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A n expert’s information search goals are simple:

1. Show me something I don’t already know.

2. Among the 500 + n3 or so articles published last month in or around my area of expertise, rank the ones I should read first.

Expert users already have proficient, polished searchskills. It doesn’t take them long to learn how to tap the valueof an information system. They have a knack for “gaming”a system (in a positive manner) to generate productiveresults. In the process they are quick to determine if thesystem may be a valuable resource for what they seek orwhether they need to find another resource. Moreover, theytend to be highly educated and smart enough to resist fallinginto any predetermined cognitive style. If one approachdoesn’t work, they find another.

Working with power users on several projects providedmy teammates and me the catalyst to investigate the latestinnovations in search research. What we discovered wasexploratory search.

Experiencing Information through SearchResearch underway at leading institutions is breathing

new life into our understanding of how we search forinformation. Exploratory search is an emerging disciplinethat encompasses the examination of dense or rich

information domains via three main facets: “Lookup,”“Learn” and “Investigate.” Researchers at MicrosoftResearch, Johns Hopkins University and other leadinginstitutions have discovered that relationships are notlinear among these facets, nor is there a definitive parent-child relationship in how we explore information. That is,we do not browse, learn and investigate in a linear processas we, say, watch a movie. For example, behaviors withinthe “Investigate” activity may precede those from “Learn”or “Lookup,” while activities under “Investigate” may bepaired with one or more from “Learn.” Rather, it is thecombination and recombination of the different relationshipsin how information is presented and how we seek for itthat holds the potential for expediting new discoveries. It isthese very relationships that have the potential to producethe “Ahas” or exclamations of “Eureka” by researchers.The goal for information architects is to support the user’sability to build relationships among discovered informationitems [1]. In the design of search results and interfaces forbrowsing rich information resources we need to design acertain degree of elasticity into the product to give usersmore control over the results.

In his article “Exploratory Search: From Finding toUnderstanding,” Gary Marchionini outlines three mainfacets of search behavior – “Lookup,” “Learn” and

I N F O R M A T I O N A R C H I T E C T U R E

Exploring Exploratory Searchby Mark Nolan

I A C o l u m n

Mark Nolan is an informationarchitect in Washington, D.C.He can be reached atmc_nolan<at>verizon.net.

C O N T E N T S N E X T PA G E >< P R E V I O U S PA G E

the authors of “Supporting Exploratory Search” put it,“What do we do if we want to locate something from adomain where we have a general interest but no specificknowledge?” [3]

It’s a good question. In other words

n How do we discover what we don’t know how to find?

n How do we locate information beyond our area of expertise that may be important to us?

n How do we browse topics and search resources for unknown quantities that we cannot define or even describe?

n How else do we “Learn?”

To continue our scenarios, users may begin in“Investigate” mode, where they are seeking to excludesources, data and information from a task, as does ourexpert researcher cited above. They then proceed to “Learn”once they have isolated a series of articles they suspect willhelp them keep current in their field. Imagine being able toisolate articles for our expert persona that use terms he orshe commonly searches on but which are used in a slightlydifferent context. For instance, a chemist may researchpublished results of experiments that use similar methods ormaterials, though in different disciplines such as microbiologyand molecular physics. Matches may generate leads thatmay hasten collaboration of research, leading to importantdiscoveries in the parallel disciplines. Today, collaborationacross disciplines is staggeringly important in research onsubjects such as the human genome, intelligence andmaterials science.

There is still an enormous amount of work to be donein improving the execution of designs and search solutionsthat will help lead the user to a greater understanding andinvestigation of a topic. For instance, information

“Investigate” – and further illustrates the differences amongthe three modal search states and makes the case for a newapproach to researching search [2]. Each of the three modalsearch states has associated behaviors and sub-modes.

n Under “Lookup” Marchionini proposes the following:fact retrieval, known item search, navigation,transaction, verifications and question/answering.

n Under “Learn” we find knowledge acquisition,comprehension/interpretation, comparison,aggregation/integration and socialization.

n Under “Investigate” the group contains accretion,analysis, exclusion/negation, synthesis, evaluation,discovery, planning and forecasting, and transformation.

In “Lookup” mode, many of us locate people, placesand things every day on Yahoo, Google or Ask. We know orsuspect the thing we’re looking for is out there – we justhave to find the right combinations of search terms tolocate it. In the process, we may “Learn” about new items,relationships among people, places and things, provided thata reasonable portion of the domain is well organized (andwell managed). The success rate on “Learn” is inconsistent,however, because it is hard to plan and manage. Efforts todate assume a logical transition from “Lookup” to “Learn”in a user’s search behavior. What the research challenges isthe assumption that to get to “Learn” users must start with“Lookup.” The research shows that in fact users may begin in“Learn” mode and transition to fact retrieval and verificationunder “Lookup.”

