Strategies LLC Taxonomy May 14, 2007Copyright 2007 Taxonomy Strategies LLC. All rights reserved. Taxonomy 1-2-3 Enterprise Search Summit 2007 Tutorial

Strategies LLCTaxonomy

May 14, 2007 Copyright 2007 Taxonomy Strategies LLC. All rights reserved.

Taxonomy 1-2-3

Enterprise Search Summit 2007

Tutorial

2Taxonomy Strategies LLC The business of organized information

Today’s agenda

9:00-9:05 5 min Introduction

9:05-9:10 5 min Warm-up exercise

9:10-9:35 25 min Building taxonomies

9:35-9:45 10 min Taxonomy exercise

9:45-10:05 20 min Taxonomy business case

10:05-10:20 15 min Taxonomy & search

10:20-10:35 15 min Coffee Break

10:35-11:05 30 min Taxonomy ROI

11:05-11:15 10 min ROI exercise

11:15-11:45 30 min Taxonomy governance

11:45-12:00 15 min Q&A


My taxonomy questions

Priority (1-5) Questions

Your title or role:

Your org or industry:

Your dept:

Your name: (optional)


Taxonomy Fundamentals: Agenda

Building taxonomies Taxonomy business case Taxonomy & search Taxonomy ROI Taxonomy maintenance


The Taxonomy problem: How to pick from > 5,000 faucets?

By: Category Price Brand Color/Finish # Handles Series Name Water Filter? Faucet Spray Handle Shape Soap Dispenser?


The main issue: What goes here?

When do the things in the list change?

How do we maintain the list?

What rules do we follow?


What's involved in creating a taxonomy?

Metadata Scheme. Data fields for describing content so that it can be found and used.

Vocabularies. Collections of terms that are used to specify some of the metadata properties.

Relationships between content, fields or terms (hierarchical, equivalence, & associative)

Some vocabularies are big & hierarchical, some are small and flat.

Application Profile. Formal representation of metadata & vocabularies.


Seven phases of taxonomy development

Week: 1 2 3 4 5 6 7 8 9 10 11 12

1 Identify Objectives

Conduct interviews

2 Inventory Resources

Identify, gather & review resources

Define fields & purpose

3 Specify Metadata

4 Model Content

Define content chunks & XML

DTDs

5 Specify Vocabularies

Compile controlled vocabularies

6 Specify Procedures

Develop workflow, rules & procedures

7 Test & Train Manually tag small sample


Taxonomy design phases need to be iterated

1 Identify Objectives

2 Inventory Resources

3 Specify Metadata

4 Model Content

5 Specify Vocabularies

6 Specify Procedures

7 Test & Train

Interview core team and stakeholders

Identify, gather & review resources

Define fields & purpose

Define content

chunks & XML DTDs

Compile controlled

vocabularies

Develop workflow rules &

procedures

Plan & Prototype

Manually tag small sample

Gather additional resources,

if any

Revise if needed, bake

into alpha CMS

Revise if needed, bake into alpha

CMS

Revise, use in alpha CMS

alpha workflows in CMS

Alpha Dev & TestReview tagged

samples, default

procedures

Use alpha CMS to tag

larger sample

Modify CMS for

beta

Modify CMS for beta

Revise, use in beta CMS

Modify & extend

workflows

Gather additional sources, if

any

Beta D&T

Interview alpha users

Use beta CMS to tag larger

sample

Finalize training materials & train

staff

Modify for 1.0

Modify for 1.0

Revise using team

procedure

Finalize procedure materials

Final D&T

Interview beta users


Licensing an existing taxonomy

See Factiva’s taxonomy www.taxonomywarehouse.com There are usually license fees, but these will be less than

the effort to develop an equivalent taxonomy. But pre-existing taxonomies rarely fit an organization’s

needs and may require extensive customization.

Recommendation Adopt a faceted approach. Reuse existing (especially internal) vocabularies for as

many of the facets as possible. Plan on doing full-custom “Content Type” and “Topic”

taxonomies.


