ORO Results in Yahoo SearchMonkey

It’s been a long – and enjoyable – day today (err, yesterday, I forgot to post this last night!), so just a quick placeholder post, that I’ll maybe elaborate on with techie details at a later date, to show one way of making some use of the metadata that appears in the ORO/eprints resource splash pages (as described in ORO Goes Naked With New ePrints Server): a Yahoo SearchMonkey ORO augmented search result – ORO Reference Details (OUseful).

The SearchMonkey extension – which when “installed” in your Yahoo profile, will augment ORO results in organic Yahoo search listings with details about the publication the reference appears in, the full title (or at least, the first few characters of the title!), the keyowrds used to describe the reference and the first author, along with links to a BibTeX reference and the document download (I guess I could also add a link in there to a full HTML reference?)

The SearchMonkey script comes in two parts – a “service” that scrapes the page linked to from the results listing:

And a “presentation” part, that draws on the service to augment the results:

It’s late – I’m tired – so no more for now; if you interested, check out the Yahoo SearchMonkey documentation, or Build your own SearchMonkey app.

Special Interest Custom Search Engines

A recent post by Downes (PubMed Now Indexes Videos of Experiments and Protocols in Life Sciences) reminded me of a Google custom search engine I started to put together almost a year or ago to provide a meta-search over science experiment protocols.

At the time, I managed to track three likely sites down, although despite my best intentions when I created the initial CSE, I haven’t managed even cursory maintenance of the site.

Anyway, for what it’s worth, here’s a link to my Science Experimental Protocols Video Search (a search for DNA will show you what sorts of results are typical). If you know of any other sites that publish scientific experimental protocols, please fee free to post a link in the comments to the post.

Another custom search engine I started looking at at the start of this year, inspired by a conversation with a solicitor friend over New Year, was a search of UK (English and Scottish) legislation. The intention here was to come up with a CSE that could provide a value adding vertical search site to a legal website. If i remember correctly (?!;-) the CSE only took an hour or so pull together, so even though we never pursued embedding it on live website, it wasn’t really that much time to take out…

If you want to check it out, you can find it here: LegalDemo.

One CSE I do maintain is “How Do I?”, a metasearch engine over instructional video websites. There are almost as many aggregating websites of this ilk as there are sites publishing original instructional content, but again, it didn’t take long to pull together, and it’s easy enough to maintain. You can find the search engine here: “How Do I?” instructional video metasearch engine, and a brief description of its origins here: “How Do I…” – Instructional Video Search.

Another 10 minute CSE I created, this time following a comment over a pint about the “official” OpenLearn search engine, was an OpenLearn Demo CSE (as described here: OpenLearn Custom Search).

And finally (and ignoring other the other half-baked CSEs I occasionally dabble with), there’s the CSE I’ve been doodling with most recently: the OUseful search engine (I need to get that sorted on a better URL..). This CSE searches over the various blogs I’ve written in the past, and write on at the moment. If you want to search over posts from the original incarnation of OUseful.info, this is one place to do it…

Just looking back over the above CSEs, I wonder again about who’s job it is (if anyone’s), to pull together and maintain vertical search engines in an academic environment, or show students how they can crate their own custom search engines? (And one level down from that, who’s role is it to lead the teaching of the “search query formulation” information skill?)

In the OU at least, the Library info skills unit have been instrumental in engaging with course teams to develop information literacy skills, as well as leading the roll out of Beyond Google… but I have to admit, I do wonder just how well equipped they are to helping users create linked data queries, SPARQL queries, or SQL database queries containing a handful of joins? (I also wonder where we’re teaching people how to create pivot tables, and the benefits of them…?!)

Thinking about advanced queries, and the sighs that go up when we talk about how difficult it is to persuade searchers to use more than two or three keyword search terms, I’ve also been wondering what the next step in query complexity is likely to be after the advanced search query. And it strikes me that the linked data query is possibly that next step?

Having introduced the Parallax Freebase interface to several people over the last week, it struck me that actually getting the most out of that sort of interface (even were Freebase populated enough for more than a tiny minority of linked queries to actually work together) is not likely to be the easiest of jobs, particularly when you bear in mind that it’s only a minority of people who know how to even conceptualise advanced search queries, let alone know how to construct them at a syntactic level, or even via a web form.

The flip side to helping users create queries is of course helping make information amenable to discovery by search, as Lorcan Dempsey picks up on in SEO is part of our business. Here again we have maybe another emerging role for …. I don’t know…? The library? And if not the library, then whom?

(See also: The Library Flip, where I idly wondered whether the academic library of the future-now should act “so as to raise the profile of information it would traditionally have served, within the search engine listings and at locations where the users actually are. In an academic setting, this might even take the form of helping to enhance the reputation of the IP produced by the institution and make it discoverable by third parties using public web search engines, which in turn would make it easy for our students to discover OU Library sponsored resources using those very same tools.”)

PS Just a quick reminder that there are several OU Library job vacancies open at the moment. You can check them out here: OU Library Jobs Round-Up (August 2008).

