You’ve been using DT fairly heavily for a couple of weeks. My database is now about 29 months old, and for the most part contains data that I’ve carefully selected over that time period. However, because my interests center around environmental science, technology and policy my collection ranges from chemical analytical/biological laboratory procedures, to legislation and regulation, to hazardous site investigation and remediation, to risk assessment, to statistical methodologies for assessment of environmental data, to toxicology and health effects, to conservation biology, genetics, economics – and a wide swath of other related materials.
My initial interest in DEVONthink was roused simply by the fact that it can do searches on the text of a variety of file types. I already had thousands of reference files on my computer. DT allowed me to search my collection, which is no small accomplishment. If that were all that DT could do, I would still be using it every day. For it has allowed me to construct a personal “encyclopedia” of my interests that is far larger, deeper and richer than the Encyclopedia Britannica.
DT doesn’t (yet) offer a full set of Boolean search operators. Users are limited to AND, OR, phrase and wildcard searches, with case/no case variants. There’s also the fuzzy search, which I often find useful for technical terminology. Of course, it’s fairly easy to do multilevel sorts and searches of search hits (DT Pro beta allows one to create “smart” groups the contents of which are based on a search strategy, but this can be emulated easily in DT PE). With a little thought and surprisingly quickly, “smart” searches of a DT database can be done now.
I’m looking forward to having the more complex search tools of DEVONagent in DEVONthink. The search potentials I miss most in DT include the lack of a NEAR operator, and the ability to mix exact multi-term phrases with AND and/or OR terms. But there will be a price to pay when we are able to construct very complex search operations: speed. Really complex searches of my database, which contains tens of thousands of files and tens of millions of words will take longer than simple AND or OR searches of a few words. Even so, I’d rather stress my CPU than my brain. (And I’ll probably move to a G5 when DT Pro version 2 comes along.)
When I’m really digging into a topic I do sometimes find the Keywords button useful, especially in a jargon-rich field, or when I’m interested in checking other items by the same author.
Perhaps the major weakness of Keywords, IMHO, is that DT only uses single terms as keywords. Let’s say that I’m looking in my database for information about polybrominated diphenyl ethers. Keywords doesn’t seem helpful. But wait! There’s an acronym, PBDEs, that’s commonly used for these chemicals. Sure enough, there the acronym is in Keywords. Click on it, and there’s a long list of the references in my database. (It helps to know the jargon.)
I make a lot more use of the See Also button. DEVONthink’s contextual recognition features really work, and can recognize multi-term patterns – think of it as Keywords on steroids, or even (often) as a very intelligent search feature.
How smart is DEVONthink’s See Also feature? In my experience, it covers the spectrum from genius to idiot. On balance, I find it extremely useful. Always remember, while you are looking at articles on the biochemistry of nitrate uptake by marine algae, that DEVONthink doesn’t know anything at all about biochemistry, or algae. See Also merely suggests other articles that have similarities to the article you are reading. It’s up to the user to understand the content being read, and to judge how related DT’s suggestions are to the user’s interest. In my database, DT will suggest several other research articles on nitrogen uptake by algae or phytoplankton, as well as articles about algal blooms and phosphate limitation, “dead zones” resulting from algal blooms, programs to reduce nitrate runoff from agriculture, potential economic losses to fisheries from excessive marine nitrate levels, and so on. DT may also suggest some items that seem dumb, based on factors such as the mailing address of a research institute, an author with the same last name who writes about racing cars rather than biochemistry, and so on. Overall, DT makes a good research assistant.
I’ve got just under 800 groups/subgroups in my database. Some groups/subgroups are very well organized, most are rather messy. I’ve never used auto-classify (although I will experiment with that using a database copy sometime soon).
The Classify button in early versions of DT often refused to highlight a suggested group for location of an item. Recently, DT classification has become more aggressive – almost always, one or more suggestions is highlighted for action by the Move button. I like that. I’ve got a big backlog of unclassified items in my “Edit These” group, and I’m making more use of DT’s decisions rather than manual decisions. Even when I could quibble with DT’s classification decisions, I see no ill effects on searching and See Also functions. The more I let DT make classification decisions, the better (more consistent, even if not like the decisions I would make) they seem to get – in this instance, perhaps DT is smarter than I am.
I have no hesitation in locating an item in more than one group. That breaks strict hierarchical rules, and can lead to a network rather than hierarchical organization. Hierarchical groups are easier for us humans to understand, but perhaps that isn’t so important after all.
At this point, I carefully classify some items, such as project records, for my own convenience. For other items, I’m willing to let DT decide where to put them.