Today, data quality issues are diagnosed and addressed in a piece-meal fashion. The authors recommend a data lifecycle approach and provide a road map, that is more appropriate with the dimensions of Big Data and fits different stages in the analytical workflow.

A rigorous and simple method for the determination of the modulation transfer function (MTF) of a sampled imaging system is presented. One calculates the MTF by imaging bar patterns and calculating the reduction in amplitude of the fundamental frequency components. The optimal set of bar-pattern frequencies that reduce errors from aliased frequency components is derived. Theoretical and experimental data are presented.

No abstract

As data sources and data size proliferate, knowledge discovery from 'Big Data' is starting to pose several challenges. In this paper, we address a specific challenge in the practice of enterprise knowledge management while extracting actionable nuggets from diverse data sources of seemingly related information. In particular, we address the challenge of archiving knowledge gained through collaboration, dissemination and visualization as part of the data analysis inference and decision-making lifecycle. We motivate the implementation of an enterprise data discovery and knowledge recorder tool called SEEKER based on a real-world case study. We motivate the implementation of an enterprise data discovery and knowledge recorder tool called SEEKER (Schema Exploration and Evolving Knowledge Entity Recorder) based on the queries and the analytical artifacts that are being created by analysts as they use the data. We show how the tool serves as a digital record of institutional domain knowledge and as documentation for the evolution of data elements, queries and schemas over time. As a knowledge management service, a tool like SEEKER saves enterprise resources and time by (1) avoiding analytic "silos" (i.e., a separate set of data that is not included in an enterprise's data administration), (2) expediting the process of multi-source data integration and (3) intelligently documenting discoveries from collaborating analysts.