Training data-sets

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Cynefin® training data-sets are sets of items that can be used in preliminary training sessions, in preparation for methods to be subsequently used.

A typical use is within the Butterfly stamping method.

Artifacts, typically "hexies" and sticky notes can be prepared in advance of training sessions, based on available data-sets. For that purpose, it is recommended that data-sets are stored in simple tables, so as to facilitate artifact production.

Data-set requirements

Data-set minimum requirements are:

  • 20 items (up to 60)
  • Items should be relevant to the Cynefin domains (most data sets are used for contextualization methods)
  • A certain degree of interpretation ambiguity is desirable
  • A certain level of contextual abstraction is desirable, i.e. topics unrelated with specific problems that will be part of subsequent discussions
  • Avoid culturally-sensitive, political, religious, or otherwise potentially controversial topics
  • Avoid the use of intellectual property, trade marks, etc.
  • A short description of each item

Data-set description

Each data-set is described by:

  • A "Data-set status" table, the progressive values of which are:
    • Idea - Name, brief explanation of concept, and a few sample items
    • Draft partial - Incomplete descriptions or insufficient number of items
    • Draft complete - First test use of data-set done without major issues detected
    • Published - Full data-set available on Wiki for use in a variety of contexts
    • Used - Dataset successfully used in live contexts
  • A "Data-set description" table, containing the description of the data-set fields for that specific data-set
  • A "DATA-SET" (sortable) table, containing the actual data

Data-set versioning is implicitly kept through the Wiki page history.

Data-set table column description
Main label Contains the name or a short descriptive phrase representing the data-set item, ideally in max. 50 characters
Category Optional. Qualifies the item according to a data-set-wide category, ideally in one or two words
Sub-category Optional. Qualifies the item according to a data-set-wide sub-category, ideally in one or two words
Picture Optional. Icon or stylized picture that visually describes or enriches the item. Ideally a small .svg file of aprox. 150x150px size and transparent background


Training data-set choice, filter, and customization...

Process for training data-set creation

Workflow

Method for data-set Creation
STAGE INSTRUCTION COMMENTARY & TIPS
Generate / capture ideas. Describe each idea of a new data-set with a few representative examples The output can be a text, a slide, a spreadsheet, or another graphical form, accompanied by a brief explanatory note. Idea generation can come from any source, including the subsequent steps of the process. The idea is reported in the Wiki, with the appropriate status and descriptions.
Sort ideas. Check if the generated idea is compatible with the minimum data-set requirements. Discard the idea or move it on to the next step, according to the check result. Sorting criteria and guidelines are provided in the Wiki. Dataset sorting can also result in further idea generation. The sorted idea is reported in the Wiki, with the corresponding updated status and descriptions.
Create, enrich, improve data-set. Produce a minimum data-set by adding enough items to the existing ones, and improve the existing ones as appropriate This stage can be repeated as many times as necessary. It can also result in further idea generation. The draft data-set is reported in the Wiki, with the added items, and the corresponding updated status and descriptions. The Triple eight method has been proposed as a way to perform this stage.
Execute test run. Try the new data-set in a safe-to-fail context This stage can also result in further idea generation, or can determine the need for further improvement of the data-set. The status is updated on the Wiki.
Release data-set. Publish the new data-set on the Wiki for future use The full data-set is now listed on the Wiki.

Sample data-sets

Butterfly stamping generic items (sample data-set)

