SciVerse held a challenge recently on apps for science. Two out of the three top place finishers had distinctly topic map like features.
Altmetric – First place: Reads in part:
Once the Altmetric app is installed you’ll notice a new ‘Altmetric’ box appear in the sidebar whenever you search on the SciVerse Hub. It’ll show you the articles in the first few pages of your search results that your peers and the general public have been talking about online; if you prefer you can choose to only see articles from the page of results that you’re currently on. You’ll also see some basic information about how and where articles are being discussed underneath the search results themselves.
Refinder – Second place: Reads in part:
When you found the right papers on SciVerse, bring them together with Refinder. Refinder is an intelligent online collaboration tool for teams. Scientists are using it to collect papers, research notes, and more information in one place. Once collected, important facts about documents can be added as comments. By using links, related things are connected. When reading an article in SciVerse, an intelligent algorithm automatically searches and suggests relevant collections, topics, documents, or experts from Refinder.
Teams love it. Shared collections are provided for each team. They are individually configured by inviting members and setting access rights. Teams use collections to share articles, ideas, dicuss topics, ask questions and get answers. Organizations can use Refiner both internally and externally, a useful feature to communicate with partners in projects.
Sounds a lot like a topic map doesn’t it? Except that they have a fairly loose authoring model, which is probably a good thing in some cases. Don’t know if the relations between things are typed or if they have some notion of identity.
iHelp – Third place: Reads in part:
iHelp enables researchers to do search in their native languages. Articles with different languages are retrieved using this multi-lingual search. Option is provided for phonetic typing of search text. User can either do native search (the typed language) or translate and search in English.
I assume talking about full text search but at least attempting to do that across languages. Suspect it has all the issues of full text plus the perils of mechanized translation. Still, if the alternative is no searching at all, this must seem pretty good.
All of these applications represent some subset of what topic maps are about, ranging from subjects being described in different languages to being able to easily collaborate with others or discover other characteristics of a work, such as its popularity.
Offering some modest improvement over current interfaces, improvements that fall far short of the capabilities of topic maps, seem to attract a fair amount of interest. Something for nay sayers about improved information applications to keep in mind.