I had a call with a Fortune 100 IT team that is looking at using semantic technology as an alternative to the Data Warehouse.  This is my favorite kind of conversation, since I firmly believe the traditional data warehouse is dead but just doesn’t know it yet.

This is the situation the IT team explained:

We need to aggregate information and present it to the user, so we build a warehouse.  We spend all this time building and designing the warehouse, and when it’s done they need something else.  Unfortunately, it’s not so easy to modify a warehouse once it’s running, so we build another one.  And then another.  The cycle has been repeating itself for years and is not sustainable.

The alternative to warehousing is Data Virtualization (EII, Data Federation…lots of terms for it)…or, at least that’s what they, and many others, see!  Essentially, they have been burned by years of working with an inflexible technology, so are looking to dump the approach all together.

I get this.  If a Durian is the only fruit you’ve ever smelled, you’d think all fruit were really stinky.

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Ask a group of Semantic Web professionals where the data should live when you’re doing data integration projects – which is just what Cambridge Semantics VP Lee Feigenbaum, acting in his capacity as co-chair of the W3C’s SPARQL Working Group, did at a panel at last week’s SemTech – and don’t expect to get a single, agreed-upon answer.

Among the choices:

“Federation will crush warehousing,” Eric Prud’hommeaux of the W3C and its Semantic Web Health Care and Life Sciences Interest Group said with an eye to provocation. “Leave data where the authorities have it and take advantage of individual domain contributions.” The basic idea of federation is that data stays in its source systems and you do integration dynamically, querying source systems on the fly.

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I have often heard people lament the lack of federated systems in the Semantic Web. Certainly, the use of URIs allows data from many different sources to link together seamlessly, and the judicious use of assertions like owl:sameAs can help fill in the gaps, but if a developer wants to do something interesting with data from more than one SPARQL endpoint, they must draw it all in from various locations before merging and linking it all locally. Where is the "webiness" in this data? Wasn’t SPARQL supposed to do all of the processing work for us? Why do we need to do this work manually?

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