Wednesday, April 30, 2008

Characteristics of Knowledge Ecology

Some of the key characteristics underlying the notion of knowledge ecology may be deduced from the characteristics of (a) knowledge and (b) ecology. Although there is no common definition of the term knowledge, there is a wide agreement that knowledge is social, personal, flexible, dynamic, decentralized, ubiquitous, networked, and complex in nature (Chatti et al., 2007). An ecology is an open, complex adaptive system comprising elements that are dynamic and interdependent (Brown, 1999). Key characteristics of knowledge ecology include: complexity, adaptation, emergence, self-organization, openness, and decentralization.

Complexity and adaptation: Knowledge ecology is a good example of a complex adaptive system (Holland, 1995). In a complex adaptive system, the behavior of the whole is much more complex than the behavior of the parts. Knowledge ecology is complex in that it is diverse and made up of multiple interconnected elements and adaptive in that it has the capacity to change and learn from experience (Holland, 1995; Holland, 1998). Knowledge ecology is also a complex system comprising many interacting identities in which cause and effect relationships cannot be distinguished (Snowden, 2002). Knowledge ecology thus has a non-deterministic character; it can evolve in ways that we may not expect or predict.

Emergence and self-organization: Emergence is central to the theory of complex adaptive systems (Holland, 1998). Goldstein (1999) defines emergence as "the arising of novel and coherent structures, patterns and properties during the process of self- organization in complex systems". Emergent properties are irreducible. As Lewes (1875) puts it: "The emergent is unlike its components in so far as these are incommensurable, and it cannot be reduced to their sum or their difference". Holland (1998) argues that emergence must be the product of self-organization, not centralized control (cited in Ryan, 2007). Thus, as an example of a complex adaptive system, knowledge ecology holds emergent properties and includes self- organized entities. Knowledge ecology is co-constructed and maintained by individuals. It emerges naturally and is derived from the bottom-up networking of multiple personal knowledge networks. Knowledge ecology houses the learning that occurs in a bottom-up and emergent manner, rather than learning that functions within top-down and hierarchical structures under the control mechanisms of outside forces.

Openness and decentralization: As with complex systems, ecologies are open and their boundaries are difficult to be determined. And, knowledge is decentralized and ubiquitous in nature. Thus, openness and decentralization are central attributes in knowledge ecologies.


Chatti, M. A., Jarke, M. & Quix, C. (submitted). Connectivism: The Network Metaphor of Learning.


Brown, J. S. (1999). Learning, Working & Playing in the Digital Age. AAHE Conference on Higher Education, Washington, D.C.

Chatti, M. A., Jarke, M. & Frosch-Wilke, D. (2007). The future of e-learning: a shift to knowledge networking and social software. International Journal of Knowledge and Learning, 3(4/5), 404-420.

Goldstein, J. (1999). Emergence as a Construct: History and Issues. Emergence: Complexity and Organization, 1(1), 49-72.

Holland, J. H. (1995). Hidden Order: How Adaptation Builds Complexity. MA: Addison-Wesley.

Holland, J. H. (1998). Emergence: From Chaos to Order. MA: Addison-Wesley.

Lewes, G. H. (1875). Problems of Life and Mind. Vol. 2. London: Kegan Paul, Trench, Turbner, & Co.

Ryan, A. J. (2007). Emergence is coupled to scope, not level: Research Articles. Complexity, 13(2), 67-77.

Snowden, D. J. (2002). Complex Acts of Knowing: Paradox and Descriptive Self-Awareness. European Conference on Knowledge Management, Dublin, Ireland.

Tuesday, April 29, 2008

Knowledge Ecology Definition

At the heart of the LaaN perspective lie knowledge ecologies.
We define knowledge ecology as a complex, knowledge intensive landscape that emerges from the bottom-up networking of personal knowledge networks.


Chatti, M. A., Jarke, M. & Quix, C. (submitted). Connectivism: The Network Metaphor of Learning.

Monday, April 28, 2008

Web 2.0 and collective intelligence

A podcast of the chat between Jay Cross and Chris Heuer at Web 2.0 Expo talking about "building on-line communities, enterprise 2.0, coping with mind-blowing change, the relationship with informal learning, etc."

