportive specialties. Each of these functions perpendicular to each other with crop-specific specialties having a "vertical" single focus on specific plant organisms (olive, citrus, subtropical crops) while the supportive functioning "horizontally", cutting through various crops, bioecological systems and research methods.

Understanding this dynamic of cross-complementarity can help illuminate epistemic inequality in data-intensive crop science. "Horizontal" specialties, such as genomics, bioinformatics and remote sensing, tend to be more technologically equipped and attract more funding, while more traditional species-focused "vertical" specialities tend to have a harder time advocating for their legitimacy and their "attractiveness". In my presentation, I wish to explore the idea that there might be organizational/operational reasons why epistemic inequalities arise based on the cross-complementarity dynamic.

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Long abstract:

In the rapidly evolving landscape of data-centric life sciences, ensuring openness and equity in knowledge production is pivotal for sustainable agricultural development. This research investigates these principles within Ghana's CSIR-Crops Research Institute (CRI). Emphasising collaborative practices, the research delves into the strategies employed by the institute to foster inclusive and participatory approaches in generating agricultural knowledge. The study focuses on the dynamics of collaboration both internally and externally, focusing on interactions between CRI researchers and farmers, and on the pivotal role played by extension officers. By examining the collaborative mechanisms, information-sharing protocols, and engagement strategies, the research seeks to understand how knowledge is co-created and disseminated.

A critical analysis of power dynamics within these collaborative practices forms a central aspect of the study. The research explores how decision-making processes unfold, and the extent to which diverse stakeholders, particularly farmers and extension officers, are empowered in the knowledge production chain. It also seeks to uncover challenges and successes encountered by the Crops Research Institute in Ghana, offering insights for similar institutions striving to enhance openness and equity in their knowledge production endeavours.

By presenting a nuanced examination of collaborative practices in the Crops Research Institute, this study aims to contribute to the broader discourse on fostering openness and equity in knowledge production within the context of agricultural research. Additionally, it seeks to understand how the identified challenges and successes can be leveraged to promote sustainable and inclusive approaches that can benefit both researchers and the communities they serve.

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Short abstract:

This paper takes water as an entry point of an investigation into the homes of the urban Colombia. It combines auto-ethnographic-exercises and water-quality-work, engaging with principles of equity in vulnerable settings. Community research assistants had labor contracts as research assistants.

Long abstract:

We know little about the socio-ecological life within low-income homes in the urban South. This, despite the fact that it is in these homes that many of the processes sustaining life in the city take place and Global South cities are home to the majority of residents worldwide. This paper takes water as an entry point of an investigation into the homes of the urban Colombia. It follows water, as it is essential for sustaining everyday life, and goes beyond it into other material/atmospheric components of the home. Stored/stagnant waters are never only water but are also home to large communities of organisms such as bacteria and mosquitoes that eventually continue their lives outside of water.

It combines auto-ethnographic-exercises (AEE) and water-quality-work (WQW). Through AEE, community members acted as community research assistants (CRAs) and wrote/talked about experiences, emphasizing everyday interactions with different types of water, pollution, and mosquitoes. In turn, the microbiological changes in domestic water, as well as the breeding of mosquitoes, were captured by CRAs through basic WQW inside homes, including pupal surveys. The combination of AEE and WQW engages with principles of openness and equity in vulnerable research settings. AEE allows for multiple perspectives and increases the source of data and information contributing to a more in-depth understanding of the home, and, in combination with WQW, enables theory construction on the interconnectedness between politics/power and the material life of water. CRAs were remunerated and had labor contracts for their work as research assistants.

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Short abstract:

This paper discusses equity within data practices in the life sciences by exploring the case of biocuration. Sensitised by the notion of epistemic injustice, it discusses how biocuration is increasingly organised as a scholarly community, and describes the geographies and practices involved in it.

