GoPubMed’s Cool Feature… 
GoPubMed is a new semantic search engine designed to deliver the ultimate research muscle to the biomedical, medical, and life sciences realm. Researchers, scientists, and general users may gain quicker more “cross-pollinated” search results for deeply layered data requests.
One of the more intriguing features of GoPubMed is the “Hot Research.” This is a nifty trend-spotter: the site’s example offers a side-by-side graphical comparison that maps trends in alzheimer’s research. There are also tools to pan for statistics on certain study authors, cities, and journals. For instance, find out who is most feverishly carving away at research related to, let’s say, neurolinguistics, from which city(ies) the most published work is coming from on the topic, and plot all of it on a cluster map of the world. Or find out who is collaborating with whom on neurolinguistics–see it visually presented as a cartographic mash-up of scientific collaboration, a partially connected mesh network, if ever I saw one.
Search results are presented with highlighted text. There are quite a few options for targeting more relevant results: A left-hand navigation field displays a “semantic” list of category choices collected from Gene Ontology (GO) and Medical Subject Headings (MeSH) classes. Use this to pinpoint results more rapidly. Also search results are accessorized with button options: link to related Wikipedia articles, “toggle” document views, and even flag a result that does not belong.
GoPubMed is on the leading edge of accessible search tools for life sciences and biomedical work groups. Many corporations already possess robust semantic middleware behind closed doors. GoPubMed attempts to give users a variety of data formats. Might we see these same components slightly renovated for other types of semantic tools? Could it be that we may see the semantic web and natural language search grow more rapidly when the medical and corporate demands (knowledge “needers”) lead the way?
Filed under: Data, Metadata, Search Engine, Semantic Web | Tagged: biomedical, go, gopubmed, mesh, semantic search