Free sources for 8 common taxonomies

Taxonomy Definition Potential SourcesOrganization Organizational structure. SP 800-87, U.S. Government Manual, Your

organizational structure, etc.

Content Type Structured list of the various types of content being managed or used.

Dublin Core Type Vocabulary, AGLS Document Type, Your records management policy, etc.

Industry Broad market categories such as lines of business, life events, or industry codes.

SIC, NAICS, Your market segments, etc.

Location Place of operations or constituencies.

FIPS 5-2, FIPS 55-3, ISO 3166, UN Statistics Div, US Postal Service, Your sales regions, etc.

Function Functions and processes performed to accomplish mission and goals.

Federal Enterprise Architecture Business Reference Model, Enterprise ontology, Your business functions, etc.

Topic Business topics relevant to your mission & goals.

Federal Register Thesaurus, NAL Agricultural Thesaurus, Your research areas, etc.

Audience Subset of constituents to whom a piece of content is directed or intended to be used.

GEM, ERIC Thesaurus, IEEE LOM, Your psycho-graphics or personas, etc.

Products & Services

Names of products/programs & services.

ERP system, Your products and services, etc.


Typical product catalog: A-Z, then idiosyncratic categories


How to analyze existing product catalog categories: Principles and priorities

Preparing a product catalog for facet browsing (aka Guided Navigation) requires a category hierarchy and additional attributes.

Principles1. Categories and subcategories that could be swapped are candidates for

conversion to attributes.2. Repeated lists of subcategories signal a possible need for an attribute.3. The number of attributes should not exceed six or seven, so not all attribute

candidates should be used.• Avoid selecting strongly correlated attributes, such as “Weight” and “Shipping

Weight”.

Priorities1. Choose Categories that apply to many products, over those with few

products.2. Choose Attributes that apply to many Categories over those that apply only

to very few categories.


Product categories example: Wireless carrier

Products

AccessoriesContentPhonesServices

BatteriesCasesChargersDataHands-FreeHeadsetsMiscellaneous

ConferencingInternet / DataLandline PhoneNetwork & Roaming

Relay ServicesSolutionsWireless Data

Versatile PhonesSmart DevicesBasic PhonesPrepaid PhonesInternational Only Phones

Mobile Broad-band Cards

PurchasedSubscription


Product attributes example: Digital cameras in an electronics catalog

Types of attributes Generic attributes

– Brand/Product Family/Model– Price Range– Usually Ships

Merchandising attributes– Usage (E-mail, Internet Browsing, Programming, …)– Segment (Home, Business, Education, Government …)– Region & Country– Most Popular– New– Related Products

Specialized attributes– Capacity (Battery; Memory; MB; GB; BPS, …)– Resolution (DPI; Megapixels; XGA, XGA, UXGA, …)– Size (Display; Screen; ...)– Standard (a, b, g, n, …; scsi, ata, sata, eide, …; dimm, simm,

…)– Type (Camera; Battery; Display; Printer; Server; Storage;

Switch; …)

Resolution3 Megapixels (4)4 Megapixels (5)5 Megapixels (27)6-8 Megapixels (21)

BrandCanon (15)Fuji (10)Kodak (17)Nikon (8)Olympus (9)

TypePoint & Shoot (25)Digital SLR (10)Packages (5)

Price Range$100-250 (5)$250-500 (16)$500-1000 (19)More than $1000 (3)


Faceted taxonomy theory & practice

How many terms are needed to provide sufficient granularity? Not as many as you think!

Post-coordinate indexing allows several simple controlled vocabularies to be combined, rather than using a single large pre-coordinated vocabulary.


The power of faceted taxonomy

4 independent categories of 10 nodes each have the same discriminatory power as one hierarchy of 10,00010,000 nodes (104) Easier to maintain Easier to tag by content authors Can be easier to navigate

It’s more effective to increase the number of facets, than to increase the number of terms per facet.

