Cart
Free Shipping in the UK
Proud to be B-Corp

Towards Responsible Plant Data Linkage: Data Challenges for Agricultural Research and Development Hugh F. Williamson

Towards Responsible Plant Data Linkage: Data Challenges for Agricultural Research and Development By Hugh F. Williamson

Towards Responsible Plant Data Linkage: Data Challenges for Agricultural Research and Development by Hugh F. Williamson


£40.89
Condition - New
Only 2 left

Towards Responsible Plant Data Linkage: Data Challenges for Agricultural Research and Development Summary

Towards Responsible Plant Data Linkage: Data Challenges for Agricultural Research and Development by Hugh F. Williamson

This open access book provides the first systematic overview of existing challenges and opportunities for responsible data linkage, and a cutting-edge assessment of which steps need to be taken to ensure that plant data are ethically shared and used for the benefit of ensuring global food security - one of the UN's Sustainable Development Goals. The volume focuses on the contemporary contours of such challenges through sustained engagement with current and historical initiatives and discussion of best practices and prospective future directions for ensuring responsible plant data linkage.

The volume is divided into four sections that include case studies of plant data use and linkage in the context of particular research projects, breeding programs, and historical research. It address technical challenges of data linkage in developing key tools, standards and infrastructures, and examines governance challenges of data linkage in relation to socioeconomic and environmental research and data collection. Finally, the last section addresses issues raised by new data production and linkage methods for the inclusion of agriculture's diverse stakeholders.

This book brings together leading experts in data curation, data governance and data studies from a variety of fields, including data science, plant science, agricultural research, science policy, data ethics and the philosophy, history and social studies of plant science.


About Hugh F. Williamson

Sabina Leonelli is Professor in Philosophy and History of Science at theUniversity of Exeter, UK, and a Turing Fellow at the Turing Institute for data science and artificial intelligence in London. She serves as the Director of the Exeter Centre for the Study of the Life Sciences and leads the Data Studies strand of the Institute for Data Science and Artificial Intelligence. Her research concerns the philosophy, history and sociology of data-intensive science, especially the research processes, scientific outputs and social embedding of Open Data and Big Data, with a specific focus on the plant and agricultural sciences. She published widely in the history, philosophy and social studies of science, as well biology and data science; and among her books are the award-winning Data-Centric Biology: A Philosophical Study (2016, Chicago University Press), the edited volume Data Journeys in the Sciences (2020, Springer; with Niccolo Tempini), and Data and Society: A Critical Introduction (2021, SAGE; with Anne Beaulieu). Her qualifications include a PhD in the history and philosophy of science from the Vrije Universiteit in Amsterdam, a MSc in History and Philosophy of Science from the London School of Economics and a BSc (Honours) in History, Philosophy and Social Studies of Science from University College London.

Hugh Williamson is Research Fellow in the Department of Sociology, Philosophy and Anthropology at the University of Exeter, UK, where he is working on the Alan Turing Institute-funded project 'From Field Data to Global Indicators:Towards a Framework for Intelligent Plant Data Linkage.' Working between the fields of science and technology studies and political anthropology, he has conducted research on agroecological conservation and rural development in Romania as well as on global data linkage in the plant and agricultural sciences. He holds an MRes and PhD in Social Anthropology from the University of Cambridge.

Table of Contents

Introduction: Towards Responsible Plant Data LinkagePart I: Experiences from the TrenchesBetween Subsistence and Agronomy: Carl Linnaeus (1707-1778) on Famine FoodsManaging Data in Crop Breeding: A Hundred Year Challenge
Data, Duplication, and the Decentralisation of Crop Collections
Data Management in a Multi-Disciplinary African RTB Crop Breeding ProgramPart II: Technical Challenges of Data LinkageChallenges to Data Linkage in Plants: Two Parables from the Pea
From Farm to FAIR: The Trials of Linking and Sharing Wheat Research Data
Plant Scientific Data Integration, From Building Community Standards to Defining a Consistent Data LifecyclePart III: Governance Challenges of Data Linkage
Spinning the Agricultural Data Web
Creating a Digital Marketplace for Agrobiodiversity and Plant Genetic Sequence Data: Legal and Ethical Considerations of an AI and Blackchain Based SolutionDigital Sequence Information and Genetic Resources: Global Policy Meets InteroperabilityCollaboration in Crop Diversity Management: A Pragmatist Approach to Data SharingPart IV: Social Challenges of Data Linkage
The Research Data Alliance Interest Group on Agricultural Data: Supporting a Global Community of PracticeEthical and Legal Considerations in Smart Farming: A Farmer's Perspective
Responsibility Beyond Ethics and Infrastructures: Conceptual and Normative Considerations for Plant Data Linkage and Agriculture

Additional information

NPB9783031132780
9783031132780
3031132785
Towards Responsible Plant Data Linkage: Data Challenges for Agricultural Research and Development by Hugh F. Williamson
New
Paperback
Springer International Publishing AG
2022-10-27
317
N/A
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
This is a new book - be the first to read this copy. With untouched pages and a perfect binding, your brand new copy is ready to be opened for the first time

Customer Reviews - Towards Responsible Plant Data Linkage: Data Challenges for Agricultural Research and Development