Searching for Curriculum Development Course Insights

For almost as long as I can remember (?! e.g. Search Powered Predictions), I’ve had the gut feeling that one of the most useful indicators about the courses our students want to study is their search behaviour, both in terms of searches that drive (potential) students to the OU courses and qualifications website from organic search listings, as well as their search behaviour whilst on the OU site, and whilst floundering around within the courses and quals minisite.

A quick skim through our current strategic priorities doc (OU Futures 2008 (internal only), though you can get a flavour from the public site: Open University Strategic Priorities 2007) suggests that there is increased interest in making use of data, for example as demonstrated by the intention to develop a more systematic approach for new curriculum developments, such that the student market, demography and employment sectors are the primary considerations.

So, to give myself something to think about over the next few days/weeks, here’s a marker post about what a “course search insights” tool might offer, inspired in part by the Google Youtube Insights interface.

So, using Youtube Insight as a starting point, let’s see how far we can get…

First off, the atom is not a Youtube video, it’s a course, or to be more exact, a course page on the courses and quals website… Like this page for T320 Ebusiness technologies: foundations and practice for example. The ideas are these: what might an “Insight” report look like for a course page such as this, how might it be used to improve the discoverability of the page (and improve appropriate registration conversion rates), and how might search behaviour inform curriculum development?

Firstly, it might be handy to segment the audience reports into four:

  • people hitting the page from an organic search listing;
  • people hitting the page from an internal (OU search engine) search listing;
  • people hitting the page from an ‘organic’ link on a third party site (e.g. a link to the course page from someone’s blog);
  • people hitting the page from an external campaign/adword etc on a search engine;
  • people hitting the page from any other campaign (banner ads etc);
  • the rest…

For the purposes of this post, I’ll just focus on the first two, search related, referrers… (and maybe the third – ‘organic’ external links). What would be good to know, and how might it be useful?

First off, a summary report of the most popular search terms would be handy:

– The terms used in referrers coming from external organic search results give us some insight into the way that the search engines see the page – and may provide clues relating to how to optimise the page so as to ensure we’re getting the traffic we expect from the search engines.

– The terms used within the open.ac.uk search domain presumably come from (potential) students who have gone through at least one micro-conversion, in that they have reached, and stayed in, the OU domain. Given that we can (sometimes) identify whether users are current students (e.g. they may be logged in to the OU domain as a student) or new to the OU, there’s a possibility of segmenting here between the search terms used to find a page by current students, and new prospects.

(Just by the by, I emailed a load of OU course team chairs a month or two ago about what search terms they would expect potential students to use on Google (or on the OU search engine) to find their course page on the courses and quals site. I received exactly zero responses…)

The organic/third party incoming link traffic can also provide useful insight as to how courses are regarded from the insight – an analysis of link text, and maybe keyword analysis of the page containing the link – can provide us with clues about how other people are describing our courses (something which also feeds into the way that the search engines will rank our course pages; inlink/backlink analysis can further extend this approach.). I’m guessing there’s not a lot of backlinking out there yet (except maybe from professional societies?), but if and when we get an affiliate scheme going, this may be one to watch…?

So that’s one batch of stuff we can look at – search terms. What else?

As a distance learning organisation, the OU has a national reach (and strategically, international aspirations), so a course insight tool might also provide useful intelligence about the geographical location of users looking at a particular course. Above average numbers of people reading about a course from a particular geo-locale might provide evidence about the effectiveness of a local campaign, or even identify a local need for a particular course (such as the opening or closure of large employer).

The Youtube Insight reports shows how as the Google monster gets bigger, it knows more and more about us (I’m thinking of the Youtube Insight age demographic/gender report here). So providing insight about the gender split and age range of people viewing a course may be useful (we can find this information out for registered users – incoming users are rather harder to pin down…), and may provide further insight when these figures are compared to the demographics of people actually taking the course, particularly if the demographic of people who view a course on the course catalogue page differs markedly from the demographics of people who take the course…

(Notwithstanding the desire to be an “open” institution, I do sometimes wonder whether we should actually try to pitch different courses at particular demographics, but I’m probably not allowed to say things like that…;-)

As well as looking at search results that (appear) to provide satisfactory hits, it’s also worth looking at the internal searches that don’t get highly relevant results. These searches might indicate weak optimisation of pages – appropriate search terms donlt find appropriate course pages – or they might identify topics or courses that users are looking for that don’t exist in the current OU offerings. Once again, it’s probably worth segmenting these unfulfilled/unsatisfactory courses according to new prospects and current students (and maybe even going further, e.g. by trying to identify the intentions of current students by correlating their course history with their search behaviour, we may gain insight into emerging preferences relating to free choice courses within particular degree programmes).

To sum up… Search data is free, and may provide a degree of ‘at arms length’ insight about potential students before we know anything about them ‘officially’ by virtue of them registering with us, as well as insight relating to emerging interests that might help drive curriculum innovation. By looking at data analysis and insight tools that are already out there, we can start to dream about what course insight tools might look like, that can be used to mine the wealth of free search data that we can collect on a daily basis, and turn it into useful information that can help improve course discovery and conversion, and feed into curriculum development.