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A '˜Killer App': Semantic Data Integration
- 1. A ‘Killer’ App:Semantic Data Integration Integrate – Innovate - Accelerate February25th, 2011 Chuck Rockey, Senior Director of Engineering & Professional Services Confidential IO Informatics © 2011
- 2. Semantic Data Integration Save Time Save Money Save Lives … by integrating ALL of the structured, unstructured and public data of interest Confidential IO Informatics © 2011
- 3. Semantic KB Advantages Inexpensive Quick to Build Comprehensive Flexible Linked Meaning is explicitly represented Confidential IO Informatics © 2010
- 4. Semantic KB Advantages An Elegant Solution… to a Difficult Problem Confidential IO Informatics © 2010
- 5. Iterative Process Gather Requirements Create / Identify Ontologies ETL / Generate Assertions Queries – Test Integration Iterate your data model in minutes! Confidential IO Informatics © 2011
- 6. ETL Approaches Custom Scripting Pipelining Tools Point & Click Tools Confidential IO Informatics © 2011
- 7. Point & Click Approach Fast and Easy Create application ontologies on-the-fly Use existing ontologies if desired Fine-grained control Instant visualizations Mappings are visual, reusable and easily maintainable Confidential IO Informatics © 2011
- 8. Live Demo Confidential IO Informatics © 2011
Editor's Notes
- Toby talked about “Practical Semantics”, this talk is about that. It’s also about making ‘the simple things simple’ which Charlie alluded to in his talk. By the end of this 10 minutes, you’ll have seen how easy semantic integration can be.
- Save Time, Save Money, Save lives.By applying all of the available data to a problem.And this is what we do with customers.
- These are some of the advantages of semantic technologies that we are realizing in practice with our customers.The top two speak to saving time and money. The latter speak to the richness of the technology model. This richness is what makes it easy for users to ask complex questions of their data and get back the results they are interested in. Pretty simple, also pretty valuable. On top of this, you can layer formal ontologies and reasoning.
- This is one take-away. Data integration in the Life Sciences is a challenge and semantic technologies present an elegant solution.
- Part of that elegance is that this model enables an iterative integration process. You don’t have to design the entire solution in detail before you start work. You can start by delivering value to users using a few data sets, then turn the crank to add more data to the integration as new data sets become available and relevant.There’ve very little risk or brittleness here.
- There are a few different approaches to building an integration. Custom scripting will work, but is pretty labor intensive and not very maintainable Pipelining is well suited to statistical processing, but when it comes to integrating data it tends to be overly complicated. We chatted a bit about the barriers involved with pipelines this morning. What I’m going to demonstrate are some point and click tools, that make it simple and quick.
- Again, point and click tools can really put the Easy Button on this process. It’s simple enough for technically minded subject matter experts to use on their own. It’s also powerful enough that IT teams can use it to create large integrations for their customers.There’s a lot of flexibility here as well. For instance, you can start with a formal ontology that you’ve adopted from a third party or built yourself.
- This is going to be an intentionally very simple demo, as I’m really trying to demystify what can be a very simple process.So this could have been any sort of structured data or relational sources.I left a lot of topics out of this demo: picking and modifying ontologies, Thesauri, working with SPARQL endpoints, different backend servers, automating this process, etc. But I hope a gave you a taste of how straightforward this can be and a also of the Practical Semantics that Toby talked about when kicking off the conference.