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・ Data Access Manager
・ Data access object
・ Data Access Technology
・ Data acquisition
・ Data administration
・ Data Age
・ Data aggregation
・ Data analysis
・ Data analysis expressions
・ Data analysis techniques for fraud detection
・ Data Analytics Acceleration Library
・ Data and Knowledge Engineering
・ Data and object carousel
・ Data anonymization
・ Data Applied
Data archaeology
・ Data architect
・ Data architecture
・ Data archive
・ Data as a service
・ Data assimilation
・ Data at rest
・ Data auditing
・ Data Authentication Algorithm
・ Data availability
・ Data bank
・ Data Base Task Group
・ Data based decision making
・ Data Becker
・ Data binding


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Data archaeology : ウィキペディア英語版
Data archaeology

Data archaeology refers to the art and science of recovering computer data encoded and/or encrypted in now obsolete media or formats. Data archaeology can also refer to recovering information from damaged electronic formats after natural or man made disasters.
The term originally appeared in 1993 as part of the Global Oceanographic Data Archaeology and Rescue Project (GODAR). The original impetus for data archaeology came from the need to recover computerized records of climatic conditions stored on old computer tape, which can provide valuable evidence for testing theories of climate change. These approaches allowed the reconstruction of an image of the Arctic that had been captured by the Nimbus 2 satellite on September 23, 1966, in higher resolution than ever seen before from this type of data.〔(Techno-archaeology rescues climate data from early satellites ) U.S. National Snow and Ice Data Center (NSIDC), January 2010 (Archived )〕
NASA also utilizes the services of data archaeologists to recover information stored on 1960s era vintage computer tape, as exemplified by the Lunar Orbiter Image Recovery Project (LOIRP).〔(LOIRP Overview ) NASA website November 14, 2008 (Archived )〕
==Recovery==
It is also important to make the distinction in data archaeology between data recovery, and data intelligibility. You may be able to recover the data, but not understand it. For data archeology to be effective the data must be intelligible. 〔 () Study on website October 23, 2011 〕

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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