Is it possible to give scientific solutions to Grand Challenges? On the idea of grand challenges for life science research

Efstathiou, Sophia

doi:10.1016/j.shpsc.2015.10.009

“…Addressing societal grand challenges can be viewed as a challenge in itself, requiring a willingness to explore new combinations of existing and novel approaches to knowledge production (Kuhlmann and Rip, 2018) as reflected in the frequent use of multi-, inter-and trans-disciplinary research programmes that bring together researchers from the natural sciences, social sciences and humanities as well as non-academic stakeholders (Efstathiou, 2016). However, it has been shown that this process can narrowly position or even mis-conceive the contribution of social sciences and humanities (Shove, 2010;Castree et al, 2014;Felt, 2014;Balmer et al, 2015), leaving such research programmes only 'selectively open' to the breadth of competencies and insights provided by these disciplines (Morris et al, 2019).…”

mentioning

confidence: 99%

Priorities for social science and humanities research on the challenges of moving beyond animal-based food systems

Morris

¹

,

Kaljonen

²

,

Aavik

³

et al. 2021

Humanit Soc Sci Commun

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Increasingly high-profile research is being undertaken into the socio-environmental challenges associated with the over-production and consumption of food from animals. Transforming food systems to mitigate climate change and hidden hunger, ensure food security and good health all point to reducing animal-based foods as a key lever. Moving beyond animal-based food systems is a societal grand challenge requiring coordinated international research by the social sciences and humanities. A ‘selective openness’ to this range of disciplines has been observed within multi-discipline research programmes designed to address societal grand challenges including those concerned with the sustainability of food systems, inhibiting the impact of social sciences and humanities. Further, existing research on animal-based foods within these disciplines is largely dispersed and focused on particular parts of food systems. Inspired by the ‘Sutherland Method’ this paper discusses the results of an iterative research prioritisation process carried out to enhance capacity, mutual understanding and impact amongst European social sciences and humanities researchers. The process produced 15 research questions from an initial list of 100 and classified under the following five themes: (1) debating and visioning food from animals; (2) transforming agricultural spaces; (3) framing animals as food; (4) eating practices and identities; and (5) governing transitions beyond animal-based food systems. These themes provide an important means of making connections between research questions that invite and steer research on key challenges in moving beyond animal-based food systems. The themes also propose loci for future transdisciplinary research programmes that join researchers from the natural sciences, social sciences, and humanities and stakeholders from beyond academia to develop cooperative research and implementation initiatives. The experiences gained from the prioritisation process draw attention to the value of spending time to discuss and collaboratively steer research enquiry into emergent and controversial matters of concern. Fundamental, ethical questions around the continuation or complete cessation of the use of animals for food was a key tension. The positioning of research towards these questions affects not only the framing of the research area but also the partners with whom the research can be carried out and for whom it may be of benefit.

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“…Humanity continues to face 'grand' challenges towards its sustainable development. Global issues such as climate change, food security and lifelong health and wellbeing require concerted efforts across the realms of science, policy and technology [4,5]; so do the challenges of biodiversity loss, fake news and pandemic tracking and mitigation. The need for a globally coordinated response to global challenges has already been well documented, with important policy goals being articulated by international organisations.…”

Section: Addressing Grand Challenges Is Linked To Scaled Cross-disciplinary Capabilitiesmentioning

confidence: 99%

FAIR Digital Objects for Science: From Data Pieces to Actionable Knowledge Units

Smedt

¹

,

Koureas

²

,

Wittenburg

³

2020

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Data science is facing the following major challenges: (1) developing scalable cross-disciplinary capabilities, (2) dealing with the increasing data volumes and their inherent complexity, (3) building tools that help to build trust, (4) creating mechanisms to efficiently operate in the domain of scientific assertions, (5) turning data into actionable knowledge units and (6) promoting data interoperability. As a way to overcome these challenges, we further develop the proposals by early Internet pioneers for Digital Objects as encapsulations of data and metadata made accessible by persistent identifiers. In the past decade, this concept was revisited by various groups within the Research Data Alliance and put in the context of the FAIR Guiding Principles for findable, accessible, interoperable and reusable data. The basic components of a FAIR Digital Object (FDO) as a self-contained, typed, machine-actionable data package are explained. A survey of use cases has indicated the growing interest of research communities in FDO solutions. We conclude that the FDO concept has the potential to act as the interoperable federative core of a hyperinfrastructure initiative such as the European Open Science Cloud (EOSC).

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“…Humanity continues to face 'grand' challenges towards its sustainable development. Global issues such as climate change, biodiversity loss, fake news, social inequality and lifelong health and wellbeing require concerted efforts across the realms of science, policy and technology [4,5]. The need for a globally coordinated response to those challenges has already been well documented, with important policy goals being articulated by international organisations.…”

Section: Addressing Grand Challenges Is Linked To Scaled Cross-discipmentioning

confidence: 99%

FAIR Digital Objects for Science: From Data Pieces to Actionable Knowledge Units

Smedt¹,

Koureas²,

Wittenburg³

2020

Preprint

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Data science is facing the following major challenges: (1) developing scalable cross-disciplinary capabilities, (2) dealing with the increasing data volumes and their inherent complexity, (3) building tools that help to build trust, (4) creating mechanisms to efficiently operate in the domain of scientific assertions, (5) turning data into actionable knowledge units and (6) promoting data interoperability. As a way to overcome these challenges, we further develop the proposals by early Internet pioneers for Digital Objects as encapsulations of data and metadata made accessible by persistent identifiers. In the past decade, this concept was revisited by various groups within the Research Data Alliance and put in the context of the FAIR Guiding Principles for findable, accessible, interoperable and reusable data. The basic components of a FAIR Digital Object (FDO) as a self-contained, typed, machine-actionable data package are explained. A survey of use cases has indicated the growing interest of research communities in FDO solutions. We conclude that the FDO concept has the potential to act as the interoperable federative core of a hyperinfrastructure initiative such as the European Open Science Cloud (EOSC).

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Is it possible to give scientific solutions to Grand Challenges? On the idea of grand challenges for life science research

Cited by 28 publications

References 39 publications

Priorities for social science and humanities research on the challenges of moving beyond animal-based food systems

Priorities for social science and humanities research on the challenges of moving beyond animal-based food systems

FAIR Digital Objects for Science: From Data Pieces to Actionable Knowledge Units

FAIR Digital Objects for Science: From Data Pieces to Actionable Knowledge Units

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