Butterfly Stamping Generic Items
Data-set status
Idea Draft partial Draft complete Published Used
X X X X X
Data-set description
Main label Generic item used in Butterfly stamping method
Category (Not used)
Sub-category (Not used)
Picture (Not used)
DATA-SET - Butterfly stamping generic items
Main label Category Sub-category Picture
Star Wars - - -
Seinfeld - - -
Biotechnology - - -
Legal argument - - -
Betrayal - - -
War and Peace - - -
Virgin Ads - - -
Love - - -
Mozart - - -
Market segmentation - - -
Atonal experimentation - - -
Whale songs - - -
Survivor - - -
Memory - - -
Animals sleeping - - -
Banking ads - - -
Terrain effect on maneuvers - - -
Gosford park - - -
Communities of practice - - -
Hair shampoo ads - - -
Criminal activity - - -
Japanese game shows - - -
Beaching whales - - -
Lawyer ethics - - -
Apple computer ads - - -
Avant-garde poetry - - -
Glass blowing - - -
Web pages - - -
Consultants' reports - - -
Fairy tales - - -
Intelligence - - -
Animals feeding - - -
Catch phrase - - -
Habits - - -
M&A's - - -
24 Hours - - -
Competition - - -
Organizational change - - -
Knowledge management - - -
Banking - - -
Foreign currency exchange - - -
Portals - - -
Unknown adversary - - -
The Matrix - - -
Military orders - - -
Musical scales - - -
Mining - - -
Legislation - - -
Pitched battle - - -
Weapon system performance - - -
Clockwork orange - - -
Flute manufacturers - - -
Migration patterns - - -
Pride and Prejudice - - -
Judicial sentences - - -
Termite mounds - - -
Pulp Fiction - - -
Coca-Cola ads - - -
Symphonies - - -
Insurance - - -

Architectural landmarks (sample data-set)

Data-set idea - Architectural Landmarks
Data-set status
Idea Draft partial Draft complete Published Used
X X X
Data-set description
Main label The name of a well-known architectural landmark from any place in the world, chosen across all continents.
Category The name of the country in which the landmark is encountered
Sub-category The name of the city or place in which the landmark is encountered
Picture Optional. A vectorial icon or stylized picture that visually describes the item 150x150px size, with transparent background
DATA-SET - Architectural landmarks
Main label Category Sub-category Picture
Colosseum Italy Rome -
Taj Mahal India Agra -
Brazilian Congress Brazil Brasília -
Eiffel Tower France Paris -
Great Wall China Beijing -
Egyptian pyramids Giza Egypt -
The Shard United Kingdom London -
Casa Rosada Argentina Buenos Aires -
Aachen Cathedral Germany Aix-la-Chapelle -
Opera House Australia Sydney -
Parthenon Greece Athens -
Machu Picchu Peru Cuzco -
Hagia Sophia Turkey Istanbul -
Angkor Wat Cambodia Siem Reap -
Borobudur Indonesia Magelang, Java -
Alhambra Spain Granada -
Forbidden City China Beijing -
Pisa Leaning Tower Italy Pisa -
Sagrada Familia Spain Barcelona -
Guggenheim Museum of Bilbao Spain Bilbao -
Guggenheim Museum of New York United States New York -
Pont du Gard Nimes France -
Hadrian's Wall United Kingdom Northern England -
Pirelli Tower Italy Milan -
Chartres Cathedral France Chartres -
Temple of Kukulcán Mexico Chichén Itzá -
Pisa Leaning Tower Italy Pisa -
Fallingwater United States Mill Run, Pennsylvania -
Tower Bridge United Kingdom London -
Hungarian Parliament Hungary Budapest -
Winter Palace Russia Saint Petersburg -
Petronas Towers Malaysia Kuala Lumpur -
Sankoré Madrasah Mali Timbuktu -

Recipes and ingredients (sample data-set)

Data-set idea - Recipes and Ingredients
Data-set status
Idea Draft partial Draft complete Published Used
X
Data-set description
Main label The name of a well-known recipe from one national or regional cuisine
Category The name of the country from which the recipe is
Sub-category A brief list of key ingredients
Picture Optional. A vectorial icon or stylized picture that visually describes the item 150x150px size, with transparent background
DATA-SET - Recipes and ingredients
Main label Category Sub-category Picture
Pizza Margherita Italy Wheat flour, tomato sauce, mozzarella cheese, basil -
Chili con carne Mexico Minced beef meat, chili peppers -
Brazilian Feijoada Brazil black beans, pork meat, "paio" sausages, green cabbage, oranges -
Ratatouille France Aubergine, tomato, courgette -
Peking roast duck China Duck, pancakes, shallot, brown sauce -

