Reality mining :: using big data to engineer a better world /
In this book, the authors explore the positive potential of big data, showing the ways in which the analysis of big data ("reality mining") can be used to improve human systems as varied as political polling and disease tracking, while considering user privacy. They describe reality mining...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge, Massachusetts :
The MIT Press,
[2014]
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | In this book, the authors explore the positive potential of big data, showing the ways in which the analysis of big data ("reality mining") can be used to improve human systems as varied as political polling and disease tracking, while considering user privacy. They describe reality mining at five different levels: the individual, the neighborhood and organization, the city, the nation, and the world. For each level, they offer a nontechnical explanation of data collection methods and describe applications and systems that have been or could be built. These include a mobile app that helps smokers quit smoking; a workplace "knowledge system"; the use of GPS, Wi-Fi, and mobile phone data to manage and predict traffic flows; and the analysis of social media to track the spread of disease. The authors argue that big data, used respectfully and responsibly, can help people live better, healthier, and happier lives. -- |
| Beschreibung: | 1 online resource (vi, 199 pages) |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 9780262324564 0262324563 9780262324571 0262324571 |
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| 245 | 1 | 0 | |a Reality mining : |b using big data to engineer a better world / |c by Nathan Eagle and Kate Greene. |
| 264 | 1 | |a Cambridge, Massachusetts : |b The MIT Press, |c [2014] | |
| 264 | 4 | |c ©2014 | |
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| 520 | |a In this book, the authors explore the positive potential of big data, showing the ways in which the analysis of big data ("reality mining") can be used to improve human systems as varied as political polling and disease tracking, while considering user privacy. They describe reality mining at five different levels: the individual, the neighborhood and organization, the city, the nation, and the world. For each level, they offer a nontechnical explanation of data collection methods and describe applications and systems that have been or could be built. These include a mobile app that helps smokers quit smoking; a workplace "knowledge system"; the use of GPS, Wi-Fi, and mobile phone data to manage and predict traffic flows; and the analysis of social media to track the spread of disease. The authors argue that big data, used respectfully and responsibly, can help people live better, healthier, and happier lives. -- |c Edited summary from book | ||
| 505 | 0 | |a Introduction -- Part 1: Individual (One Person): -- Mobile phones, sensors, and lifelogging: collecting data from individuals while considering privacy -- Using personal data in a privacy-sensitive way to make a person's life easier and healthier -- Part 2: Neighborhood And The Organization (10 to 1,000 People): -- Gathering data from small heterogeneous groups -- Engineering and policy: building more efficient businesses, enabling hyperlocal politics, life queries, and opportunity searches -- Part 3: City (1,000 to 1,000,000 people): -- Traffic data, crime stats, and closed-circuit cameras: accumulating urban analytics -- Engineering and policy: optimizing resource allocation -- Part 4: Nation (1 Million to 100 Million People) -- Taking the pulse of a nation: census, mobile phones, and internet giants -- Engineering and policy: addressing national sentiment, economic deficits, and disasters -- Part 5: Reality Mining The World's Data (100 Million to 7 Billion People): -- Gathering the world's data: global census, international travel and commerce, and planetary-scale communication: -- Engineering a safer and healthier world -- Conclusion -- Notes -- Index. | |
| 650 | 0 | |a Data mining. |0 http://id.loc.gov/authorities/subjects/sh97002073 | |
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| author | Eagle, Nathan Greene, Kate, 1979- |
| author_GND | http://id.loc.gov/authorities/names/no2010154518 http://id.loc.gov/authorities/names/n2014006398 |
