HowTo
How to Properly Semantify Your Data Gathering and Querying Needs using a Semantified Wiki to create a fitting Knowledge Graph
This guide outlines a systematic approach starting with your Needs and ending up with a fully operational Semantic MediaWiki that you may use as a prototype of even for production.
The Ideal Process
Start with gathering your needs
You can do this systematic, semi-systematic or fully freestyle in natural languages. Just make sure you get to an agreement between the stakeholders about what is relevant and capture the needs in computer readable form.
Set Up Your Wiki
Utilize ProfiWiki and py-mediawikidocker to set up your Semantic MediaWiki environment. This provides a solid foundation for your semantified wiki in a few minutes.
Create a Contex for your project
You'll find examples context right in this wiki at List of Contexts Currently there are 16 example Contexts available:
Examples
SMWCon
SMWCon is the acronym for the Semantic Mediawiki conference The lessons learned from the SMWCon experience and best practices in Semantic MediaWiki (SMW) are the basis for this example
Historical Context: SMWCon and List of Attendees
The journey of semantification for SMWCon began with the creation of the first SMWCon page using SemanticMediaWiki properties to capture information about SMWCon Events. https://www.semantic-mediawiki.org/wiki/SMWCon_Fall_2011 is an example for such a SMWCon page.
The proper way to handle the catalog of properties (Metadata management) has been much debated.
A self-reflective, semantified version of the Attendees list, as proposed by Pierre Racine (see Metadata management) of the List of Attendees at SMWCon Fal 2015 was a step forward. Over the years, additions were made, but unfortunately, SMWCon didn't fully embrace the power of self -reflective semantification.
3. Set Up Your Wiki
Utilize ProfiWiki and py-mediawikidocker to set up your Semantic MediaWiki environment. This provides a solid foundation for your semantified wiki.
4. Implement Self-Reflection
Follow Pierre Racine's proposal for metadata management. Implement a self-reflective structure where properties and other semantic elements are themselves described using semantic annotations.
5. Convert Existing Content
If you have existing content (like the SMWCon List of Attendees), convert it to use the newly created semantic structure. This may involve:
- Updating pages to use the new templates
- Replacing free-text information with property assignments
- Creating new pages for concepts that were previously only mentioned in free text
6. Maintain Semantic Consistency
Regularly review and update your semantic structure. As your domain evolves, make sure to:
- Update the UML diagram
- Regenerate semantic elements as needed
- Refactor existing content to match the updated structure
Lessons Learned from SMWCon
1. Avoid Redundancy: Don't copy-paste content. Use semantic properties and queries to display information in multiple contexts. 2. Eat Your Own Dog Food: If you're promoting semantification, use it extensively in your own wiki. 3. Maintain Consistency: Regularly review and update your semantic structure to ensure it remains relevant and efficient. 4. Automate Where Possible: Use tools like the y-principle generator to maintain consistency and reduce manual work. 5. Embrace Self-Reflection: Implement a system where your wiki's structure is itself described semantically, allowing for easier management and evolution of your knowledge base.
Conclusion
By following this process and learning from the SMWCon experience, you can create a truly semantified wiki that leverages the full power of Semantic MediaWiki. Remember, the goal is not just to add properties to pages, but to create a interconnected, self-describing knowledge base that can evolve with your needs.
Further Reading
This revised version focuses on the correct process for semantification, emphasizing the lessons learned from the SMWCon experience and the importance of avoiding redundancy while leveraging the full power of Semantic MediaWiki. It also includes references to the tools and concepts you mentioned, such as the y-principle generator, ProfiWiki, and py-mediawikidocker.