Travel destinations (sample data-set)

Data-set idea - Travel destinations
Data-set status
Idea Draft partial Draft complete Published Used
X
Data-set description
Main label The name of a travel destination
Category The name of the country
Sub-category (Not used)
Picture Optional. A vectorial icon or stylized picture that visually describes the item 150x150px size, with transparent background
DATA-SET - Travel destinations
Main label Category Sub-category Picture
Berlin museum tour Germany - -
Heli-ski in Hokkaido Japan - -
Angkor Wat by bike Cambodia - -
Cancun 5-star sea resort Mexico - -
Amalfi Coast by sailing boat Italy - -

Corporate functions and departments (sample data-set)

Data-set Idea - Corporate functions and departments
Data-set status
Idea Draft partial Draft complete Published Used
X
Data-set description
Main label The name of a corporate department
Category The name of the main related corporate function
Sub-category (Not used)
Picture Optional. A vectorial icon or stylized picture that visually describes the item 150x150px size, with transparent background
DATA-SET - Corporate functions and departments
Main label Category Sub-category Picture
Large account management Sales - -
Employer branding Human resources - -
Inbound logistics application maintenance Information technology - -
Account payables Finance - -
Finished goods assembly Production - -

Product decisions sourced from practitioners across different orgs (sample data-set)

Data-set Idea - Product Decisions sourced from practitioners
Data-set status
Idea Draft partial Draft complete Published Used
X X
Data-set description
Main label A product decision
Category Unsure ... could be about time scale?
Sub-category (Not used)
Picture Optional. A vectorial icon or stylized picture that visually describes the item 150x150px size, with transparent background
DATA-SET - Product decisions sourced from practitioners
Main label Category Sub-category Picture
Challenge work that has recently shipped? Days - -
(Not) join a meeting? Hours - -
Draft a set of project requirements? Months - -
Translate research output into a visual? Hours - -
Favour the business (internal) or the customer (external)? Years - -
Balance between research and production work? Hours - -
Adopt Wardley Maps as a gatekeeper to decisions and budget? Months - -
Conduct research over time? - e.g. diary studies Weeks - -
Work on MVP or build for the long-term? Weeks - -
Create a working group of experts around a topic? Weeks - -
Evaluate our new knowledge-base tool? Days - -
Observe the competitor landscape? Weeks - -
Ignore the wishes of the product sponsor? Days - -
Stop what we are doing? Weeks - -
Grow the team? Months - -
Select product metrics? Days - -
Edit the deliverables in the business plan? Hours - -
Hire an additional team member or shrink scope? Months - -
Reorganise our priorities in the task management tool? Hours - -
Choose appropriate feedback loops? Weeks - -
Should I resign? Years - -
Ditch or keep the Alpha > Beta > Live process? Months - -
Organise a workshop? Days - -
Reorder slides in a presentation showing our progress? Hours - -
Reorder the backlog for next sprint? Weeks - -
Interview customers individually or as a panel? Weeks - -
Choose a cloud provider? Years - -
Use Miro and Trello to organise ourselves? Months - -
A/B test the colour of a submit button? Hours - -
Standardise our methodology toolkit worldwide? Months - -
Conduct a user research session? Days - -
Decide what to test next week? Weeks - -
Pitch execs on the ROI of design? Weeks - -
Create a roadmap? Months - -
Draft a training plan for a colleague? Weeks - -
Make sure the team gets X hours of face time with users every month? Months - -
Let go of a team member who isn’t adding value? Months - -
Shuffle a deck of Oblique Strategy cards? Minutes - -
Prioritise our assumptions by estimated risk? Hours - -
Stay in a Zoom meeting which doesn't seem useful? Hours - -
Respond to an email? Minutes - -
Map our "future vision" vs our existing service? Weeks - -
Choose which user journey to prototype first? Days - -
Use an HTML prototyping kit or a prototyping tool? Hours - -
Hire juniors or seniors? Months - -
Share an article to encourage colleagues to experiment more? Minutes - -
Agree how we’re going to work together as a new team? Weeks - -
How to respond to a difficult email? Weeks - -
Replatform to a new tech stack? Years - -

