Coevolving Innovations

… in Business Organizations and Information Technologies

Positioning “A Pattern Language” more like “Creating Order of”, then “The Timeless Way of Building” more like “Negotiating Order with”, was a productive framing to discuss the systems theory inside Christopher Alexander’s thinking (as well as positioning “The Nature of Order“).

The purpose of a workshop on “Negotiating Order with Generative Pattern Language” at PLoP 2017 was to open up discussions that could deepen the foundational understanding in linkages between pattern language and systems thinking. At least three of us routed to Vancouver BC for a Monday morning start, in a quick trip from the Purplsoc meeting in Austria that finished on Saturday.  The PLoP program emphasizing writers’ workshops meant that our 90-minute dialogue didn’t conflict with any presentations.

On the audio recording, active participants in the sensemaking included Helene Finidori and Christian Kohls.  With a more relaxed pace, the open time after the slides were completed allowed some pattern language novices to also have questions answered.

PLoP 2017

The frame for discussion was slides that had previously been posted on the Coevolving Commons.

The digital audio recording has been matched up with slides, for a less ambiguous viewing as a web video.

March 10th, 2018

Posted In: pattern language, systems

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Pattern language is not for wicked problems, said Max Jacobson, coauthor with Christopher Alexander of the 1977 A Pattern Language: Towns, Building, Construction.  In addition, the conventional definition of an Alexandrian pattern as “a solution to a problem in context” when applied to social change might better use the term “intervention”, rather than “solution”.

These are two of the major ideas that emerged at Purplsoc 2017 conference last October.  A 90-minute workshop was run in parallel with other breakouts.

For about the first hour, vocal participants included Max Jacobson (who had given a plenary talk on “A Building is not a Turkish Carpet“), Christian Kohls (who gave a plenary talk on “Patterns for Creative Space“) and Peter Baumgarnter (one of the Purlpsoc chairs).

As an impetus to discussion, we stepped through slides that had been posted on the Coevolving Commons.

For people who would like the next-best experience to being there, the slides have now been matched up with the digital audio recording, for viewing as a web video.

For devices decoupled from the Internet, downloadable video files are portable.

Video H.264 MP4 WebM

March 3rd, 2018

Posted In: pattern language, philosophy, systems

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What if a pattern language was opened up to contemporaneous research into wicked problems, the systems approach, ecological epistemology, hierarchy theory, and interactive value?  This 30-minute presentation at Purplsoc 2017 last October aimed to provide a broader context to a social change community focused on works of Christopher Alexander.

This talk was a complement to “Pattern Manual for Service Systems Thinking” presented a year earlier, at PUARL 2016.  Last year, the agenda was centered on the approach from Christopher Alexander, and divergences due to the changing in domain from the built environment to service systems.

The slides on the Coevolving Commons are dense.  I had showed them at the poster session in the day preceding, and promised to spend more time speaking to them in the workshop scheduled for the next day.

For 2017, the view looked beyond Alexander, to related research both at Berkeley, and elsewhere in the systems community.  The agenda was in 3 major sections (here expanded with more detailed overview of the middle section):

  • 1. What is multiparadigm inquiry?
  • 2. Where have (and might have) (1960s-2010s) paradigms influenced generative pattern language?
    • a. Over 50 years, Christopher Alexander and coauthors evolved concepts and language in built environments

January 19th, 2018

Posted In: pattern language, services, systems

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At U.C. Berkeley in the 1960s, Christopher Alexander, Horst Rittel and C. West Churchman could have had lunch together.  While disciplinary thinking might lead novices to focus only on each of pattern language, wicked problems and the systems approach, there are ties (as well as domain-specific distinctions) between the schools.

Circa 1968-1970: Christopher Alexander, Horst Rittel, West Churchman

Circa 1968-1970: Christopher Alexander, Horst Rittel, West Churchman

West Churchman joined Berkeley in 1957, and initiated master’s and doctoral programs in operations research at the School of Business Administration.   From 1964 to 1970, Churchman was associate director and research philosopher at UC Berkeley’s Space Sciences Laboratory, directing its social sciences program.  After his retirement in 1981, Churchman taught in the Peace and Conflict Studies program for 13 years.

Horst Rittel came to the Berkeley College of Environmental Design in 1963, the same year that dean William Wurster recruited Christopher Alexander.  In 1973, Rittel split his time between Berkeley and the architecture faculty at the University of Stuttgart, where he founded the Institut für Grundlagen der Planung.

Christopher Alexander became a cofounder of the Center for Environmental Structure at Berkeley in 1967, gradually moving outside of the university by 2000.

The tie between Churchman and Rittel are well-documented, in a 1967 article in Management Science.

