Quick note on Frankenplace, a cool search tool that displays the geographic distribution of documents that match the user's query as a heatmap. Details of how the tool works are given in: At the heart of the method is a discrete global grid that divides the world up into small areas of the same size.

One of my frustrations with the GBIF portal is that it is hard to drill down and search in a specific area. You have to zoom in and then click for a list of occurrences in the current bounding box of the map. You can't, for example, draw a polygon such as the boundary of a protected area and search within that area.

One of the limitations of the Biodiversity Heritage Library (BHL) is that, unlike say Google Books, its search functions are limited to searching metadata (e.g., book and article titles) and taxonomic names. It doesn't support full-text search, by which I mean you can't just type in the name of a locality, specimen code, or a phrase and expect to get back much in the way of results.

This is not a post I'd thought I'd write, because OpenURL is an awful spec. But last week I ended up in vigorous debate on Twitter after I posted what I thought was a casual remark: This ended up being a marathon thread about OpenURL, accessibility, bibliographic metadata, and more.

I spend a lot of time searching the web for bibliographic metadata and links to digitised versions of publications.

Google's Knowledge Graph can enhance search results by display some structured information about a hit in your list of results. It's available in the US (i.e., you need to use www.google.com, although I have seen it occasionally appear for google.co.uk. Here is what Google displays for Eidolon helvum (the straw-coloured fruit bat). You get a snippet of text from Wikipedia, and also a map from the BBC Nature Wildlife site.

Prompted by the appearance on the BHL blog of an article about BioStor I've thinking about how to improve what is basically a fairly clunky tool. One major weakness is searching the collection of nearly 40,000 articles extracted from BHL. Note the word "extracted." BioStor isn't a tool like PubMed or Google Scholar where the goal is to find articles on a topic.

Jeff Atwood, one of the co-founders of Stack Overflow recently wrote a blog post Trouble In the House of Google, where he noted that several sites that scrape Stack Overflow content (which Stack Overflow's CC-BY-SA license permits) appear higher in Google's search rankings than the original Stack Overflow pages . When Stack Overflow chose the CC-BY-SA license they made the assumption that: Jeff Atwood's post goes on to argue

One response to the analysis I did of the Google rank of mammal pages in Wikipedia is to suggest that Wikipedia does well for mammals because these are charismatic. It's been suggested that for other groups of taxa Wikipedia might not be so prominent in the search results. As a quick test I extracted the 1552 fungal species I could find in Wikipedia and repeated the analysis.

One assumption I've been making so far is that when people search for information on an organism using its scientific name, Wikipedia will dominate the search results (see my earlier post for an example of this assumption). I've decided to quantify this by doing a little experiment. I grabbed the Mammal Species of the World taxonomy and extracted the 5416 species names. I then used Google's AJAX search API to look up each name in Google.