Supporting Exploratory Search“Investigate” is the most challenging of the three primary

tasks to work on and the crux of our design challenge. As

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I A C o l u m nN O L A N , c o n t i n u e d

C O N T E N T S N E X T PA G E >< P R E V I O U S PA G ET O P O F A R T I C L E

architects working on solutions associated with distancelearning online instruction may find themselves butting upagainst the challenges of creating pre-coordinateinformation displays to facilitate “Learn” and “Lookup.”

Peter Morville’s prescient observation that “we do notrealize the potential of what we can do until we discover thepossibilities” [4] haunts us every day. The observation cutsright to the heart of the challenge in designing informationarchitecture solutions for experts: designing solutions tofacilitate “Investigate,” “Learn” or “Lookup.” To date,search engine technology remains the only viable optionfor supporting explorations of rich information collections,particularly ones with a high volume of contributed content.

Improvements in search engine technology are offeringnew opportunities. Search engine technology is the nextfrontier in the quest to bridge the gap between data miningtools, translation techniques and etymology. Improvingsearch engine technology by applying findings fromexploratory search research has already begun. Some effortshave proved successful while others have generatedinconsistent outcomes to date, but work is underway toimprove results. For instance, engineers are adding differentusage metrics to the mix to sharpen rankings for relevancy.In the near future, the system will not only know what wasalready searched on (as some search engines do today), butalso whether to show that information to the users, giventhe context of the their searches, their search patterns andtheir history of adding or eliminating terms based on theirreview of prior search results. More to the point, emergingsearch technologies such has Twine and Readware havethe power to explain why certain results were producedand give the user the option to adjust, tweak, expand orwinnow the criteria on-the-fly to a degree unprecedented inthe past. These new tools are transforming search engines

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T O P O F A R T I C L E

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into engines of discovery. New solutions will open upreams of information resources, reducing the time it takesto “Learn” and “Investigate” a topic.

Information architects influence the production ofcontent. Metadata is helpful when and where metadata canbe applied or when it is part of a formalized productionprocess. However, information is often not formallyprocessed. The level of inconsistency in the production andcapture of supplemental information provided in a prooffor a research experiment, for example, is astounding in thisday and age. It is in these small corners of rich informationdomains that important discoveries may sit for months,even years.

Rich information domains vary in structure andorganization. Nevertheless, they have the equivalent offingerprints – they produce their own heuristics, howeverinconsistent. Some resources reflect the way information iscaptured or stored; others may reflect a process or techniqueused for capturing the information, such as a publishingprocess. Yet others reflect the disposition of the professionalswho organized them or built the appliance that captures theinformation. The means of production of content directlyaffects a system’s ability to locate, draw meaning from orbuild relationships among its contents.

To enable exploratory search, the IA community needsto exert more influence in the design and development ofthe solutions that capture, originate and produce content.For example, at the object level, in the planning stages,information architects could effect efficiencies by providingrequirements for how information should be managed at itscreation. We have data and data architects; we haveinformation and information architects – and we haveconfusion in the industry on the role each plays in the designand development of systems. This situation needs to end.

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SummaryExploratory search research opens new opportunities

for information architects to grow the profession. Researchdiscoveries are unleashing profound enhancements in searchengine technology. To increase the value of the findings ofthe research on exploratory search, information architectsneed to explore new methods and approaches to designing

information displays for expert systems. As professionals,we need to exert more influence over the devices,appliances and software that govern the production ofcontent. Enhancements to the production of content willcyclically increase our understanding of designinginformation solutions for experts, adding additional valueto the user interfaces designed for less expert solutions. n

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[1] Gersh, J., Lewis, B., Montemayor, J., Piatko, C., & Turner, R. (2006, April). Supporting insight-based information exploration in intelligence analysis. Communications of the ACM, 49 (4.), 63-68. Abstract and references available at http://portal.acm.org/citation.cfm?id=1121949.1121984.Full electronic text available to subscribers or for purchase.

[2] Marchionini, G. (2006, April). Exploratory search: From finding to understanding. Communications of the ACM, 49(4), 41-46. Abstract and references available at http://portal.acm.org/citation.cfm?id=1121979. Full electronic text available to subscribers or for purchase.

[3] White, R.W., Kales, B., Ducker, S.M., & Schraefel, M.C. (2006, April). Supporting exploratory search. Communications of the ACM, 49(4), 36-39.Abstract and references available at http://portal.acm.org/citation.cfm?doid=1121949.1121978. Full electronic text available to subscribers or for purchase.

[4] Torenvliet, G. (2007, May + June), Review of “Ambient Findability by Peter Morville,” O'Reilly Media, 2006; ISBN 0-596-00765-5; $29.95.Interactions,14(3), 50-51. Electronic text available to subscribers or for purchase at http://portal.acm.org/citation.cfm?id=1242421.1242455&coll=ACM&dl=ACM&idx=J373&part=magazine&WantType=Magazines&title=interactions&CFID=18803928&CFTOKEN=62699246.

Resources Cited in the Article