AdvocacyContractors & Grantees

Environmental Professionals

Federal Facilities

General PublicIndustryKidsResearchers & Scientists

Small BusinessStudents

Audience

AdvisoryExposureFood SafetyHealth Assessment

Health EffectHealth Risk Occupational Health

Pesticide Effects

Sun ProtectionToxicity

Health Industry

AllergenBiological Contaminant

CarcinogenChemicalExplosiveLiquid WasteMicroorganismOzonePesticideRadioactive Waste

Substance

Agriculture & Cattle

Automobile Repair

ChemicalDry CleaningElectronics & Computer

EnergyExtractive Industries

Food Processing

Leather Tanning & Finishing

Metal Finishing


Automatically created taxonomies

Documents can be ‘clustered’ based on similarities and differences.

Problems: Typically only a single

hierarchy No overall plan Results hard for people to

navigate

What does “North” mean on this map?


Automatic taxonomy construction software

Software can scan large quantities of content and extract statistically significant words and phrases.

Example: Archive of 10 publications analyzed for

topics related to “copyright.” Software does a poor job of

De-duplication. Turning significant words and phrases

into a larger structure. Discriminating between “gold” and

“garbage.” Software is good for

Getting an understanding of the key noun phrases in a large collection.

Providing test cases for evaluating a taxonomy.

Source: Sample data courtesy of nStein.


Most popular flickr tags on 20 Feb 2007http://www.flickr.com/photos/tags/

Sort flickr categories into 5 or fewer groups. Then label each group.


Taxonomy exercise—Facet grouping

Universal taxonomy facets By location (spatially) By time (chronologically) By type (genre) By physical properties (size, color, shape, etc.) By subject (topic)

Richard Saul Wurman. Information Architects (1996)


Taxonomy exercise— Facet grouping

Location Time Type

Color Subject

Sort flickr categories into 5 or fewer groups. Then label each group.





Business case and motivations for taxonomies

How are we going to use content, metadata, and taxonomies in applications to obtain business benefits?


What technology analysts have said: Add metadata to search on!

“Adding metadata to unstructured content allows it to be managed like structured content. Applications that use structured content work better.”

“Enriching content with structured metadata is critical for supporting search and personalized content delivery.”

“Content that has been adequately tagged with metadata can be leveraged in usage tracking, personalization and improved searching.”

“Better structure equals better access: Taxonomy serves as a framework for organizing the ever-growing and changing information within a company. The many dimensions of taxonomy can greatly facilitate Web site design, content management, and search engineering. If well done, taxonomy will allow for structured Web content, leading to improved information access.”


Fundamentals of taxonomy ROI

Tagging content using a taxonomy is a cost, not a benefit. There is no benefit without exposing the tagged content

to users in some way that cuts costs or improves revenues.

Putting taxonomy into operation requires UI changes and/or backend system changes, as well as data changes.

You need to determine those changes, and their costs, as part of the ROI.


Product utilization: Taxonomy compared to search

Conversion rate increases. HomeDepot.com – Double digit increase. 1-800-Flowers.com – More than a 10% increase. Otto Group (Kaleidoscope, Freemans, Grattan, and lookagain

catalogs) – 130% increase.

Lift in average order size.


Product catalog: Taxonomy compared to search

Benefit:Increased conversion rate & revenue lift

Web sales net income $ 80,000,000

Increased conversion rate 30%

$ 24,000,000

Order size lift 10%

$ 8,000,000

Potential revenue increase per year $ 32,000,000


Usability research: Taxonomy compared to search

“We found that users preferred a browsing oriented interface for a browsing task, and a direct search interface when they knew precisely what they wanted.”

Marti Hearst (and others)

“The category interface is superior to the list interface in both subjective and objective measures.”

