An Information Product Approach for Total Information Awareness

Abstract

Abstract--To fight terrorism successfully, the quality of data must be considered to avoid garbage-in-garbage-out. Research has shown that data quality (DQ) goes beyond accuracy to include dimensions such as believability, timeliness, and accessibility. In collecting, processing, and analyzing a much broader array of data than we do currently, therefore, a comprehensive approach must be developed to ensure that DQ is incorporated in determining the most probable current or future scenario for preemption, national security warning and decision making. Additional data such as who was the data source, when was the data made available, how, where, and why also need to be included to judge the quality of the information assembled from these data.We propose such an approach for Total Information Awareness with Quality (TIAQ), which includes concepts, models, and tools. Central to our approach is to manage information as a product with four principles. We have applied the information product approach to research sites where opportunities arise. For example, the Air Force Material Command uses requirements definition and forecasting processes to perform a number of functions. However, the Air Force experienced several complex problems due to DQ problems; as a result, fuel pumps were unavailable. Each engine needs a fuel pump; when a pump is not available, a military aircraft is grounded. We traced the fuel-pump throughout the process of remanufacture, and identified root causes such as delays by pump contractors and ordering problems. To a certain extent, detecting foreign terrorists and decipher their plots are analogous to tracing fuel pumps. Our research provides an interdisciplinary approach to facilitating Total Information Awareness.

Macroeconomics of privacy and security for identity management and surveillance

“…The principle behind ID management is to increase the amount of information collected for every citizen (Crosby, 2008). Information is held for the purpose of protecting society from fraudulent behaviour, criminal activities, and terrorism (Wang et al, 2002). ID management is about the unreserved collection of data, which includes identification as well as behavioural data.…”

Dealing with information quality in software package selection: an empirically based approach

“…Firstly, the rigorous research method adopted by the authors, based on two consecutive surveys to deliver intermediate quality dimensions, then a follow‐up two‐phase empirical study to form families of quality factors or categories. Secondly, the effective use of the framework reported in industry and government [25–27]. Finally, we designed an on‐line questionnaire aimed to analyse the dimensions and aspects that were important for most SP selectors.…”

“…Further evidence exist that these four level dimensions and assets provide comprehensive coverage of the multi‐dimensional IQ construct in very diverse settings [25–27]. However, although the dimensions seemed suitable for general purposes, the assets proposed by Wang and Strong [12] have been traditionally applied in the context of data warehouses but not in a context as SP selection where some differences might be expected.…”

The Design and Implementation of a Corporate Householding Knowledge Processor to Improve Data Quality

“…Traditionally, "high quality" refers to the accuracy of data. In order to target the problems more precisely, research conducted at MIT Total Data Quality Management (TDQM) program [15,16] has shown data quality as a multidimensional concept, which includes dimensions such as accessibility, timeliness, believability, relevance, and accuracy of data. Methods, models, tools, and techniques for managing data quality using the information product approach have also been proposed [15,17].…”