World urban subway networks

(IMAGE TO BE REPLACED)
Data-set status
Idea Draft partial Draft complete Published Used
X
Data-set description
Main label The name of a city with an urban metro (subway) network
Category Country
Sub-category (Not used)
Picture A small-scale subway map
DATA-SET - World urban subway networks
Main label Category Sub-category Picture
Buenos Aires Argentina - -
Vienna Austria - -
Santiago Chile - -
Beijing China - -
Chongqing China - -
Guangzhou China - -
Hong Kong China - -
Shanghai China - -
Shenzhen China - -
Paris France - -
Cologne Germany - -
Berlin Germany - -
Frankfurt Germany - -
Hamburg Germany - -
Munich Germany - -
Delhi India - -
Milan Italy - -
Nagoya Japan - -
Osaka Japan - -
Tokyo Japan - -
Mexico city Mexico - -
Moscow Russia - -
St. Petersburg Russia - -
Singapore Singapore - -
Seoul South Korea - -
Barcelona Spain - -
Madrid Spain - -
Taipei Taiwan - -
Istanbul Turkey - -
London United Kingdom - -
Boston United States - -
Chicago United States - -
Los Angeles United States - -
New York United States - -
Washington United States - -

Everyday activities sourced from participants of workshops (sample data-set)

Data-set Idea - Everyday activities sourced from participants of workshops
Data-set status
Idea Draft partial Draft complete Published Used
X X
Data-set description
Main label Every day activity
Category (Not used) could be about family, environment, materials, work, entertainment ...?
Sub-category (Not used)
Picture Optional. A vectorial icon or stylized picture that visually describes the item 150x150px size, with transparent background
DATA-SET - Everyday activities sourced from participants
Main label Category Sub-category Picture
Teaching your kids math - - -
Adopting a child - - -
Choosing a lifetime career - - -
finding a life partner - - -
Writing a book - - -
Power outage - - -
Living with roommates - - -
Learning new language - - -
Moving to a new country - - -
Planning a retirement - - -
Getting into medical school - - -
Planning your work schedule - - -
Teaching your kids math - - -
Changing a flat tire - - -
Curing cancer - - -
Mowing a law - - -
Investing in stock market - - -
New gutters on the house - - -
Children in school - bad company - - -
Children in school - no interest in learning - - -
Buying a house - - -
Death of a family member - - -
Changing brake pads on a car - - -
Getting your family to exercise - - -
Car repair - - -
Backyard work - - -
Serious health care crisis - - -
Driving home after a major earthquake - - -
Divorce in family - - -
Mountain hiking trip - - -
Out of town family visiting for a week - - -
Car winterization - - -
Creation of reading habits in children - - -
Heath care provider selection - - -
Creation of learning habits - - -
Increasing school engagement - - -
Winter wood supply - - -
Careless driving habits - - -
Family housekeeping duties - - -
Overweight remedy - - -
Tonight's dinner preparation - - -
Children trouble in school - - -
Nurse training - - -
Addressing global warming - - -
High blood pressure treatment - - -
Diabetes treatment - - -
Next reading (book) selection - - -
Planning vacations - - -
Movie selection - - -
Work estimation - - -
Aging parent care - - -
Gift shopping - - -
Buying of a new car - - -
Professional career building - - -

Art work

Data-set status
Idea Draft partial Draft complete Published Used
X X
Data-set description
Main label Art work
Domain To which domain(s) is the item relevant?
Description What is the relevance to the domain(s)?
Picture Mandatory. A vectorial icon or stylized picture that visually describes the item 100x100px size, with transparent background


Download the pictures with a square background for printing.
Download the pictures with a hexagonal background for printing.