Hao Chen & Susan Dumais


Usability research: Taxonomy compared to search

0

20

40

60

80

100

120

140

Category List

Me

dia

n S

earc

h T

ime

in

Se

con

ds

In top 20 results

Not in top 20 results

Category is 36% faster

Category is 48% faster

Source: Chen & Dumais


Time saved: Taxonomy compared to search

1 hour per day searching x 36% faster = 22 minutes each day

22 minutes x 250 working days per year = 5500 minutes or 92 hours per year


Time saved: Taxonomy compared to search

Benefit: Increase service efficiency

Number of call center calls per month 50,000

Average cost per call $ 20

Call response costs per month $ 1,000,000

Total call response costs per year $12,000,000

Percentage of self-serviced calls due to improved information browsing 30%

Service costs savings per year $ 3,600,000


Trusted advisers: Taxonomy avoids costs

“The amount of time wasted in futile searching for vital information is enormous, leading to staggering costs …”

Sue Feldman,

Sun’s usability experts calculated that 21,000 employees were wasting an average of six minutes per day due to inconsistent intranet navigation structures. When lost time was multiplied by staff salaries, the estimated productivity loss exceeded $10M per year—about $500 per employee per year.

Jakob Nielsen, useit.com


Searching

Creating

Commun-icating

Knowledge workers spend up to 2.5 hours each day looking for information …

… But find what they are looking for only 40% of the time.

Source: Kit Sims Taylor


Creating new

content

Recreating existing content

SearchingCommun-icating

25%8%

Knowledge workers spend more time re-creating existing content than creating new content

Source: Kit Sims Taylor (cited by Sue Feldman in her original article)


Cost saved by not recreating content

Benefit: Increase in productivity

Number of employees 100

Average employee salary $ 80,000

Employee costs per year $8,000,000

Increase in productivity from not re-creating content 25%

Employee cost savings per year $2,000,000


Business case summary

1. Classifications and classification-like schemes are being used to facilitate information seeking in the workplace, and on the web.

2. Users take advantage (and prefer) this type of scheme (faceted navigation) when it is made available in the user interface.

3. Hierarchical or facet navigation can be guided by the User Interface.

4. Facet navigation is best combined with keyword searching. E.g., keyword search followed by faceted navigation of results.





Do taxonomies actually improve search?

Input (Query) Side “Search” using a small set of pre-defined values instead of trying

to guess what word or words might have been used in the content.

Have synonyms mapped together so searches for “car” and “automobile” return the same things.

Output (Results) Side Organize search results into groups of related items. Sorting and filtering Refining search results


Finding information should not be about “Feeling Lucky”


Google search on “pcb” –Returns > 28M items

Taxonomy could suggest “polychlorinated

biphenyls”


169,169 items

169,169 items

Categorized results Refine search by clicking on categories


Taxonomy in action on the results side: www.CareerBuilder.com search on IT positions

By Category By Company By City By State


Typical search on “database”: List of ranked hits on www.oracle.com/prNavigator.jsp

Select item


Faceted search on “database”: Categorized results + Ranked list

Select item, or

Refine search by clicking on categories





Key Factors in ROI (Return on Investment)

Breadth “How many people will metadata affect?”

Repeatability “How many times a day will they use it?

Cost/Benefit “Is this a costly effort with little or no benefits?”

Source: Todd Stephens, Dublin Core Global Corporate Circle


Some common taxonomy ROI scenarios

Product catalog Increased conversions Increased self-service & use Increased productivity

Customer support Cutting requests for information costs Increased web statistics (page hits) Higher ACSI (American Customer Satisfaction Index) score

Knowledge worker productivity Less time searching, more time working Avoiding re-creating information that already exists

Compliance Improved regulatory compliance Improved enforcement Higher PARS (Performance & Accountability Reports) FDIC, SOX, HIPAA, etc. compliance


How to estimate costs—Tagging

Taxonomy Facet Hier?TypicalCV Size

Time/ Value (min)