Friday, April 25, 2008

Top 10 Knowledge Management Myths

Mary Abraham cites Jean E. Engle and Ed Rogers from the NASA/Johnson Space Center, who provide a list of "Top 10 Knowledge Management Myths":

10. Culture can be mandated from the top
9. Collaboration can be "purchased" or "sharing can be rewarded"
8. KM can be outsourced
7. Anybody (who isn't busy) can do KM
6. KM can be solved by buying the right software
5. KM can be independent of the business process
4. Communities of practice can be established by the top
3. KM is about centralizing knowledge content to use it more efficiently
2. KM is really about databases
1. KM is an IT function and should be given to the CIO

A detailed discussion of the Myths can be found here.

Thursday, April 24, 2008

DataPortability Project

A press release to present the progress within the DataPortability project as of November 2007.

Six months from its start, the DataPortability Project has advanced the conversation about user data rights. The project's volunteers have worked together to develop a uniquely open, transparent and effective community; earn support from standards groups and vendors; initiate documentation of technical best practices; and introduce a trustmark for the data web. DataPortability Connect.Control.Share.Remix

Wednesday, April 23, 2008

E-Learning 2.0 at Educamp 2008

Via George Siemens and Stephen Downes.

Recordings of presentations by George Siemens, Stephen Downes, Henry Jenkins, John Seely Brown and others at Educamp 2008 in Germany.

Tuesday, April 22, 2008

Building a collaborative workplace

Via Stephen Downes.

A good Anecdote white paper (.pdf) by Shawn Callahan, Mark Schenk, and Nancy White, entitled "Building a collaborative workplace".

This paper has three parts. We start by briefly exploring what we mean by collaboration and why organisations and individuals should build their collaboration capability. Then, based on that understanding, we lay out a series of steps for developing a collaboration capability. We finish the paper with a simple test of your current collaboration capability.

Monday, April 21, 2008

Skills 2.0

A nice article (.pdf) by Harold Jarche entitled "Skills 2.0". Harold writes:

Today, active involvement in informal learning, particularly through webbased communities, is key to remaining professional and creative in a field. Being a learning professional in a Web 2.0 world is becoming more about your network than your current knowledge.

Friday, April 18, 2008

Google App Engine vs. Amazon EC2 (2)

Another nice post by Dion Hinchcliffe where he compares Google and Amazon Platform-as-a-Service (PaaS) offerings, i.e. Google App Engine vs. Amazon Elastic Compute Cloud.

related posts:

Thursday, April 17, 2008


A nice post by Dion Hinchcliffe on the shift from Service-Oriented Architecture (SOA) to Web-Oriented Architecture (WOA).

Wednesday, April 16, 2008

Google App Engine vs. Amazon EC2


In his blog, Brad Feld publishes the text of an email from Scott Moody comparing Google App Engine and Amazon EC2. Here is the text as published by Brad:

Google hides infrastructure from AppEngine users. AE programmers never (and, in fact, aren't allowed to) think about database scaling and configuration, load balancing , fail-over, etc. In theory, the complexity of writing a highly scalable app completely disappears.

With EC2, you still have to set-up load balancers, configure multiple replicated database servers, implement scalability hacks if things grow too fast (such as distributed caching of data via memcached), keep distros and apps up-to-date, etc. Bottom Line: EC2-based companies still require sys admins, AppEngine companies don't. That will certainly change as more companies begin offering EC2 server management services.

Google provides a non-relational datastore and that's the only datastore available (no traditional file system, no relational databases). With EC2, people generally use MySQL or Postgresql. Amazon offers a non-relational datastore called SimpleDB, but it's a bit *too* simple. For example, it does not support sorting of results sets. Huh? That makes it non-workable in my opinion. There's also an issue with using EC2 virtual machines for your database servers -- Amazon says that when a virtual machine crashes, all the data managed by it disappears, so virtual machine crash = hard drive crash.

With EC2, programmers can use any (non-Microsoft) language to develop their apps. AppEngine users must code in Python. Also, Google does not support sockets at this time. All cross-app communication must be done via HTTP.

At *this* moment in time, it would be difficult to move apps off of AppEngine. Doing that in EC2 is trivial. This, to me, is the biggest issue, as I believe it could make startups less-interesting from an acquisition perspective by anyone other than Google. This will most likely change as people develop compatibility layers. However, Google has yet to provide any information about how to migrate data from their datastore the best I can tell. If you have a substantial amount of data, you can't just write code to dump it because they will only let any request run for a short period before they terminate it.