Long abstract:

This paper discusses equity within data practices in the life sciences by exploring the ways in which biocuration – the extraction of “knowledge from biological data and [its conversion] into a structured, computable form” (Quaglia et al 2022) – is developing as a professional and scholarly community. Based on interviews with biocurators around the world and on ongoing ethnographic with the field, the paper makes three moves. First, I outline how biocurators are seeking to organise as a community, and why they see it as urgent to do so: their work is framed as being central to the contemporary biosciences, but simultaneously precarious, and often entirely invisible to its users. Second, I use the notion of epistemic (in)justice (cf. Milan & Treré 2019) to reflect on how and why curation may be devalued in science, arguing that recognising the epistemic value of the practices involved in curation could help build more equitable research systems. Finally, I reflect on the geographies of biocuration, its place in global research infrastructures, and uneven locations of agency within these. The paper thus seeks to contribute to discussions of open data by outlining some of the diverse forms of work that lie behind data sharing in the life sciences, and by highlighting inequity in how different aspects of this work may be (de)valued.

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Short abstract:

Through a study of a replication debate, I examine how data processing can both enforce and invisibilize critical epistemic decisions. This project examines both open data and open source processing tools as sites for epistemic contestation, particularly across diverse forms of expertise.

Long abstract:

Critical research on scientific data processing has often focused on the human discernment involved in cleaning, labeling, and otherwise caring for data. For open datasets, data processing is understood to include the data transformations that “everyone”—all imagined research users—would agree are necessary. However, the epistemic values involved in processing decisions are often rooted in a community of practice which shares a specific understanding of their object of study—an understanding which may be distinct from that of other research communities. Here, I examine the role of data processing in human microbiome research through a recent replication debate over a high-profile study. While numerous groups have claimed fault with its findings, the argument hinges not on issues with the data or analytic method, but the data processing pipeline: the open dataset used in the paper was processed with a different set of assumptions than those of the researchers, whose own processing tools are alleged to have introduced (rather than identified) their key finding. Drawing on this debate, as well as interviews with bioinformatics software developers, I show that open source data processing tools can both enforce and invisibilize critical decisions, demonstrating the limits of openness without an awareness of tacit epistemic norms. I also reflect on what this means for diverse research communities who share large data resources, typically produced by investigators in the Global North.

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Long abstract:

The purpose of this communication is to present the results of a scoping review within the project: Long-term consequences of Zika virus infections during pregnancy for school-aged children and their families in Brazil (LIFE Zika). Since a cluster of newborn microcephaly cases was noticed and related to vertical transmission of Zika virus infections during pregnancy, Brazil has experienced a range of repercussions of the Zika virus epidemic (ZIKV) particularly devastating consequences of Congenital Zika Syndrome for children (CZS) and their families. Zika virus was considered a Public Health Emergency of International Concern (PHEIC) from February to November 2016 by WHO, and CZS is a new disease with many knowledge gaps to inform clinical decision-making and public policies (e.g., prenatal screening, educational adaptations, and social protection), requiring data sharing for both scientists and health authorities. In this sense, our study aims to map and analyse how data sharing in the ZIKV epidemic, and Congenital Zika Syndrome have been approached in the scientific literature from 2015 to 2023. We consider international perspectives on data sharing in PHEIC and distinctive elements from low- and middle-income countries using the Zika epidemic in Brazil as a case study. Our categories of analysis were delineated considering scientific, technical and social issues concerning data sharing and stakeholders’ roles (academia, funders, multilateral organisations, governmental authorities, affected subjects, communities and countries).

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Short abstract:

Do open data infrastructures like genomic commons help address the issues of data sharing, data access and underrepresentation for countries like India which are riddled by various inequities themselves?

Long abstract:

This paper explores if open data infrastructures like genomic commons would help address the issues of data access and underrepresented countries. India is the most populous country in world but is severely underrepresented in the global public databases used for risk interpretation of inherited cancers. The underrepresentation is significantly affected by local data practices for risk interpretation of inherited cancer which include variant data generation, sequencing, annotation, interpretation and sharing. The paper argues that data practices are actively shaped by unequal realities of Indian public health, external market pressures, unavailability of data resources to institutions and individuals in different socioeconomic, geographical, and demographic positions, deficiency of institutional and organizational resources and postcolonial expertise and infrastructure.

