NKE: Navigational Knowledge Engineering
From the website:
Although structured data is becoming widely available, no other methodology – to the best of our knowledge – is currently able to scale up and provide light-weight knowledge engineering for a massive user base. Using NKE, data providers can publish flat data on the Web without extensively engineering structure upfront, but rather observe how structure is created on the fly by interested users, who navigate the knowledge base and at the same time also benefit from using it. The vision of NKE is to produce ontologies as a result of users navigating through a system. This way, NKE reduces the costs for creating expressive knowledge by disguising it as navigation. (emphasis in original)
This methodology may or may not succeed but it demonstrates a great deal of imagination.
Now imagine a similar concept but built around subject identity.
Where known ambiguities offer a user a choice of subjects to identify.
Or where there are different ways to identify a subject. The harder case.
Questions:
- Read the paper/run the demo. Comments, suggestions? (3-5 pages, no citations)
- How would you adapt this approach to the identification of subjects? (3-5 pages, no citations)
- What data set would you suggest for a test case using the technique you describe in #2? Why is that data set a good test? (3-5 pages, pointers to the data set)
Hi Patrick,
A core design consideration of my platform is to let users record information according to their own world view using a minimal system ontology as a guide. The “ontology as a guide” and even a no ontology approach allows users to express what they want and the system tracks the relationships they make. Later they or someone else can go back and map concepts to other ontology relationships, or even evolve their on models over time.
I need to look at NKE in more detail, but it seems to have a similar approach.
Similar to software systems, information has an ontology whether it’s explicit or not. It’s often more important to initially capture than to structure, as repurposing and extraction for particular contexts is the norm.
Better to have tools that allow and even encourage this process.
Cheers,
ast
Comment by Andrew S. Townley — December 18, 2010 @ 8:16 am