There was an interesting thread yesterday on the PAMnet listserv regarding "core" databases in Mathematics and which could be cut to save money.
One response was that it's better to search full text anyway (I couldn't disagree more).
Ben Wagner expressed concern that Google Scholar was going to drive all of the databases out of business and then Google would abandon the project.
Joe Hourclé posted about ADS - a core database in astro. Fred Stoss posted about PubMed - needs no intro here, surely!
Here's my response.
I think Scopus and WoS are the biggest immediate threats to the smaller domain specific indexes particularly when the largest number of academic users are looking for a few reasonable things and aren't doing the complex queries or needing to be very precise and have very high recall. In my world, I'm like the goalie: by the time they ask me, they've tried Google, they've asked their friends, they've asked their mother*... it's gotten past 10 people without an adequate answer. For these hard questions, I need the power of a good database (like Inspec). But... if you look at quantities and numbers of users... does that justify the huge cost? Maybe? But do our auditors agree? Infrequent big wins vs. day to day common usage?
As Ben has often chronicled, we've shifted money out of every other budget to support our sci/tech journal habit. We've starved the humanities. We've dropped databases. All for more and more expensive journals. Seems like if the content does get paid for out of other budgets via page charges or institutional support for open access publishing, that might make it even more important that libraries have better ways to find the distributed content. But, like Ben, I worry that we'll put these finding tools out of business.
Another observation: two of the "core" databases mentioned, ADS and PubMed, are government supported as a service to the community. The solar physics bibliography is a very specialized resource but is also super important to those researchers. Maybe if building specialty research databases is no longer profitable but there remains a need, the community-built tools will improve/grow/gain support? Maybe they'll be backwards and using technology from 1995, though
I'm working with some projects that are actually taking big piles of full text documents and using computational methods to classify using an ontology that's built by subject matter experts (with some advice from a professional taxonomist in my group). The volume/velocity/yadda yadda of the data precludes the careful indexing done by our fancy databases... but this and other projects like it I think show a swing back toward the importance of good indexing and the importance of having domain experts reviewing the classification system.
* My mom is a statistician so I might ask her first