DATA-SET - Art work
Main label Domain Description Picture
EYE SEE YOU - Perspective Playground, photokina 2018 - "Super Labyrinth“ by Morag Myerscough and Luke Morgan - Picture by Alexander Schimmeck on Unsplash Ordered The result is predictable. The piece can be reproduced by following instructions.
Alexander-schimmeck-unsplash.jpg
Bristol Street Art - Picture by Annie Spratt on Unsplash Chaos The result seems random. As it is street art, the passage of time other human additional intervention also affects it.
Annie-spratt-unsplash.jpg
Solva (Fishing Village in Pembrokeshire), 1936 by Frances Hodgkins (d. 1947) - Picture by Birmingham Museums Trust on Unslplash Complex The painting depicts an existing landscape. In order to create it, there is a part related to planning the outline of the piece, and then improvising, exploring how to represent (and not copy) reality.
Birmingham-museums-trust-unsplash2.jpg
Morgan-le-Fay, 1864 Artist: Frederick Sandys - Picture by Birmingham Museums Trust Unsplash Orderd/Complex Some part relate to an accurate representation of reality and others call upon the imagination to interpret the abstract features to something specific.
Birmingham-museums-trust-unsplash.jpg
In Summer, Kiowa, 1898 - Picture by Boston Public Library on Unsplash Orderd/Complex Some part relate to an accurate representation of reality. Others call upon the imagination to interpret the abstract features to something specific.
Boston-public-library-unsplash.jpg
Birch trees at Spot Pond, 1931 [Original picture] - Picture by Boston Public Library on Unsplash Orderd The representation is trying to get closer to what we would see in reality.
Boston-public-library-unsplash1.jpg
Tribes and Castes of India. 'Sannyasi’ a Saiva mendicant. Circa 1825 - Picture by British Library on Unsplash Orderd/Complex Some part relate to an accurate representation of reality. Others call upon the imagination to interpret the abstract features to something specific.
British-library-unsplash.jpg
A portrait of a dancing girl in a white sari with a red border, seated on a western style sofa on a terrace. Circa 1780 - Picture by British Library on Unsplash Orderd/Complex Some part relate to an accurate representation of reality. Others call upon the imagination to interpret the abstract features to something specific.
British-library-unsplash1.jpg
Urban black and white line graffiti, Los Angeles (USA) - Picture by Content Pixie on Unsplash Complex We are able to recognize faces thanks to our cognitive abilities allowing us to give meaning to abstraction. The process of creating the piece called upon some planning and some improvisation.
Content-pixie-unsplash.jpg
Nina Chanel Abnex Studio, INC. 2018-0000 - Picture by Cris Dinoto on Unsplash Ordered The result is predictable and could be reproduced by following instructions.
Cris-dinoto-unsplash.jpg
Rudolph II as Vertumnus by Giuseppe Arcimboldi (1590-1591) - Picture by Europeana on Unsplash Ordered The representation is trying to get closer to what we would see in reality.
Europeana-unsplash.jpg
A ball of energy with electricity beaming all over the place - Picture by Halgatewood on Unsplash Complex The process of creating the piece called upon some planning and some improvisation.
Halgatewood-unsplash.jpg
Layers of wheat-pasted posters on a wall, Brooklyn, NYC, USA - Picture by Jazmin Quaynor on Unsplash Chaos The result seems random. As it is street art, the passage of time and other human additional intervention also affects it.
Jazmin-quaynor-unsplash.jpg
Over the City Nocturnal - Picture by Jr Korpa on Unsplash Chaos The result seems random and couldn't be reproduced.
Jr-korpa-unsplash 2.jpg
Dreamy Tree 2 - Picture by Jr Korpa on Unsplash Complex The process of creating the piece called upon some planning and some improvisation.
Jr-korpa-unsplash.jpg
