Search Patterns and Faceted Taxonomies

Peter Morville and Jeffrey Callendar have produced a beautiful  manifesto calling to improve search  called Search Patterns: Design for Discovery (Oreilly, 2010). It is an ode to making complex data beautiful and navigable in user interfaces.  It’s nice to see O’Reilly produce a book with visual flair.

But once you journey through the many beautiful interfaces and design principles on how to present data,  you realize that there is still a need to understand that data presentation is related to data organization.  Morville hints at how data is organized to facilitate these interfaces.  In Chapter 2 on the anatomy of search, the authors write that sites should “embrace faceted navigation… Global facets might include topic, format, date and author.”   Morville downplays the role of formal hierarchies, focusing instead of the user experience of multiple interactions from “pearl growing” to browsing to managing your data to work towards a more immediate user experience.  Faceted navigation is described as “arguably the most significant search innovation of the past decade” (p 95), but there is only one short chapter on called Engines for Discovery that discusses how to create faceted navigation.

The data organization that combines the product taxonomy with other facets is called “unified discovery.”  The engines of this discovery (Chapter 6) and this is where we get into the expanded role of the taxonomists is to add facets for

  • Category: broad classifications that vary by application,
  • Topics:  the smaller areas of common interest  such as specific cars or books or recipes
  • Format: how data is formatted whether as content, video, or idea
  • Audience:  the fundamental activity of understanding the needs of who might need the data, from scholar and expert to novice browser

This global “one size fits all’  recommendation leaves out Time and Chance, which is when an object is produced, and the element of chance in that it is highly respected and relevant to the needs of users.  Date and date range is an important global facet.  Whether there is an “out of the box ” global taxonomy is probably up for debate.   Facets, and how many and how they are labeled,  needs to be validated by user need, application and content.   A global  model is a good starting point, but will probably need to be tuned.  Search across health care policies, for example, which probably requires facets on diseases, symptoms and treatments, and additional resources.    Determining the top categories can take some time so that these categories reflect common shared knowledge and vocabulary.  The top facets do not have to be 5 or 7 plus or minus 2, but rather what is needed by the application, users, and to organize the content.   Get over fixed universality rules and instead collect more data about user needs and content.

These navigations rely on separate and distinct data structures which allow users to navigate and refine queries before they are passed to underlying database or data structures.  These data structures  needs to be maintained, governed and analyzed. Over time, the richer this conceptual metadata, the better the search experience – better techniques for creating and using metadata are only around the corner.

On taxonomies and ontologies, the authors specifically argue that there may be other approaches to disambiguating terms (like Java the programming language from Java the island) based on clues like user and context rather than vocabularies:

“It’s not that there’s no value in parsing sentences for meaning or developing thesauri (or ontologies) that map equivalent, hierarchical, and associative relationships.  These approaches can add value, especially within verticals with limited formal vocabularies, like medicine, law and engineering.  It’s just that less obvious approaches like employing query-query reformulation and post-query click data to drive autosuggest – may deliver better results at lower costs. And we should be wary of claims that computers “understand meaning,” at least until they get a whole lot better at filtering spam.” (p. 162)

While these ideas are valid, it loses the essential wisdom of why librarians adapted taxonomies and spent so long building a body of standards for taxonomy creation. One thing librarians have long known about taxonomies is that they have a shelf-life beyond a specific application – that they can be used to share data across applications, communities and across the globe.

If we are to move the beauty of Morville and Callendar’s interfaces to uses beyond e-commerce and towards accessible, lower cost applications, we are going to have to understand the data structures behind these beautiful designs, and reach some shared understandings about how they should be built.  Search-side approaches to search are wise, but they depend on a good design for faceted navigation where it has validated user categories with user’s needs.  The skills of the taxonomist can be applied to search-side information design.

