In spite of advances in technologies for working with data, analysts still spend an inordinate amount of time diagnosing data quality issues and manipulating data into a usable form. This process of ‘data wrangling’ often constitutes the most tedious and time-consuming aspect of analysis. Though data cleaning and integration arelongstanding issues in the database community, relatively little research has explored how interactive visualization can advance the state of the art. In this article, we review the challenges and opportunities associated with addressing data quality issues. We argue that analysts might more effectively wrangle data through new interactive systems that integrate data verification, transformation, and visualization. We identify a number of outstanding research questions, including how appropriate visual encodings can facilitate apprehension of missing data, discrepant values, and uncertainty; how interactive visualizations might facilitate data transform specification; and how recorded provenance and social interaction might enable wider reuse, verification, and modification of data transformations

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Background: Awareness of energy efficiency has been rising in the industrial and residential sectors but only recently in the health care sector.Purpose: To measure the energy consumption of modern CT and MRI scanners in a university hospital radiology department and to estimate energy-and cost-saving potential during clinical operation. Materials and Methods:Three CT scanners, four MRI scanners, and cooling systems were equipped with kilowatt-hour energy measurement sensors (2-Hz sampling rate). Energy measurements, the scanners' log files, and the radiology information system from the entire year 2015 were analyzed and segmented into scan modes, as follows: net scan (actual imaging), active (room time), idle, and system-on and system-off states (no standby mode was available). Per-examination and peak energy consumption were calculated. Results:The aggregated energy consumption imaging 40 276 patients amounted to 614 825 kWh, dedicated cooling systems to 492 624 kWh, representing 44.5% of the combined consumption of 1 107 450 kWh (at a cost of U.S. $199 341). This is equivalent to the usage in a town of 852 people and constituted 4.0% of the total yearly energy consumption at the authors' hospital. Mean consumption per CT examination over 1 year was 1.2 kWh, with a mean energy cost (6standard deviation) of $0.22 6 0.13. The total energy consumption of one CT scanner for 1 year was 26 226 kWh ($4721 in energy cost). The net consumption per CT examination over 1 year was 3580 kWh, which is comparable to the usage of a two-person household in Switzerland; however, idle state consumption was fourfold that of net consumption (14 289 kWh). Mean MRI consumption over 1 year was 19.9 kWh per examination, with a mean energy cost of $3.57 6 0.96. The mean consumption for a year in the system-on state was 82 174 kWh per MRI examination and 134 037 kWh for total consumption, for an energy cost of $24 127. Conclusion:CT and MRI energy consumption is substantial. Considerable energy-and cost-saving potential is present during nonproductive idle and system-off modes, and this realization could decrease total cost of ownership while increasing energy efficiency.

Visualization is coming of age. With visual depictions being seamlessly integrated into documents, and data visualization techniques being used to understand increasingly large and complex datasets, the term "visualization"' is becoming used in everyday conversations. But we are on a cusp; visualization researchers need to develop and adapt to today's new devices and tomorrow's technology. Today, people interact with visual depictions through a mouse. Tomorrow, they'll be touching, swiping, grasping, feeling, hearing, smelling, and even tasting data. The next big thing is multisensory visualization that goes beyond the desktop.