Bicycling. Aquelle print by L. Prang & Co. of a painting by Henry "Hy" Sandham, c1887. Graphics Art Collection. Library of Congress Prints & Photographs Division, Original - Picture by Library of Congress on Unsplash Complex The process of creating the piece called upon some planning and some improvisation around how to represent reality whithout trying to copy it accurately.
Library-of-congress-unsplash.jpg
Yayoi asukayama hanami. (Translated title: Third Lunar Month, Blossom Viewing at Asuka Hill). Woodcut print by Kitao Shigemasa, (1772 - 1776]). Library of Congress Prints & Photographs Division. Original - Picture by Library of Congress on Unsplash Complex The process of creating the piece called upon some planning and some improvisation around how to represent reality whithout trying to copy it accurately.
Library-of-congress-unsplash2.jpg
Learn to swim campaign. Classes for all ages forming in all pools. Poster from the Federal Art Project, (1936-1940). Library of Congress Prints & Photographs Division, Original - Picture of Library of Congress on Unsplash Ordered The result is predictible and can be reproduced by following instructions.
Library-of-congress-unsplash3.jpg
The National Parks Preserve Wild Life. Poster from the NYC: Works Progress Administration, Federal Art Project, (1936-1939]. Library of Congress Prints & Photographs Division, Original - Picture by Library of Congress on Unsplash Complex The process of creating the piece called upon some planning and some improvisation around how to represent reality whithout trying to copy it accurately.
Library-of-congress-unsplash4.jpg
Untitled - Picture by Max Kleinen on Unsplash Chaos The result seems random and couldn't be reproduced.
Max-kleinen-unsplash.jpg
First. First of Many, I guess?, Unknown (2015) Montreal, Canada - Picture by Mr Tt on Unsplash Ordered/Complex The process of creating the piece called upon some stricter planning and some improvisation around how will come next.
Mr-tt-unsplash.jpg
Untitled - Picture by Oleg Laptev on Unsplash Ordered The result is predictible and can be reproduced by following instructions.
Oleg-laptev-unsplash.jpg
Brick wall painting of faces - Picture by Oliver Cole on Unsplash Complex We are able to recognize faces thanks to our cognitive abilities allowing us to give meaning to abstraction. The process of creating the piece called upon some planning and some improvisation.
Oliver-cole-unsplash.jpg
Untitled - Picture by Pawel Czerwinski on Unsplash Chaos The result seems random and couldn't be reproduced.
Pawel-czerwinski-unsplash.jpg
Untitled - Picture by Dids on Pexels Chaos The result seems random and couldn't be reproduced.
Dids-pexels.jpg
Untitled - Picture by Eberhard Grossgasteiger on Pexels Complex We are able to recognize the objects thanks to our cognitive abilities allowing us to give meaning to abstraction. The process of creating the piece called upon some planning and some improvisation around how to provide an impression of what it is whithout copying it accurately.
Eberhard-grossgasteiger-Pexels.jpg
Untitled - Picture by Karolina Grabowska on Pexels Chaos The result seems random and couldn't be reproduced.
Karolina-Grabowska-Pexels.jpg
Untitled - Picture by Luis Quintero on Pexels Chaos The result seems random and couldn't be reproduced.
Luis-Quintero-Pexels.jpg
Untitled - Picture by Nick Collins on Pexels Chaos The result seems random and couldn't be reproduced.
Nick-Collins-Pexels.jpg
Untitled - Picture by Steve Johnson on Pexels Chaos The result seems random and couldn't be reproduced.
Steve-Johnson-Pexels.jpg
Untitled - Picture by Steve Johnson on Unsplash Chaos The result seems random and couldn't be reproduced.
Steve Johnson on Unsplash.jpg
Rapid Ice Movement on Russian islands in the Arctic Ocean - Picture by Usgs on Unsplash Chaos The result seems random and couldn't be reproduced.
Usgs on Unsplash.jpg