@IBM @nuriaoliver After #cdsEurope: #DeepThinking under the Bonnet of ‘Uncluttered Diagrams’ – comparing with @IBMWatson

I have called myself a ‘passionate and compulsory networker’, connecting ideas, people and computers long before the internet was born…

In the age of Twitter and LinkedIn I have learned “Publish, don’t Send” from ‘white hacker’ James A Cattell and thus write ‘link language’ to refer to longer texts.

After Mark Wall’s excellent presentation on ‘outthinking’ and Cognitive Business @ IBM, I learned about IBM Watson. Nice after recently indulging in Sherlock Holmes movies!

Insights into the business language of data Officers, Analysts and Scientists were most fascinating:

  • e.g. people advocate ‘predictive analytics’ – while I have one method for ‘predicting’ / projecting or forecasting time series
  • and another one to ‘analyse visually’ by layering multi-dimensional data – with added functionality for ‘prioritising visually’ besides adding new metrics.

These are the most recent links to my ‘uncluttered diagrams‘ that would add ‘visual value‘ to any set of numbers in a spreadsheet:

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Posted in Big data, Data Profiling, Forecasting, IBM, IBM Watson, Layering Complex Data | 1 Comment

#cdsEurope Day Two ends in ‘Big Data for Social Good’: Data Officers, Analysts and Scientists = MYTH BUSTERS!

16-09-13-chief-data-scientist-day-2First speaker Armando Vieira from Bupa Global, a health insurance company, about Deep Learning and Artificial Intelligence.

Second speaker Dan Kellett from Capital One – promising ‘certainty’ in the credit card market – by combining the understanding of statistics with the understanding of data.

His Venn diagram says:

  • Data Scientist = Machine Learning + Coding + Data Engineering

He advocates using the right tool! Here is a catalogue of data analytics toolsContinue reading

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Believing in #DataScience or Understanding Humans – is that the Question? #CDSEurope @openDATA

16-09-13-chief-data-scientistChief Data Scientist Europe is a two-day event at Kensington Close Hotel that I am attending.

How do I LOVE being stimulated by talks about ‘data science’ and its implications for humanity’s thinking and evolution!

The first speaker came from a Recruitment Agency and addressed

  • predictions regarding human behaviour as employees;
  • to ‘entertain’ the audience, he asked who believes to be a better driver than others…

The second speaker was a mathematician who had become a marketeer and spoke about

  • how to ask the right question when marketing the Premier League
  • how football fans behave was the ‘right’ question to ask!

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Doodling with @jaCattell to develop #SmartKnowledgeWikis for structured #openData for #openDefra in #openCulture style

The Russian Dolls illustrate ‘nesting’ and ‘drilling down’ as well as the transition from perceptions in 3D space and visualisations on 2D screens

James Arthur Cattell calls himself a ‘government hacker’. Typical for his age group, he did not only grow up with computers, but also learned to write code before he would have learned about Shakespeare.

He is an ‘evangelist’ of #openDATA and #openCULTURE and facilitates ‘unConferences’ to encourage both.

I met him at the openDEFRA event when he invited me into the DataCave that serves as an open space for co-creativity – across the many governmental departments – despite the dispersion of team members nationwide.

The last time I had met him at the Open Data Institute where we heard the Friday lunchtime lecture on Who Owns your Reputation?

Thanks to James, I met Russian Irina Bolychevsky who inspired me to bring a set of Russian Dolls as a tool to explain my proposal about openDfT: to make better transport policy by gathering, preparing, visualising and interpreting transport data using 3dM Diagrams.

As a result, I’ve updated my response to the techUK paper on the ‘Big Data Supply Chain’ into Smart Knowledge Wikis.

And James tweeted: do you doodle?

Doodling with James Arthur Cattell on 28 July 2016 in the DataCAVE

Adding to the corridor wall – as ‘real time blogging’ in 3D space

 

Posted in 3D Metrics, Big data, Data Profiling, DEFRA, Layering Complex Data, Open data | Leave a comment

@openDEFRA with #openDATA in #openCULTURE: Valuing #Data #Life and #Internet over #Money

cmcxuw_wkaagcbfThis unconference on Tuesday 28 June in an open space of the Nobel House at Smith Square in Central London was more than a shot in the arm:

  • it gave me hope that my faith in people and the internet is justified for our children’s and grandchildren’s future;
  • while I’ve analysed the long term organisation of man-made evil and its victims for a considerable length of time, I can now pin my hopes on the humanness of ‘geeks’ – in governmental settings:
  • Be bold, be human, be your Self is the motto that  James Arthur Cattell got from the UK Civil Service Leadership Statement;
  • James is a ‘government hacker’ and had facilitated the event most admirably and charmingly;
  • these DEFRA geeks are using social media in very effective and creative ways:

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Posted in 3D Metrics, DEFRA, Open data | 1 Comment

Benefits of ‘3D Metric’ Diagrams: Linking Data Silos for Improved Policy Making

16 04 09 Benefits Diagrams-page-001The gap between scientific and business language does not seem to narrow despite computer screens as the common medium:

  • big business data‘ seems to concentrate on ‘non-structured‘ data relating to patterns of consumption, as growth of profit, turnover and productivity are the ‘mantras’ in companies that are expected to sell or be bought up…
    • very big science data‘, however, consists in my view mainly of ‘structured‘ data, i.e. time series:
    • financial or originating from sensors: measurements from instruments;
    • but ‘big business data’ can ALSO be expressed in time series;
    • altogether:
      • better business strategy decisions can be taken
      • better policy can be made
      • and who knows what scientific improvements can be made!?…better

On the Benefits of ‘3dM Diagrams’

 21 layers 3 pollutants Excel  21 layers 3 pollutants 3dM

3dM Diagrams ‘unclutter’ Excel graphs:
e.g. data from the London Air Quality Network

 21 layers 3 pollutants 3dM  21 layers Sorted

3dM Diagrams create ‘visual priorities’ and new insights for ‘optimal slopes’.
This leads to ‘domain experts’ determining novel parameters for automated processing.

3dM Diagrams are generic, i.e. independent of domain and of time scales.
They can include forecasts derived from new algorithms.Thus they allow for:-·       linking ‘data silos’ and comparing different time frames – which leads to

Ø   contrasting short, medium and long term trend periods defined by ‘domain experts’;

·       ‘data experts’ discovering correlations – which leads to

Ø   defining ‘optimal slopes’ for automating ‘big data’ and real time processing;

·       enhancing processes that influence interdependencies – which leads to

Ø   improving policy by making better informed decisions from connected data silos.

3dM Diagrams illustrate for Domain and Data Experts
what Executive Summaries demonstrate for Policy Makers:
Key Findings as the Basis for Executive Decisions

 

Posted in Data Visualization, Forecasting, Layering Complex Data, Trend Analysis | Tagged | 3 Comments