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| contents | Introduction -- Part 1: Individual (One Person): -- Mobile phones, sensors, and lifelogging: collecting data from individuals while considering privacy -- Using personal data in a privacy-sensitive way to make a person's life easier and healthier -- Part 2: Neighborhood And The Organization (10 to 1,000 People): -- Gathering data from small heterogeneous groups -- Engineering and policy: building more efficient businesses, enabling hyperlocal politics, life queries, and opportunity searches -- Part 3: City (1,000 to 1,000,000 people): -- Traffic data, crime stats, and closed-circuit cameras: accumulating urban analytics -- Engineering and policy: optimizing resource allocation -- Part 4: Nation (1 Million to 100 Million People) -- Taking the pulse of a nation: census, mobile phones, and internet giants -- Engineering and policy: addressing national sentiment, economic deficits, and disasters -- Part 5: Reality Mining The World's Data (100 Million to 7 Billion People): -- Gathering the world's data: global census, international travel and commerce, and planetary-scale communication: -- Engineering a safer and healthier world -- Conclusion -- Notes -- Index. |
| ctrlnum | (OCoLC)886539978 |
| dewey-full | 006.3/12 |
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| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.3/12 |
| dewey-search | 006.3/12 |
| dewey-sort | 16.3 212 |
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| discipline | Informatik |
| format | Electronic eBook |
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| id | ZDB-4-EBA-ocn886539978 |
| illustrated | Not Illustrated |
| indexdate | 2024-11-27T13:26:07Z |
| institution | BVB |
| isbn | 9780262324564 0262324563 9780262324571 0262324571 |
| language | English |
| oclc_num | 886539978 |
| open_access_boolean | |
| owner | MAIN DE-863 DE-BY-FWS |
| owner_facet | MAIN DE-863 DE-BY-FWS |
| physical | 1 online resource (vi, 199 pages) |
| psigel | ZDB-4-EBA |
| publishDate | 2014 |
| publishDateSearch | 2014 |
| publishDateSort | 2014 |
| publisher | The MIT Press, |
| record_format | marc |
| spelling | Eagle, Nathan, author. https://id.oclc.org/worldcat/entity/E39PBJqk3FfWBKgR6ywGkjrTHC http://id.loc.gov/authorities/names/no2010154518 Reality mining : using big data to engineer a better world / by Nathan Eagle and Kate Greene. Cambridge, Massachusetts : The MIT Press, [2014] ©2014 1 online resource (vi, 199 pages) text txt rdacontent computer c rdamedia online resource cr rdacarrier Includes bibliographical references and index. Print version record. In this book, the authors explore the positive potential of big data, showing the ways in which the analysis of big data ("reality mining") can be used to improve human systems as varied as political polling and disease tracking, while considering user privacy. They describe reality mining at five different levels: the individual, the neighborhood and organization, the city, the nation, and the world. For each level, they offer a nontechnical explanation of data collection methods and describe applications and systems that have been or could be built. These include a mobile app that helps smokers quit smoking; a workplace "knowledge system"; the use of GPS, Wi-Fi, and mobile phone data to manage and predict traffic flows; and the analysis of social media to track the spread of disease. The authors argue that big data, used respectfully and responsibly, can help people live better, healthier, and happier lives. -- Edited summary from book Introduction -- Part 1: Individual (One Person): -- Mobile phones, sensors, and lifelogging: collecting data from individuals while considering privacy -- Using personal data in a privacy-sensitive way to make a person's life easier and healthier -- Part 2: Neighborhood And The Organization (10 to 1,000 People): -- Gathering data from small heterogeneous groups -- Engineering and policy: building more efficient businesses, enabling hyperlocal politics, life queries, and opportunity searches -- Part 3: City (1,000 to 1,000,000 people): -- Traffic data, crime stats, and closed-circuit cameras: accumulating urban analytics -- Engineering and policy: optimizing resource allocation -- Part 4: Nation (1 Million to 100 Million People) -- Taking the pulse of a nation: census, mobile phones, and internet giants -- Engineering and policy: addressing national sentiment, economic deficits, and disasters -- Part 5: Reality Mining The World's Data (100 Million to 7 Billion People): -- Gathering the world's data: global census, international travel and commerce, and planetary-scale communication: -- Engineering a safer and healthier world -- Conclusion -- Notes -- Index. Data mining. http://id.loc.gov/authorities/subjects/sh97002073 Big data. http://id.loc.gov/authorities/subjects/sh2012003227 Computer networks Social aspects. Information science Social aspects. Information science Statistical methods. http://id.loc.gov/authorities/subjects/sh2007006260 Data Mining https://id.nlm.nih.gov/mesh/D057225 Exploration de données (Informatique) Données volumineuses. Réseaux d'ordinateurs Aspect social. Sciences de l'information Aspect social. COMPUTERS General. bisacsh COMPUTERS Database Management Data Mining. bisacsh Big data fast Computer networks Social aspects fast Data mining fast Information science Social aspects fast Information science Statistical methods fast Greene, Kate, 1979- author. https://id.oclc.org/worldcat/entity/E39PCjwGf3VWkQWfYp8Wc6Q4Rq http://id.loc.gov/authorities/names/n2014006398 Print version: Eagle, Nathan. Reality mining 9780262027687 (DLC) 2013047165 (OCoLC)869880206 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=826635 Volltext |
