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Governing Smart Cities As Knowledge Commons - Introduction, Chapter 1 & Conclusion, Brett M. Frischmann, Michael J. Madison, Madelyn Sanfilippo Jan 2023

Governing Smart Cities As Knowledge Commons - Introduction, Chapter 1 & Conclusion, Brett M. Frischmann, Michael J. Madison, Madelyn Sanfilippo

Book Chapters

Smart city technology has its value and its place; it isn’t automatically or universally harmful. Urban challenges and opportunities addressed via smart technology demand systematic study, examining general patterns and local variations as smart city practices unfold around the world. Smart cities are complex blends of community governance institutions, social dilemmas that cities face, and dynamic relationships among information and data, technology, and human lives. Some of those blends are more typical and common. Some are more nuanced in specific contexts. This volume uses the Governing Knowledge Commons (GKC) framework to sort out relevant and important distinctions. The framework grounds …


A New Framework For Securing, Extracting And Analyzing Big Forensic Data, Hitesh Sachdev, Hayden Wimmer, Lei Chen, Carl Rebman Oct 2018

A New Framework For Securing, Extracting And Analyzing Big Forensic Data, Hitesh Sachdev, Hayden Wimmer, Lei Chen, Carl Rebman

Journal of Digital Forensics, Security and Law

Finding new methods to investigate criminal activities, behaviors, and responsibilities has always been a challenge for forensic research. Advances in big data, technology, and increased capabilities of smartphones has contributed to the demand for modern techniques of examination. Smartphones are ubiquitous, transformative, and have become a goldmine for forensics research. Given the right tools and research methods investigating agencies can help crack almost any illegal activity using smartphones. This paper focuses on conducting forensic analysis in exposing a terrorist or criminal network and introduces a new Big Forensic Data Framework model where different technologies of Hadoop and EnCase software are …


Welcome To The Machine: Privacy And Workplace Implications Of Predictive Analytics, Robert Sprague Apr 2015

Welcome To The Machine: Privacy And Workplace Implications Of Predictive Analytics, Robert Sprague

Robert Sprague

Predictive analytics use a method known as data mining to identify trends, patterns, or relationships among data, which can then be used to develop a predictive model. Data mining itself relies upon big data, which is “big” not solely because of its size but also because its analytical potential is qualitatively different. “Big data” analysis allows organizations, including government and businesses, to combine diverse digital datasets and then use statistics and other data mining techniques to extract from them both hidden information and surprising correlations. These data are not necessarily tracking transactional records of atomized behavior, such as the purchasing …


Commons At The Intersection Of Peer Production, Citizen Science, And Big Data: Galaxy Zoo, Michael J. Madison Jan 2014

Commons At The Intersection Of Peer Production, Citizen Science, And Big Data: Galaxy Zoo, Michael J. Madison

Book Chapters

The knowledge commons research framework is applied to a case of commons governance grounded in research in modern astronomy. The case, Galaxy Zoo, is a leading example of at least three different contemporary phenomena. In the first place Galaxy Zoo is a global citizen science project, in which volunteer non-scientists have been recruited to participate in large-scale data analysis via the Internet. In the second place Galaxy Zoo is a highly successful example of peer production, sometimes known colloquially as crowdsourcing, by which data are gathered, supplied, and/or analyzed by very large numbers of anonymous and pseudonymous contributors to an …


Slaves To Big Data. Or Are We?, Mireille Hildebrandt Oct 2013

Slaves To Big Data. Or Are We?, Mireille Hildebrandt

Mireille Hildebrandt

In this contribution the notion of Big Data is discussed in relation to the monetisation of personal data. The claim of some proponents as well as adversaries, that Big Data implies that ‘n = all’, meaning that we no longer need to rely on samples because we have all the data, is scrutinized and found both overly optimistic and unnecessarily pessimistic. A set of epistemological and ethical issues is presented, focusing on the implications of Big Data for our perception, cognition, fairness, privacy and due process. The article then looks into the idea of user centric personal data management, to …