The Data Revolution: Big Data, Open Data, Data Infrastructures and Their Consequences

The Data Revolution: Big Data, Open Data, Data Infrastructures and Their Consequences

By: Rob Kitchin (author)Paperback

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"Carefully distinguishing between big data and open data, and exploring various data infrastructures, Kitchin vividly illustrates how the data landscape is rapidly changing and calls for a revolution in how we think about data." - Evelyn Ruppert, Goldsmiths, University of London "Deconstructs the hype around the `data revolution' to carefully guide us through the histories and the futures of `big data.' The book skilfully engages with debates from across the humanities, social sciences, and sciences in order to produce a critical account of how data are enmeshed into enormous social, economic, and political changes that are taking place." - Mark Graham, University of Oxford Traditionally, data has been a scarce commodity which, given its value, has been either jealously guarded or expensively traded. In recent years, technological developments and political lobbying have turned this position on its head. Data now flow as a deep and wide torrent, are low in cost and supported by robust infrastructures, and are increasingly open and accessible. A data revolution is underway, one that is already reshaping how knowledge is produced, business conducted, and governance enacted, as well as raising many questions concerning surveillance, privacy, security, profiling, social sorting, and intellectual property rights. In contrast to the hype and hubris of much media and business coverage, The Data Revolution provides a synoptic and critical analysis of the emerging data landscape. Accessible in style, the book provides: A synoptic overview of big data, open data and data infrastructures An introduction to thinking conceptually about data, data infrastructures, data analytics and data markets Acritical discussion of the technical shortcomings and the social, political and ethical consequences of the data revolution An analysis of the implications of the data revolution to academic, business and government practices

About Author

Rob Kitchin is a professor and ERC Advanced Investigator in the National Institute of Regional and Spatial Analysis at the National University of Ireland Maynooth, for which he was director between 2002 and 2013. He has published widely across the social sciences, including 23 books and 140 articles and book chapters. He is editor of the international journals, Progress in Human Geography and Dialogues in Human Geography, and for eleven years was the editor of Social and Cultural Geography. He was the editor-in-chief of the 12 volume, International Encyclopedia of Human Geography, and edits two book series, Irish Society and Key Concepts in Geography. He is currently a PI on the Programmable City project, the Digital Repository of Ireland, and the All-Island Research Observatory. He has delivered over 100 invited talks at conferences and universities and his research has been cited over 600 times in local, national and international media. His book `Code/Space' (with Martin Dodge) won the Association of American Geographers `Meridian Book Award' for the outstanding book in the discipline in 2011 and a `CHOICE Outstanding Academic Title 2011' award from the American Library Association. He was the 2013 recipient of the Royal Irish Academy's Gold Medal for the Social Sciences.


Chapter 1: Conceptualising Data What are data? Kinds of data Data, information, knowledge, wisdom Framing data Thinking critically about databases and data infrastructures Data assemblages and the data revolution Chapter 2: Small Data, Data Infrastructures and Data Brokers Data holdings, data archives and data infrastructures Rationale for research data infrastructures The challenges of building data infrastructures The challenges of building data infrastructuresData brokers and markets Chapter 3: Open and Linked Data Open data Linked data The case for open data The economics of open data Concerns with respect to opening data Chapter 4: Big Data Volume Exhaustive Resolution and indexicality Relationality Velocity Variety Flexibility Chapter 5: Enablers and Sources of Big Data The enablers of big data Sources of big data Directed Data Automated data Volunteered data Chapter 6: Data Analytics Pre-analytics Machine learning Data mining and pattern recognition Data visualisation and visual analytics Statistical analysis Prediction, simulation and optimization Chapter 7: The Governmental and Business Rationale for Big Data Governing people Managing organisations Leveraging value and producing capital Creating better places Chapter 8: The Reframing of Science, Social Science and Humanities Research The fourth paradigm in science? The re-emergence of empiricism The fallacies of empiricism Data-driven science Computational social sciences and digital humanities Chapter 9: Technical and Organisational Issues Deserts and deluges Access Data quality, veracity and lineage Data integration and interoperability Poor analysis and ecological fallacies Skills and human resourcing Chapter 10: Ethical, Political, Social and Legal Concerns Data shadows and dataveillance Privacy Data security Profiling, social sorting and redlining Secondary uses, control creep and anticipatory governance Modes of governance and technological lock-ins Chapter 11: Making Sense of the Data Revolution Understanding data and the data revolution Researching data assemblages Final thoughts

Product Details

  • ISBN13: 9781446287484
  • Format: Paperback
  • Number Of Pages: 240
  • ID: 9781446287484
  • weight: 370
  • ISBN10: 1446287483

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