From OntologySummit2013 Communique
Ontologies are human-intelligible and machine-interpretable representations of some portions and aspects of a domain. Since an ontology contains terms and their definitions, it enables the standardization of a terminology across a community or enterprise; thus, ontologies can be used as a type of glossary. Since ontologies can capture key concepts and their relationships in a machine-interpretable form, they are similar to domain models in system and software engineering. And since ontologies can be populated with or linked to instance data to create knowledge bases, and deployed as parts of information systems for query answering, ontologies resemble databases from an operational perspective.
You need a common vocabulary for a community to share knowledge. Ontologies are meant to provide that vocabulary.
Currently, there is no agreed on methodology for development of ontologies, and there is no consensus on how ontologies should be evaluated. Consequently, evaluation techniques and tools are not widely utilized in the development of ontologies. This can lead to ontologies of poor quality and is an obstacle to the successful deployment of ontologies as a technology.
This document focuses on the evaluation of five aspects of the quality of ontologies: intelligibility, fidelity, craftsmanship, fitness, and deployability.
To determine the quality of an ontology, we need to evaluate the ontology as a domain model for human consumption, the ontology as a domain model for machine consumption, and the ontology as deployed software that is part of a larger system. In this document, we focus on five high-level characteristics:
1. Can humans understand the ontology correctly? (Intelligibility)
2. Does the ontology accurately represent its domain? (Fidelity)
3. Is the ontology well-built and are design decisions followed consistently? (Craftsmanship)
4. Does the representation of the domain fit the requirements for its intended use? (Fitness)
5. Does the deployed ontology meet the requirements of the information system of which it is part? (Deployability)
This document also contains the Ontology Life Cycle Model and is certainly worth a read.
So why is this document important?
Ontologies play different roles in information systems, natural language based analytics and knowledge discovery.
Having a consistent view of Ontologies and the process of building one can immensely impact the shared knowledge in any organization. They improve communication, ability to contribute to the shared knowledge, better searching. They provide great tools for efficiently organize information and provide better context for automated agents.
I was jotting down ideas on the various aspects of Information that a business has to deal with. Not all of them are relevant to all businesses. However, as I was thinking about Information, I was amazed by the number of attributes and activities related to information. Here is a list.
- Gathering – Identifying the Right Sources
- Finding – Search and Other tools
- Validating – Verifying the authenticity and sources
- Deduplicating – Enormous overload occurs due to slightly modified versions of Information occurring over a period of time
- Normalizing – Reducing it to some kind of canonical form (who are the players, what is happenings etc.)
- Filtering – The essential tool to manage the overload and separate signal from noise. But the noise of one person may be the signal for another. So can we customize, individualize filters? What do we do with sediments left behind the filtering process?
- Detecting patterns – occurrence patterns and source bias patterns and other cause-effect patterns
- Classification – Topic Aggregation, Topic Similarity, Topic Hierarchy
- Relating – independent, interdependent, co-occurrence and correlations
- Analysis – contextual analysis, source context, use context, bias, analysis of language, overtones/undertones,
- Synthesis – Making sense of different pieces of information
- identifying Propagation Patterns – How does it propagate? What is the correlation of information paths to styles of information
- Insights – Detecting trends, velocity and currency
- Intelligence – Deriving actionable intelligence, mining, extracting facts, extracting entities, why/what/how/when/where analysis
- Layering – how each layer maps to the organization’s layers?
- Flow – An analysis of flow of information. Tracing information between people, teams, departments, up and down the organization. Also flows between an organization, its partners and customers.
- Structuring – How do we link these different pieces – Unstructured, semi-structured and structured?
- identifying barriers to use – stovepipes/silos, lost information
- Supplementing/Augmenting Information – with annotations and collaborative editing
- Visualizing – Different levels and types of visualization
- Alerts and Notifications – Smart alerts/notifications based on analysis and detection of patterns and occurrence of events based on rules. Needed for both internal and external information.
- Synchronizing – Updating internal information based on changes taking place external to the organization.
This is just a partial list. As the information increases dramatically, we need to think about these various aspects of Information and how we can leverage it to help an organization. What is your IIQ (Information Intelligence Quotient)?
Update June 2012
The team at Next Wave Multimedia were kind enough to create a presentation from this post. Do you want to create your own fun presentations? You can try ComicsHead, an iPad app.