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Big data ethics, also known simply as data ethics, refers to systemizing, defending, and recommending concepts of right and wrong conduct in relation to data, in particular personal data. [1] Since the dawn of the Internet the sheer quantity and quality of data has dramatically increased and is continuing to do so exponentially.
The term big data has been in use since the 1990s, with some giving credit to John Mashey for popularizing the term. [22] [23] Big data usually includes data sets with sizes beyond the ability of commonly used software tools to capture, curate, manage, and process data within a tolerable elapsed time.
Technoethics (TE) is an interdisciplinary research area that draws on theories and methods from multiple knowledge domains (such as communications, social sciences, information studies, technology studies, applied ethics, and philosophy) to provide insights on ethical dimensions of technological systems and practices for advancing a technological society.
Big data is generally defined as the rapid accumulation and compiling of massive amounts of information that is being exchanged over digital communication systems. The volume of data is large (often exceeding exabytes), cannot be handled by conventional computer processors, and is instead stored on large server-system databases. This ...
Dataism implies that all data is public, even personal data, to make the system work as a whole, which is a factor that's already showing resistance today. [ 12 ] Other analysts, such as Terry Ortleib, have looked at the extent to which Dataism poses a dystopian threat to humanity.
Information ethics has been defined as "the branch of ethics that focuses on the relationship between the creation, organization, dissemination, and use of information, and the ethical standards and moral codes governing human conduct in society". [1]
Data exhaust or exhaust data is the trail of data left by the activities of an Internet or other computer system users during their online activity, behavior, and transactions. This is part of a broader category of unconventional data [ 1 ] that includes geospatial, network, and time-series data and may be useful for predictive analytics .
Here data governance is a data management concept concerning the capability that enables an organization to ensure that high data quality exists throughout the complete lifecycle of the data, and data controls are implemented that support business objectives.