FROM the Impossible to the Imaginable: ‘Data Profiling’ Big Business and Very Big Science Data

Profiling Big Data for Business[1] and Very Big Data for Science[2]

Peaks, Troughs and Averages – independent of Application and Scale –
in new Depth, Detail and Perspective

 verti-n30-m40-300x215  Multi-dimensional sine 8d  Jouzel Selects 001 1934 diffs x sc

Vertical Data Layers along a ‘visual z-axis’

Profiling Data is based on layering complex data[3] into vertical slices along a ‘visual z-axis’. This disruptive software method processes multivariate, univariate, sequential and time series data alike. It is now apparent that its algorithms can be usefully applied to bridging knowledge gaps between finance, economics, business and science.

In particular, market data, business intelligence, medical and climate data, measurements, sensor data, experimental results, clinical and experiential data can all be visualised with more depth, detail and other advantages:

  • ‘Extreme data profiles’ show minima, maxima, averages and other statistical measures and derived metadata:
    • This allows for sorting, ranking, weighting and prioritising visually.
  • A new forecasting mechanism can be applied for short-, medium and long-term trends:
    • Overlaying these trends allows for new predictive time windows.
    • Parameters are derived from historic data to fine tune the generic approach.

In business, time is money. In life and science, knowledge is power. It is therefore a promising perspective to examine business and science related data with the same tool!

In the spirit of Humboldtian Science[4], software lenses[5] are state of the art measuring instruments to compare hitherto incomparable data and images from finance, business and science. Visual assessments by data experts, combined with numerical processing power, allow for creating ‘Smart Knowledge Portals’, e.g.:

  • Smart Particle Physics: meta views of individual as well as grouped experiments;
  • Smart Science: the data source and expertise determine domain, scale and insights;
  • Smart Energy Consumption: systems of control and communication are fine tuned and tweaked as peaks, troughs and other numerical metadata are aligned over different time spans.

It is hoped that collaboration can be created between CERN and 3D Metrics[6] to accelerate science:

PS. I took the phrase ‘from the impossible to the imaginable’ from Ben Segal‘s review of the book on How the Web was Born.

About Sabine Kurjo McNeill

I'm a mathematician and system analyst formerly at CERN in Geneva and became an event organiser, software designer, independent web publisher and online promoter of Open Justice. My most significant scientific contribution is
This entry was posted in 3D Metrics, Accelerating Science, CERN, Data Profiling, Data Science, Measurement based science, Particle Physics, Science, Smart Knowledge Systems, Smart Portals, Software Lenses, Software Vision, Web Science and tagged , , , , , , , , , , , , , . Bookmark the permalink.

3 Responses to FROM the Impossible to the Imaginable: ‘Data Profiling’ Big Business and Very Big Science Data

  1. Pingback: BANK HOLIDAY news & views – after 6 days around CERN in Geneva | Victims Unite!

  2. Pingback: OPEN LONDON: the invitation for Open Investigation? | 3D Metrics

  3. Pingback: NUMERICAL METADATA for Meta Views of Big and Very Big Data |

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