| spellingShingle | Eagle, Nathan Greene, Kate, 1979- Reality mining : using big data to engineer a better world / Introduction -- Part 1: Individual (One Person): -- Mobile phones, sensors, and lifelogging: collecting data from individuals while considering privacy -- Using personal data in a privacy-sensitive way to make a person's life easier and healthier -- Part 2: Neighborhood And The Organization (10 to 1,000 People): -- Gathering data from small heterogeneous groups -- Engineering and policy: building more efficient businesses, enabling hyperlocal politics, life queries, and opportunity searches -- Part 3: City (1,000 to 1,000,000 people): -- Traffic data, crime stats, and closed-circuit cameras: accumulating urban analytics -- Engineering and policy: optimizing resource allocation -- Part 4: Nation (1 Million to 100 Million People) -- Taking the pulse of a nation: census, mobile phones, and internet giants -- Engineering and policy: addressing national sentiment, economic deficits, and disasters -- Part 5: Reality Mining The World's Data (100 Million to 7 Billion People): -- Gathering the world's data: global census, international travel and commerce, and planetary-scale communication: -- Engineering a safer and healthier world -- Conclusion -- Notes -- Index. Data mining. http://id.loc.gov/authorities/subjects/sh97002073 Big data. http://id.loc.gov/authorities/subjects/sh2012003227 Computer networks Social aspects. Information science Social aspects. Information science Statistical methods. http://id.loc.gov/authorities/subjects/sh2007006260 Data Mining https://id.nlm.nih.gov/mesh/D057225 Exploration de données (Informatique) Données volumineuses. Réseaux d'ordinateurs Aspect social. Sciences de l'information Aspect social. COMPUTERS General. bisacsh COMPUTERS Database Management Data Mining. bisacsh Big data fast Computer networks Social aspects fast Data mining fast Information science Social aspects fast Information science Statistical methods fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh97002073 http://id.loc.gov/authorities/subjects/sh2012003227 http://id.loc.gov/authorities/subjects/sh2007006260 https://id.nlm.nih.gov/mesh/D057225 |
| title | Reality mining : using big data to engineer a better world / |
| title_auth | Reality mining : using big data to engineer a better world / |
| title_exact_search | Reality mining : using big data to engineer a better world / |
| title_full | Reality mining : using big data to engineer a better world / by Nathan Eagle and Kate Greene. |
| title_fullStr | Reality mining : using big data to engineer a better world / by Nathan Eagle and Kate Greene. |
| title_full_unstemmed | Reality mining : using big data to engineer a better world / by Nathan Eagle and Kate Greene. |
| title_short | Reality mining : |
| title_sort | reality mining using big data to engineer a better world |
| title_sub | using big data to engineer a better world / |
| topic | Data mining. http://id.loc.gov/authorities/subjects/sh97002073 Big data. http://id.loc.gov/authorities/subjects/sh2012003227 Computer networks Social aspects. Information science Social aspects. Information science Statistical methods. http://id.loc.gov/authorities/subjects/sh2007006260 Data Mining https://id.nlm.nih.gov/mesh/D057225 Exploration de données (Informatique) Données volumineuses. Réseaux d'ordinateurs Aspect social. Sciences de l'information Aspect social. COMPUTERS General. bisacsh COMPUTERS Database Management Data Mining. bisacsh Big data fast Computer networks Social aspects fast Data mining fast Information science Social aspects fast Information science Statistical methods fast |
| topic_facet | Data mining. Big data. Computer networks Social aspects. Information science Social aspects. Information science Statistical methods. Data Mining Exploration de données (Informatique) Données volumineuses. Réseaux d'ordinateurs Aspect social. Sciences de l'information Aspect social. COMPUTERS General. COMPUTERS Database Management Data Mining. Big data Computer networks Social aspects Data mining Information science Social aspects Information science Statistical methods |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=826635 |
| work_keys_str_mv | AT eaglenathan realityminingusingbigdatatoengineerabetterworld AT greenekate realityminingusingbigdatatoengineerabetterworld |