Nearly a year ago I wrote a short essay entitled The Four Principles of (Open) Knowledge Development in which I proposed that the four key features features of a successful (open) knowledge development process were that it was:

  1. Incremental
  2. Decentralized
  3. Collaborative
  4. Componentized

As I emphasized at the time the most important feature — and currently least advanced — was the last: Componentization. Since then I’ve had the chance to discuss issue further, most recently and extensively at Open Knowledge 1.0 and this has prompted me to re-evaluate and extend the ideas I put forward in the original essay.

What Do We Mean By Componentization?

Componentization is the process of atomizing (breaking down) resources into separate reusable packages that can be easily recombined.

Componentization is the most important feature of (open) knowledge development as well as the one which is, at present, least advanced. If you look at the way software has evolved it now highly componentized into packages/libraries. Doing this allows one to ‘divide and conquer’ the organizational and conceptual problems of highly complex systems. Even more importantly it allows for greatly increased levels of reuse.

The power and significance of componentization really comes home to one when using a package manager (e.g. apt-get for debian) on a modern operating system. A request to install a single given package can result in the automatic discovery and installation of all packages on which that one depends. The result may be a list of tens — or even hundreds — of packages in a graphic demonstration of the way in which computer programs have been broken down into interdependent components.


Atomization denotes the breaking down of a resource such as a piece of software or collection of data into smaller parts (though the word atomic connotes irreducibility it is never clear what the exact irreducible, or optimal, size for a given part is). For example a given software application may be divided up into several components or libraries. Atomization can happen on many levels.

At a very low level when writing software we break thinks down into functions and classes, into different files (modules) and even group together different files. Similarly when creating a dataset in a database we divide things into columns, tables, and groups of inter-related tables.

But such divisions are only visible to the members of that specific project. Anyone else has to get the entire application or entire database to use one particular part of it. Furthermore anyone working on any given part of one of the application or database needs to be aware of, and interact with, anyone else working on it — decentralization is impossible or extremely limited.

Thus, atomization at such a low level is not what we are really concerned with, instead it is with atomization into Packages:


By packaging we mean the process by which a resource is made reusable by the addition of an external interface. The package is therefore the logical unit of distribution and reuse and it is only with packaging that the full power of atomization’s “divide and conquer” comes into play — without it there is still tight coupling between different parts of a given set of resources.

Developing packages is a non-trivial exercise precisely because developing good stable interfaces (usually in the form of a code or knowledge API) is hard. One way to manage this need to provide stability but still remain flexible in terms of future development is to employ versioning. By versioning the package and providing ‘releases’ those who reuse the packaged resource can use a specific (and stable) release while development and changes are made in the ‘trunk’ and become available in later releases. This practice of versioning and releasing is already ubiquitous in software development — so ubiquitous it is practically taken for granted — but is almost unknown in the area of knowledge.

A Basic Example: A Photo Collection

Imagine we had a large store of photos, say more than 100k of individual pictures (~50GB of data at 500k per picture). Suppose that initially this data is just sitting as a large set of files on disk somewhere. Consider several possibilities for how we could make them available:

  1. Bundle all the photos together (zip/tgz) and post them for download. Comment: this is a very crude approach to componentization. There is little atomization and the ‘knowledge-API’ is practically non-existent (it consists solely of the filenames and directory structure).

  2. In addition tag or categorize the photos and make this database available as part of the download. Comment: By adding some structured metadata we have started to develop an ‘knowledge-API’ for the underlying resource that makes it more useful. One could now write a screensaver program which showed photos from a particular category or auto-import photos by their area.

  3. In addition suppose the photos fall into several well-defined and distinct classes (e.g. photos of animals, of buildings and of works of art). Divide the photo collection into these three categories and make each of them as a separate download. Comment: A initial step on atomizing the resource to make it more useful, after all 5GB is rather a lot to download for one photo.

  4. In addition to dividing them up allow different people to maintain the tags for different categories (one might imagine those knowledgeable about animals are different from those knowledgeable about art). Comment: Atomization assists the development of good knowledge-APIs (the human mind is limited and divide and conquer helps us deal with the complexity).

  5. Standardize the ids for each photo (if this hasn’t been done already) and separate the tags/categories data from the underlying photo data. This way multiple (independent) groups can provide tags/categorization data for the photos. Comment: Repackaging — along with the development of a better knowledge-API for the basic resource — allows a dramatic decrease in the level of coupling and increase the scope for independent development of complementary libraries (the tags). This in turn will increase the utility to end users.


In the early days of software there was also little arms-length reuse because there was little packaging. Hardware was so expensive, and so limited, that it made sense for all software to be bespoke and little effort to be put into building libraries or packages. Only gradually did the modern complex, though still crude, system develop.

The same evolution can be expected for knowledge. At present knowledge development displays very little componentization but as the underlying pool of raw, ‘unpackaged’, information continues to increase there will be increasing emphasis on componentization and reuse it supports. (One can conceptualize this as a question of interface vs. the content. Currently 90% of effort goes into the content and 10% goes into the interface. With components this will change to 90% on the interface 10% on the content).

The change to a componentized architecture will be complex but, once achieved, will revolutionize the production and development of open knowledge.

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Rufus Pollock is Founder and President of Open Knowledge.

7 thoughts on “What Do We Mean by Componentization (for Knowledge)?”

  1. I agree completely – the world is atomic in scale and time.
    But I am a reductionist in daily life – most hackers are. It’s the only way things work. In my musings I try to transcend it.

  2. It is interesting article. However, it seem that it was written from
    theoretical prospective and not practical. One thing must be point out,
    there is more to open content than the points mentioned, open content increase the speed spread of knowledge of the information as oppose to regular academic publishing.

    Genick Bar-Meir,

  3. Genick, I completely agree with you but this post was not intended to be a general discussion of why open knowledge (content) might be good but a specific examination of what we need to do to be able to develop open knowledge/content more easily and effectively — in particular by making knowledge more componentized.

  4. To follow up this post, Prodromos Tsiavos made the excellent point in discussion of this on list:

    … the way in which the artefact is atomized (it is not all artefacts that are atomized in the same way or even are susceptible to atomization) to a great extent influences the development routines.

    My response to this question was as follows:

    Absolutely that is something I wanted to go into greater detail about. I see a definite spectrum with some areas of knowledge much more amenable to this componentization compared to others. The classic examples where it is hard to componentize is narrative prose. It is generally not possible to take the start of one novel, the middle of another and the end of the third, stick them together and get anything resembling a decent new novel. In essence the problem is that narrative prose is highly coupled (to use a bit of terminology from software architecture): when you change one thing it generally has large knock-on effects elsewhere (anyone who has tried to tweak and old essay for republication elsewhere will know this all too well).

    Something similar is true about music to a lesser extent though of course music can be incorporated into other types of works (such as films) and we do have whole genres based on sampling — though the gluing effort even there is very substantial (perhaps this may be changing see the example given in [1][]).

    Film provides an interesting example because here, though the finished product may be highly coupled, there is significant scope for componentization and atomization earlier on the production process. I remember Adnan talking about the process being developed at where one group of people would shoot footage, others would divide it up into 10-30s segments which they would tag and annotate with metadata and then others would come along and combine the segements into documentary films.


    Overall I guess I current see a spectrum that looks like:

    Suitability for Applying the 4 principles (esp. componentization)

     Low       Narrative Text (Novels, Essays etc)
      |        Music
      |        Film
      V        Databases
    High       Code

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