One discussion I enjoyed was on the under-appreciated role of color as a “quick way to reference the major categories and key players.” (p.15) I have often thought that it might be useful to have a color attribute when defining a facet or category so that all the terms and concepts within a facet share the same color.  That would help in visual sorting of ideas which is an idea Morville and Callendar explore more on the following pages.  Sites without a visual library of photos but only ideas and concepts could become more visual through the use of color-coding.  That would be useful if blogs and databases would look at ways of adding color so that similar concepts in a facet or category  can also be categorized by shared color.

To move to the next level, where we move search patterns from e-commerce to other uses, such as health care or better access to government information and more widely adapt better and more visual search designs,  we have to broaden the understanding of how to create and validate  faceted navigation and categories and what the supporting data structures need to be.  Perhaps O’Reilly’s next book should be on the common data structures for design for discovery such as the art of taxonomy and ontology.

Search Patterns is a valuable little  book  to stimulate creative juices.  The link  to buy Search Patterns is at http://searchpatterns.org/

Thank you to Andy Oram, a mensch of an editor at O’Reilly.

~ Marlene Rockmore

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The Mars Test

A recent segment on NPR discussed with New Yorker writer Peter Hessler, who has lived in China for the past 15 years, what it was like to re-enter life in the United States and how United States looks to Chinese citizens.  Hessler discussed how hard it is for the rest of the world to understand our complex system of check and balances, of federal, state and local power, of influential groups with non-governmental status.    So that raised the question of what governmental websites do to help orient visitors to what the basic organization and framework of government.

What if we were visiting from Mars?  What would we learn from our governmental websites about how the United States is organized.   The Mars test, in taxonomy and information design, is also called the ‘mental model.’  A mental model uses common knowledge or frameworks for creating website navigation.  So a good place to start design a US Government website might be with 4th grade civics, which distinguishes Executive and administration, Legislative, and Judicial Branches and explain responsibilities of federal government and those functions reserved for state government.

Here is the US Government portal called USA.gov.  Does it pass the Mars test?

USA.gov on April 16, 2010

It is a directory like interface  that is organized, it seems to me, based on arbitrary topics with no association to government agencies. Where would I even begin to find out about the President of the United States, the new health care bill, the Supreme Court?  How do you find a local office of a government office like my legislator’s office or the social security office.  In a week where a United States Supreme Court justice retired and volcanic ash disrupted air travel, there is no acknowledgment of these events or links to related website.  The site in fact gives an impression that lights are on but nobody is home.

USA.Gov.com  is actually experimenting with some sophisticated clustering software such as  Vivisimo (vivisimo.com).  This clustering application illustrates how clustering results can be customized in this case by topic, by agency and by sources. While the topic clusters are automatically generated on-the-fly, the agency and source filters are generated based on HTML metatags.

The United Kingdom is experimenting with its own clustered interface but the site also uses  RDFa and shared metadata. This system has the advantage of having a reusable metadata model that can allow state and local agencies map their content to the governmental model.  This promotes “harmonization” and cooperation in supplying data between federal and state government.  Because of this harmonization through use of shared metadata,  directgov.uk can enable features such as search by zipcode for local offices that deliver state and local services.  Even better, the interface looks like someone is minding the store and cares what content appears on the website.

Direct.Gov.UK April 16, 2010

I am not opposed to clustering.  Clustering promises to be a great technology to quickly retrieve masses of documents and content, but a little upfront work is needed to filter automated technologies into useful categories that reflect our  shared  knowledge and common sense.  This work  would help in  creating automated systems that sort results into useful buckets that clarify content and help users find government assistance and  solutions.

Search.usa.gov is actually an exciting engine that has clustered over 50 million government documents.  However it needs a friendlier, warmer interface to the experience.   For example search for  Supreme Court, and results  mixes state courts with the United States Supreme Court.  Wouldn’t  search experience  be improved if the portal to the search engine helpe users  understand and  filtered  searches to distinguish between by federal and  state courts.

Using common models through taxonomies and shared metadata might not only help the visitors from Mars.  It might also help citizens of the United States find a clearly navigable path based on stuff they learned in 4th grade.

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