Some people are complaining about Google having access to their source code. I don't see this as an issue. I'd rather have it be stored at Google than at some small hosting company.

One final nice little thing in AppEngine's favor: Websites that store less than 500MB of data and get roughly 5MM pageviews per month or less can use AppEngine for free. The downside is that Google has yet to say what they'll charge if apps go over that quota, but I have to believe that it will be reasonable. Right now, you're prevented from going above the free-level quotas.

Tuesday, April 15, 2008

RSS Tips

Monday, April 14, 2008

NetBeans now supports JavaScript

Via - Screenshot of the Week #28: NetBeans + JavaScript = True!
- NetBeans 6.1: A JavaScript IDE

Friday, April 11, 2008

KM 2.0

A nice presenation by Ray Sims on KM and Web 2.0 (available via Slideshare).
Thanks for sharing this Ray!

Thursday, April 10, 2008

A chaque continent ses préférences

Via Tim O'Reilly.

A nice visualization of the adoption of social networking sites in the different continents, from Le Monde:

Wednesday, April 09, 2008

Google App Engine at Campfire One

At Google Campfire One, Google launched a preview release of Google App Engine, "a developer tool that enables you to run your web applications on Google's infrastructure".

More details from the new Google App Engine Blog:

Google App Engine is a developer tool that enables you to run your web applications on Google's infrastructure. The goal is to make it easy to get started with a new web app, and then make it easy to scale when that app reaches the point where it's receiving significant traffic and has millions of users.

Google App Engine gives you access to the same building blocks that Google uses for its own applications, making it easier to build an application that runs reliably, even under heavy load and with large amounts of data. The development environment includes the following features:

  • Dynamic webserving, with full support of common web technologies
  • Persistent storage (powered by Bigtable and GFS with queries, sorting, and transactions)
  • Automatic scaling and load balancing
  • Google APIs for authenticating users and sending email
  • Fully featured local development environment
Google App Engine packages these building blocks and takes care of the infrastructure stack, leaving you more time to focus on writing code and improving your application.

Videos announcing Google App Engine at Campfire One on April 7, 2008

Campfire One: Introducing Google App Engine (pt. 1)

Campfire One: Introducing Google App Engine (pt. 2)
Campfire One: Introducing Google App Engine (pt. 3)
Campfire One: Introducing Google App Engine (pt. 4)
Campfire One: Introducing Google App Engine (pt. 5)
Campfire One: Introducing Google App Engine (pt. 6)

Tuesday, April 08, 2008

WEBIST 2008 Program

The program of the 4th International Conference on Web Informations Systems and Technologies (WEBIST 2008) is now available at:
I'll be presenting there our paper "Towards Web 2.0 Driven Learning Environments".


Over the last decade, it has been widely argued that technology-enhanced learning could respond to the needs of the new knowledge society and transform the way we learn. However, despite isolated achievements, technology-enhanced learning has not really succeeded yet in revolutionizing our education and learning processes. In fact, most current initiatives do not focus on the social aspect of learning and learning content is still pushed to a pre-defined group of learners in closed environments. Recently, Web 2.0 concepts have started to open new doors for more effective learning and have the potential to overcome many of the limitations of traditional learning models. In this paper we show in which way the community-driven platform Learnr, under development at the University of Münster, puts crucial success factors for future technology enhanced learning into practice, applying well known concepts like networking and social tagging. As a consequence, a Web 2.0 perspective on learners, learning content and learning communities can be derived.


M.A. Chatti, D. Dahl, M. Jarke, G. Vossen: Towards Web 2.0-Driven Learning Environments (Proc. 4th International Conference on Web Information Systems and Technolgies (WEBIST), Funchal (to appear)), 2008

Monday, April 07, 2008

OpenID Providers

Sarah Perez from ReadWriteWeb has recently compiled a good list of OpenID providers, resources, and major sites supporting this authentication standard. More information about OpenID is available here.