With these underlying issues plaguing the risk interpretation landscape, it is worth exploring if open data sharing approaches like commons would enable equitable data sharing, data access and representation when it is not a level playing field for countries like India. This mixed method study highlights the perspectives of local practitioners and testing laboratories about the existing information infrastructures and potential solutions like commons. Preliminary analysis points that inadequate funding, expertise and siloed governance are major impediments for approaches like commons to be reality in India. This, however, exists in a paradoxical juxtaposition to the India’s contribution in leading international consortia and transnational genomic initiatives, illustrating their capacities to make genomic data accessible under collective action. This work-in-progress aims to highlight such tensions between possibilities and limitations of engagement of the underrepresented countries.

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Short abstract:

This paper traces a movement to “open” the research and making of drugs, a sociotechnical space known for entrenched intellectual property regimes, and analyzes its implications for health equity.

Long abstract:

Research institutions and funding agencies have increasingly embraced open science as a means to propel biomedical advancement. Meanwhile, the rising complexity and costs of drug development have led some to wonder whether open practices should be extended to pharmaceuticals, a space known for entrenched intellectual property regimes. In this paper, I trace the emergence of collective action to apply open science to the research and making of drugs, an area I call "open pharma." Drawing on in-depth interviews with open pharma leaders and document analysis of journal articles and organizational policies and websites, I demonstrate how open pharma resembles other scientific/intellectual movements by formulating and advancing a new program of thought. At the same time, the sociotechnical space of pharmaceuticals is deeply entwined in capitalist political economic structures (legal, regulatory, and financial markets) that shape how actors frame and organize their work. Findings identify major narratives discursively employed by actors to frame the movement and mobilize others, often drawing on market logics; illustrate the active building and institutionalizing of open pharma infrastructure through the establishment of organizations and open science policies; and reveal structural barriers to open pharma in universities with publishing and commercialization imperatives—which often translate to patent imperatives. I demonstrate that “open” is being defined and operationalized in particular ways, prioritizing public data sharing of early research (which may later be privatized) over other interventions such as public clinical trials and commercialization, begging the question of where, when, and for whom open pharma is beneficial.

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Short abstract:

Social genomics, which studies genetic correlates of social outcomes, has built a cohesive research community thanks to inconsistent openness. Its approaches to data sharing successfully manage, but do not resolve, controversies over its understanding of human difference and social inequality.

Long abstract:

“Social genomics” research attempts to correlate human genetics with social phenomena such as educational attainment and wealth. Its growth in recent decades, from sample sizes of hundreds to millions, relies on mobilizing genetic and phenotypic data from government, academic, and corporate platforms; these data were usually originally collected for other purposes, including biomedicine and genealogy. Openness is thus a desideratum in social genomics, as in other data-centric sciences, but it has a complex relationship with other principles, including individual privacy, intellectual property, and equity.

This paper examines how social genomic researchers have sought or refused openness, and how this has structured the community’s norms, epistemology, and even membership. A young research program on the interstices of the life and social sciences, social genomics lacks many disciplinary structures that, in other sciences, would determine which research is encouraged or discouraged. The stances data-sharing platforms take towards openness have thus taken an outsize role in shaping this community. For instance, they request data from others in the name of understanding and reducing inequality, but use technical, legal, and rhetorical means to discourage data sharing for undesirable research, for instance, labeling certain inter-group comparisons as discriminatory and unscientific. To constrain downstream uses, data may be shared or not shared, abstracted or synthesized, or accompanied by binding or non-binding instructions proscribing immoral or unscientific uses. By focusing on openness as merely a matter of sharing (or not) scientific objects, social genomics has managed, but failed to resolve, controversies about its epistemological and moral principles.