© 2020

Data Journeys in the Sciences

  • Sabina Leonelli
  • Niccolò Tempini
  • Facilitates an in-depth understanding of data-intensive methods

  • Is the most advanced survey of data practices across the sciences

  • Presents a ground-breaking and comprehensive framework for data studies

  • Contains original contributions by world-leading science scholars in the respective fields

Open Access

Table of contents

  1. Front Matter
    Pages i-xvii
  2. Sabina Leonelli
    Pages 1-24 Open Access
  3. Origins: Data Collection, Preparation and Reporting

  4. Clustering: Data Ordering and Visualization

  5. Sharing: Data access, Dissemination and Quality Assessment

  6. Interlude

    1. Front Matter
      Pages 227-227
    2. Theodore M. Porter
      Pages 229-236 Open Access
  7. Interpreting: Data Transformation, Analysis and Reuse

About this book


This groundbreaking, open access volume analyses and compares data practices across several fields through the analysis of specific cases of data journeys. It brings together leading scholars in the philosophy, history and social studies of science to achieve two goals: tracking the travel of data across different spaces, times and domains of research practice; and documenting how such journeys affect the use of data as evidence and the knowledge being produced. 

The volume captures the opportunities, challenges and concerns involved in making data move from the sites in which they are originally produced to sites where they can be integrated with other data, analysed and re-used for a variety of purposes. The in-depth study of data journeys provides the necessary ground to examine disciplinary, geographical and historical differences and similarities in data management, processing and interpretation, thus identifying the key conditions of possibility for the widespread data sharing associated with Big and Open Data. 

The chapters are ordered in sections that broadly correspond to different stages of the journeys of data, from their generation to the legitimisation of their use for specific purposes. Additionally, the preface to the volume provides a variety of alternative “roadmaps” aimed to serve the different interests and entry points of readers; and the introduction provides a substantive overview of what data journeys can teach about the methods and epistemology of research.


Big Data Data Epistemology Data Ethics Data Science Epistemology of Science Social Studies of Data Social Studies of Science Data Collection, Preparation and Reporting Data at the Large Hadron Collider Data Journeys in Medical Case Reports Data Ordering and Visualization Clustering Practices in Plant Phenomics Databases in Systems Biology Data access, Dissemination and Quality Assessment Methods for Climate Data Processing Data Journeys in Pharmaceutical Regulation Data Mixes in Big Data Linkage Practice Radiocarbon Dating and Robustness Reasoning in Archaeology Data from Objects to Assets Open Access

Editors and affiliations

  • Sabina Leonelli
    • 1
  • Niccolò Tempini
    • 2
  1. 1.Department of Sociology, Philosophy and Anthropology & Exeter Centre for the Study of the Life Sciences (Egenis)University of Exeter, Exeter, UK, Alan Turing InstituteLondonUK
  2. 2.Department of Sociology, Philosophy and Anthropology & Exeter Centre for the Study of the Life Sciences (Egenis)University of Exeter, Exeter, UK, Alan Turing InstituteLondonUK

About the editors

Sabina Leonelli is Professor in Philosophy and History of Science at the University of Exeter, where she co-directs the Centre for the Study of the Life Sciences and leads the data governance strand of the Institute for Data Science and Artificial Intelligence. Her interests include the epistemology, history and social studies of data-intensive science, open science and biological modelling. She is a Turing Fellow, ERC grantee, Editor-in-Chief of History and Philosophy of the Life Sciences, Associate Editor of the Harvard Data Science Review.

Niccolò Tempini is Senior Lecturer in Data Studies at the University of Exeter and a Turing Fellow at the Alan Turing Institute. He researches big data research and digital infrastructures, investigating the specific knowledge production economies, organization forms and data management innovations that these projects engender with a focus in their social and epistemic consequences. His research has been published in international journals across science and technology studies, information systems, sociology and philosophy. 

Bibliographic information