Thursday, April 03, 2008

Knowledge Management Definition

Ray Sims has done a great job in collecting 50+ different published definitions of Knowledge Management. This long list shows that KM is hard to define in a precise way. Web 2.0 is facing the same problem. There is still no clear definition of the term. Is this a sign that Web 2.0 will go the way of KM; i.e. much hype (in the 90s) followed by a slow death?
In my opinion, the difficulty to find a common definition for KM is mainly due to an attempt to define something that
doesn't exist or at least cannot happen. Unlike "Information", "Knowledge" cannot be managed. Knowledge is a complex entity. Management cannot work while dealing with complex entities/systems. In this case, networking is the solution. In an earlier post, I suggested a move away from "Knowledge Management" to "Knowledge Networking" and noted that these two perspectives differ from each other on four dimensions:

  • Focus
  • Core Knowledge Activity
  • Enabler
  • Target Group

Wednesday, April 02, 2008

SoSEA 2008

The First International Workshop on Social Software Engineering and Applications (SoSEA 2008 in conjunction with ASE 2008 L'Aquila, Italy, September 15, 2008

Paper submission (deadline): June 15, 2008.

Social software has emerged as one of the most exciting and important phenomenon in today's software and business arena. With social software, individuals can interact, share, and meet other individuals, presumably with similar interests, forming large data, knowledge, and user bases. Social software engineering, in turn, can be defined as the application of processes, methods, and tools to enable community-driven creation, management, deployment, and use of software in online environments.

The social software movement can be regarded as both a challenge and an opportunity for software development. On the one hand, social software itself brings its own kinds of challenges such as data sensitivity, content legality, scalability, and performance. On the other hand, the social software movement is apparently causing a fundamental change in the way software engineering is practiced, benefiting from the technologies and experiences gained from Web 2.0 and the expectations of the forthcoming Web 3.0. In the near future, various forms of social software development will become a reality. Examples include software mashups, intelligent context-aware software downloads, and online cooperative CASE tools. Such a cooperative model of software development would also meet the challenges of contemporary software engineering such as outsourcing, offshoring, open source software, etc. Due to its distributed nature, automated approaches to social software engineering are needed.

The goal of the workshop is to bring together interested academics, practitioners, and enthusiasts to discuss topics related to the area of social software engineering. Focusing on technology issues, the workshop will offer an opportunity for the participants to share experiences and discuss challenges involved in building and using social software. A special emphasis will be put the role of social software concepts and technologies in shaping up future software development. The workshop will also identify key research issues and challenges that lie ahead.

We solicit two kinds of contributions:
* short position papers describing particular challenges, experiences, or visions relevant to the scope of the workshop (not to exceed 4 pages);
* full research papers describing original work in any aspect of social software engineering (not to exceed 8 pages).

Articles should be novel, have not been published elsewhere, and are not under review by another publication. We are negotiating with major publishers the possibility to publish extended versions of a selection of the best papers (chosen by the program committee) as post-proceedings. Papers must conform, at time of submission, to the ASE 2008 Format and Submission Guidelines. Submission instructions are available at:

The workshop will concentrate on two main themes:
* engineering of social software applications;
* the use of social software in software development, exploiting models, methodologies and technologies.

Workshop topics include (but are not limited to):
* requirements and challenges of building and using social software, including concerns such as scalability, performance, security, sensitivity and other legal issues;
* organization and interaction schemes in social software;
* automated approaches, best practices, architectures, frameworks, methodologies, technologies, tools, and environments for social software engineering;
* industrial involvement in social software: building, managing and interfacing with communities, opening up software platforms, integrating social software;
* building social software engineering communities: the role of companies, research groups, governments, NGOs, and individuals;
* social software engineering versus other forms of globalization such as global software development, distributed software engineering, open source, etc;
* experience reports and lessons on building social software and its use in software development.

Paper submission (deadline): June 15, 2008
Acceptance Notification: July 20, 2008
Final Camera-ready: August 20, 2008

Imed Hammouda,
Tampere University of Technology

Jan Bosch,
Intuit Inc.

Mehdi Jazayeri,
University of Lugano

Tommi Mikkonen,
Tampere University of Technology

Andrea Capiluppi (University of Lincoln, UK)
Björn Lundell (University of Skövde, Sweden)
Cesare Pautasso (University of Lugano, Switzerland)
Frank van der Linden (Philips Medical Systems, the Netherlands)
James D. Herbsleb(Carnegie Mellon University, USA)
Jan Bosch (Intuit Inc., USA)
Imed Hammouda (Tampere University of Technology, Finland)
Mehdi Jazayeri(University of Lugano, Switzerland)
Mohamed Amine Chatti (RWTH Aachen University, Germany)
Pekka Abrahamsson (VTT, Finland)
Tommi Mikkonen (Tampere University of Technology, Finland)