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A federated wiki site on cPanel

Since my cPanel shared hosting provider supports node.js hosting, installing a federated wiki site beside the usual Softaculous packages is an option. The app requires node.js, and there is a variety of ways to deploy that.

In 2014, I had installed a federated wiki site on Openshift, but then didn’t maintain it as other priorities surfaced.  The site is now available at http://wiki.coevolving.com, and the prior content has been restored.

The installation isn’t a one-button procedure.  However, an administator comfortable with opening an SSH terminal onto your shared hosting account should be able to follow the steps below.  (If you have problems, the federated wiki community hangs out in a room on matrix.org).

A. Creating a Subdomain

(1) Through your browser, from cPanel … Domains … , create a Subdomain.

  • As an example, I can create a Subdomain wiki in the Domain coevolving.com, that will actually be stored in my Home (Document Root) as a wiki.coevolving.com directory.

Subdomain_CreateASubdomain

B. Installing Federated Wiki

(2) From cPanel … Software … Setup Node.js App.

  • In the Web Applications list, Create Application.  As an example, set:
      • Node.js version: 10.11.0
      • Application mode: Production
      • Application root: wiki.coevolving.com

Since my cPanel shared hosting provider supports node.js hosting, installing a federated wiki site beside the usual Softaculous packages is an option. The app requires node.js, and there is a variety of ways to deploy that.

In 2014, I had installed a federated wiki site on Openshift, but then didn’t maintain it as other priorities surfaced.  The site is now available at http://wiki.coevolving.com, and the prior content has been restored.

The installation isn’t a one-button procedure.  However, an administator comfortable with opening an SSH terminal onto your shared hosting account should be able to follow the steps below.  (If you have problems, the federated wiki community hangs out in a room on matrix.org).

A. Creating a Subdomain

(1) Through your browser, from cPanel … Domains … , create a Subdomain.

  • As an example, I can create a Subdomain wiki in the Domain coevolving.com, that will actually be stored in my Home (Document Root) as a wiki.coevolving.com directory.

Subdomain_CreateASubdomain

B. Installing Federated Wiki

(2) From cPanel … Software … Setup Node.js App.

  • In the Web Applications list, Create Application.  As an example, set:
      • Node.js version: 10.11.0
      • Application mode: Production
      • Application root: wiki.coevolving.com

Artificial intelligence, natural stupidity

Psychologist Amos Tversky, with Daniel Kahneman, collaborated not on artificial intelligence, but on the study of natural stupidity.  Their research into cognitive biases eventually became recognized in an emerging field of behavioral economics.  In hindsight, I can claim to have received an “A” in a Ph.D. course taught by the winner of a Nobel Prize in economics.

In my first cycle of doctoral studies, I was guided at UBC by my supervisor Ken MacCrimmon into a PSYC546 “Seminar in Psychology Problems”, which was led by Danny Kahneman.  This course was offered shortly after the 1982 publication of the book Judgment under uncertainty: Heuristics and biases, edited by Daniel Kahneman, Paul Slovic, and Amos Tversky.  With Kahneman at UBC in Vancouver, and Tversky at Stanford University in the San Francisco Bay Area, the back-and-forth flights to visit each other was frequent.  I uncovered more about the relationship between the two psychology professors in reading The Undoing Project. That book describes a difficult history of university faculty offers, not only around the two collaborators, but also the accommodation of wives Barbara Gans Tversky and Anne Treisman.

Psychologist Amos Tversky, with Daniel Kahneman, collaborated not on artificial intelligence, but on the study of natural stupidity.  Their research into cognitive biases eventually became recognized in an emerging field of behavioral economics.  In hindsight, I can claim to have received an “A” in a Ph.D. course taught by the winner of a Nobel Prize in economics.

In my first cycle of doctoral studies, I was guided at UBC by my supervisor Ken MacCrimmon into a PSYC546 “Seminar in Psychology Problems”, which was led by Danny Kahneman.  This course was offered shortly after the 1982 publication of the book Judgment under uncertainty: Heuristics and biases, edited by Daniel Kahneman, Paul Slovic, and Amos Tversky.  With Kahneman at UBC in Vancouver, and Tversky at Stanford University in the San Francisco Bay Area, the back-and-forth flights to visit each other was frequent.  I uncovered more about the relationship between the two psychology professors in reading The Undoing Project. That book describes a difficult history of university faculty offers, not only around the two collaborators, but also the accommodation of wives Barbara Gans Tversky and Anne Treisman.