Professor Horst Rittel of the University of California Architecture Department has suggested in a recent seminar that the term “wicked problem” refer to that class of social system problems which are ill-formulated, where the information is confusing, where there are many clients and decision makers with conflicting values, and where the ramifications in the whole system are thoroughly confusing. The adjective “wicked” is supposed the describe the mischievous and even evil quality of these problems, where proposed “solutions” often turn out to be worse than the symptoms. [p. B-141]

October 14th, 2017

Posted In: pattern language, systems

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Making my dissertation relevant to non-academics calls for a change in style.  An invitation to speak at the Open Data Häme workshop, following announcement of funding by the European Regional Development Fund, gave a venue to unveil some normative theory-building from my research potentially useful in the real world.

This talk was fewer slides, and more talk.  With 9 content slides to cover in about an hour, the agenda was:

  • 1. Why does open data mean open sourcing (with commercial potential)?
  • 2. When did open data begin? What’s the history?
  • 3. How do behaviours change with open innovation learning?

The slides had been posted on the Coevolving Commons in advance of the event.

The slides has now been matched up with the digital audio recording, for viewing as a web video.  Another voice in the mix is Minna Takala, as a Senior Advisor at Häme Regional Council.

The audio recording was exceptionally clear, and is downloadable (so boosted volume is probably unnecessary).

Digital audio
[20170810_Hame_Ing mp3] (58MB)
[20170810_Hame_Ing 3db mp3] (volume boosted 3db, 58MB)
[20170810_Hame_Ing 6db mp3] (volume boosted 6db, 58MB)

Alternatively, downloadable video files may be better for people on the move.

Video H.264 MP4 WebM
Digital video
[Hame_Ing_HD  m4v]
(HD 325Kbps 238MB)
[20170810_Hame_Ing_nHD m4v]
(nHD 109Kkps 97MB)
[20170810_Hame_Ing webm]
(HD 470Kbps 212MB)
[20170810_Hame_Ing nHD webm]
(nHD 177Kbps 80MB)

The first part of the talk places open data in the larger context and trend towards the behaviour of open sourcing, and open innovation. Open sourcing enables visibility into system internals, in contrast with private sourcing that makes internals opaque.  The rise of open sourcing became more noticeable with the advent of open source licensing in software, but can generalized outside of technology with an example of raising and catching salmon.

September 2nd, 2017

Posted In: innovation

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For the Quantitative Methodologies for Design Research (定量研究方法) course for Ph.D. students at Tongji University in spring 2017, Susu Nousala invited me to join the team of instructors in collaborative education in Shanghai.  Experts were brought in during the course to guide the graduate students.

My participation in the course over two days had three parts:  (a) preparing a lecture outline; (b) orienting the students; and (c) equipping the students with tools.

(A) Preparing a lecture outline

While I’m comfortable with the mathematics underlying statistical analysis, I have a lot of practical experience of working with business executives who aren’t.  Thus, my approach to working with data relies a lot on presentation graphics to defog the phenomena.  While the label of data science began to rise circa 2012, I’ve had the benefit of practical experience that predates that.

Today's APL

AGSS: A Graphical Statistical System (1994)

In my first professional assignment in IBM Canada in 1985, data science would have been called econometrics.  My work included forecasting country sales, based on price-performance indexes (from the mainframe, midrange and personal computer product divisions) and economic outlooks from Statistics Canada.  Two years before the Macintosh II would bring color to personal computing, I was an early adopter of GRAFSTAT: “An APL system for interactive scientific-engineering graphics and data analysis” developed at IBM Research.  This would eventually become an IBM program product by called AGSS (A Graphical Statistical System) by 1994.

Metaphor Computer Systems workstation

Metaphor Computer Systems workstation

In 1988, I had an assignment where data science would have been called marketing science.  I was sent to California to work in the IBM partnership with Metaphor Computer Systems. This was a Xerox PARC spin-off with a vision that predated the first web page on the World Wide Web by a few years.  These activities led me into the TIMS Marketing Science Conference in 1990, cofounding the Canadian Centre for Marketing Information Technologies (C2MIT) and contributing chapters to The Marketing Information Revolution published in 1994.

This journey led me to appreciate the selection and use of computer-based tools for quantitative analysis.  Today, the two leading platforms in “Data Science 101” are Python (a general purpose language with statistical libraries), and the R Project for Statistical Computing (a specialized package for data analysis and visualization).  Both are open source projects, and free to download and use on personal computers.  I tried both.  R is a higher level programming language more similar to the APL programming language that gets work done more quickly.  For statistical work, I recommend R over Python (although APL is a theoretically better implementation).

Intro to R Programming, Big Data University

Intro to R Programming, Big Data University, Feb. 22, 2017

Since I live in Toronto, I attended the February session of Data Science with R – Bootcamp in person, at Ryerson University.  There, I was watched Polong Lin leading a class through R using the Jupyter notebook, both in (i) an interactive version, and (ii) a printable version.  Students had the choice to either follow Polong (i) actively, in a step-by-step execution in the Cognitive Class Virtual Lab (formerly called the Data Scientist Workbench) with a cloud-based R session through their web browsers, or (ii) passively, reading the static printable content.

August 26th, 2017

Posted In: universities

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