The impacts of platforms

Concerns in the larger research body of research on platforms often leads to a subset looking into the impacts of the platform economy.  Let’s try some more digests responding to questions.

  • A. Is a shift to platforms considered as disruptive innovation?
  • B. Do network effects lead to a platform economy of “winner take all”?
  • C. With digital platforms based in information systems, what are the opportunities for knowledge effects?
  • D. What is the logic of participation on a platform?
  • E. Should platform capitalism be seen as positive or negative?
  • F. As an alternative to platform capitalism, should platform cooperativism be considered?
  • G. In the larger context of the sharing economy, how might platform initiatives be categorized?

The rise of the platform economy may be described either by the metaphor of “We Don’t Know Who Discovered Water, But We Know It Wasn’t a Fish” or the fable of the “Boiling Frog“.

Concerns in the larger research body of research on platforms often leads to a subset looking into the impacts of the platform economy.  Let’s try some more digests responding to questions.

  • A. Is a shift to platforms considered as disruptive innovation?
  • B. Do network effects lead to a platform economy of “winner take all”?
  • C. With digital platforms based in information systems, what are the opportunities for knowledge effects?
  • D. What is the logic of participation on a platform?
  • E. Should platform capitalism be seen as positive or negative?
  • F. As an alternative to platform capitalism, should platform cooperativism be considered?
  • G. In the larger context of the sharing economy, how might platform initiatives be categorized?

The rise of the platform economy may be described either by the metaphor of “We Don’t Know Who Discovered Water, But We Know It Wasn’t a Fish” or the fable of the “Boiling Frog“.

Platforms, an emerging appreciation

The term “platform” is now popular in a variety of contexts.  What do “platforms” mean, and what research might guide our appreciation?

Let’s outline some questions:

  • A. What came before the rise of platforms?
  • B. What types of platforms are there?
  • C. Why take a platform approach?
  • D. How do platforms manifest?
  • E. Why might a platform not be viable?
  • F. How are digital and non-digital platforms different?
  • G. What don’t researchers know about digital platforms?
  • H. What are the economic consequences of the platform economy?

The articles cited below are not exhaustive, but they may give a sense of the ballpark.

A. What came before the rise of platforms?

The industrial age was typified by descriptions of “supply chains” and “value chains”, which otherwise may be called “pipelines”. Marshall Van Alstyne, Geoffrey G. Parker, and Sangeet Paul Choudary write:

… platforms differ from the conventional “pipeline” businesses that have dominated industry for decades. Pipeline businesses create value by controlling a linear series of activities — the classic value-chain model. Inputs at one end of the chain (say, materials from suppliers) undergo a series of steps that transform them into an output that’s worth more: the finished product. [….]

The term “platform” is now popular in a variety of contexts.  What do “platforms” mean, and what research might guide our appreciation?

Let’s outline some questions:

  • A. What came before the rise of platforms?
  • B. What types of platforms are there?
  • C. Why take a platform approach?
  • D. How do platforms manifest?
  • E. Why might a platform not be viable?
  • F. How are digital and non-digital platforms different?
  • G. What don’t researchers know about digital platforms?
  • H. What are the economic consequences of the platform economy?

The articles cited below are not exhaustive, but they may give a sense of the ballpark.

A. What came before the rise of platforms?

The industrial age was typified by descriptions of “supply chains” and “value chains”, which otherwise may be called “pipelines”. Marshall Van Alstyne, Geoffrey G. Parker, and Sangeet Paul Choudary write:

… platforms differ from the conventional “pipeline” businesses that have dominated industry for decades. Pipeline businesses create value by controlling a linear series of activities — the classic value-chain model. Inputs at one end of the chain (say, materials from suppliers) undergo a series of steps that transform them into an output that’s worth more: the finished product. [….]

Optimism for open sourcing

The October 2018 acquisition of Red Hat by IBM gives me hope.  Both IBM and Red Hat have been champions in promoting open sourcing behaviours.

Open sourcing is an open innovation behaviour related to, but distinct from, open source as licensing.  [Ing (2017) chap. 1, p. 1].

The label of open sourcing frames ongoing ways that organizations and individuals conduct themselves with others through continually sharing artifacts and practices of mutual benefit. The label of private sourcing frames the contrasting and more traditional ways that business organizations and allied partners develop and keep artifacts and practices to themselves.  [Ing (2017) sec. 1.2, p. 5].

The label of open source is most readily recognized from software development. An open source license allows free use, modification and sharing.  Open sourcing is a norm where the resources of system internals, e.g. artifacts and practices, are shared in a community beyond the originators.  Private sourcing is coined as a norm where the resources of system internals are reserved within a privileged group.  [Ing (2017) sec. 1.3, p.6]

This deal continues a socio-economic trajectory by IBM …

  • starting in 1993 with the Lou Gerstner expectation of “open, distributed user-based solutions” after the Chantilly meeting [Ing (2017) sec. 2.3.1, pp. 55-56];

The October 2018 acquisition of Red Hat by IBM gives me hope.  Both IBM and Red Hat have been champions in promoting open sourcing behaviours.

Open sourcing is an open innovation behaviour related to, but distinct from, open source as licensing.  [Ing (2017) chap. 1, p. 1].

The label of open sourcing frames ongoing ways that organizations and individuals conduct themselves with others through continually sharing artifacts and practices of mutual benefit. The label of private sourcing frames the contrasting and more traditional ways that business organizations and allied partners develop and keep artifacts and practices to themselves.  [Ing (2017) sec. 1.2, p. 5].

The label of open source is most readily recognized from software development. An open source license allows free use, modification and sharing.  Open sourcing is a norm where the resources of system internals, e.g. artifacts and practices, are shared in a community beyond the originators.  Private sourcing is coined as a norm where the resources of system internals are reserved within a privileged group.  [Ing (2017) sec. 1.3, p.6]

This deal continues a socio-economic trajectory by IBM …

  • starting in 1993 with the Lou Gerstner expectation of “open, distributed user-based solutions” after the Chantilly meeting [Ing (2017) sec. 2.3.1, pp. 55-56];

Innovation Learning and Open Sourcing: IoT + Cloud + Cognitive

The theme of “New Developments of Systems Thinking: From IoT to AI” at the Tenth International Symposium on Service Systems Science presented an opportunity to look at changes currently happening with contemporary technologies.  For a short talk, my agenda focused on three assertions:

  • 1. Open innovation learning, through open sourcing while private sourcing, has grown from 2001 to become mainstream
  • 2. Significant Internet of Things, cloud platforms and cognitive computing initiatives involve commercial and noncommercial contributors
  • 3. Creators, makers and remixers should consciously choose and declare conditions for derivative works

The relevance of the research for my dissertation (currently in review at Aalto University) became a frame for examining IoT, cloud and cognitive.  With both commercial and noncommercial contributors working alongside each other, content creators and makers should think ahead to conditions they wish to place on others who may derive from their works.  The previously posted slides on the Coevolving Commons have been synchronized with the digital audio recording.

The lecture and subsequent questions-and-answers are available online as web video.

For those who just want to listen, downloadable audio files (some with digitally boosted volume) are an option.

Audio

The theme of “New Developments of Systems Thinking: From IoT to AI” at the Tenth International Symposium on Service Systems Science presented an opportunity to look at changes currently happening with contemporary technologies.  For a short talk, my agenda focused on three assertions:

  • 1. Open innovation learning, through open sourcing while private sourcing, has grown from 2001 to become mainstream
  • 2. Significant Internet of Things, cloud platforms and cognitive computing initiatives involve commercial and noncommercial contributors
  • 3. Creators, makers and remixers should consciously choose and declare conditions for derivative works

The relevance of the research for my dissertation (currently in review at Aalto University) became a frame for examining IoT, cloud and cognitive.  With both commercial and noncommercial contributors working alongside each other, content creators and makers should think ahead to conditions they wish to place on others who may derive from their works.  The previously posted slides on the Coevolving Commons have been synchronized with the digital audio recording.

The lecture and subsequent questions-and-answers are available online as web video.

For those who just want to listen, downloadable audio files (some with digitally boosted volume) are an option.

Audio
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