Avg # values /

Item $ / MinCost/

Element

Audience N 10 0.25 2 $ 0.42 $ 0.21

Content Type N 20 0.25 1 $ 0.42 $ 0.11

Organizational Unit Y 50 0.5 2 $ 0.42 $ 0.42

Products & Services Y 500 1.5 4 $ 0.42 $ 2.52

Geographic Region Y 100 0.5 2 $ 0.42 $ 0.42

Broad Topics Y 400 2 4 $ 0.42 $ 3.36

TOTALS 1080 5 15 $ 7.04

Inspired by: Ray Luoma, BAU Solutions


How to estimate costs—Assumptions

ASSUMPTIONS

Enterprise SW License $ 100,000

Maintenance/Support 15%

SW Implementation x 200%

Legacy Content Items 100,000

Content Growth Rate 15%

Tagging/Item $ 7.04

Enterprise Taxonomy $ 100,000


How to estimate costs—Total cost of ownership (TCO)

Description Year 1 Year 2 Year 3 Year 4 Year 5

SW

Licenses $ 100,000

Maintenance $ 15,000 $ 15,000 $ 15,000 $ 15,000

Implementation $ 200,000

App Tech Support $ 30,000 $ 30,000 $ 30,000 $ 30,000

Tagging

Legacy Content $ 703,500

Ongoing $ 105,525 $ 121,354 $ 139,557 $ 160,490

Taxonomy

Creation $ 100,000

Maintenance $ 15,000 $ 15,000 $ 15,000 $ 15,000

TOTAL $ 1,103,500 $ 165,525 $ 181,354 $ 199,557 $ 220,490


Benefits Assumptions

Productivity Assumptions

Employee costs per year (100 employees, $75,000 per year) $ 7,500,000

Increase in productivity (from not recreating content) 25%

Cost savings $ 1,875,000

Percentage realized in first year 10%

Service Efficiency Assumptions

Customer service calls cost/year $ 12,000,000

Efficiency (from customer self-service) 30%

Cost savings $ 3,600,000

Percentage realized in first year 10%


Sample ROI Calculations

Description Year 1 Year 2 Year 3 Year 4 Year 5

Costs

Software Licenses/ Maintenance $ 100,000 $ 15,000

$ 15,000

$ 15,000

$ 15,000

Implementation/Support $ 200,000 $ 30,000 $ 30,000

$ 30,000

$ 30,000

Taxonomy Creation/ Maintenance $ 100,000 $ 15,000

$ 15,000

$ 15,000

$ 15,000

Legacy/Ongoing Tagging $ 703,500 $ 105,525 $ 121,354

$ 139,557

$ 160,490

Benefits

Productivity increases $ - $ 187,500 $ 1,875,000 $ 1,875,000 $ 1,875,000

Service efficiency gains $ - $ 360,000 $ 3,600,000 $ 3,600,000 $ 3,600,000

Yearly Net Benefits $(1,103,500) $ 381,975 $ 5,293,646 $ 5,275,443 $ 5,254,510

Payback period 1.1 Years until Benefits = Costs

Inspired by: Todd Stephens, Dublin Core Global Corporate Circle


ROI exercise—Why tag?

Tagging content using a taxonomy is a cost, not a benefit. There is no benefit without exposing the tagged content to users in

some way that cuts costs or improves revenues. Putting taxonomy into operation requires UI changes and/or

backend system changes, as well as data changes. You need to determine those changes, and their costs, as part of

the ROI.

List the top 5 benefits from tagging content. Then, rank the benefits by priority.



ROI exercise—Benefits from tagging content


List the top 5 benefits from tagging content.

Then, rank the benefits by priority.

Potential benefits from tagging content

1. Reduce information requests

2. Reduce cost per UU (unique user)

3. Expand to new audiences

4. Improve customer satisfaction

5. Improve performance & accountability

6. Increase number of successful website searches

7. Increase number of links (internal cross-cutting & external)

8. Reduce time to build websites

9. Increase metadata consistency & quality

10. Decrease time to create & publish marketing information

11. Improve e-commerce

12. Decrease product development lifecycle


Why implement a taxonomy?

Find relevant information quicker. Discover information you didn’t know you had. Avoid duplicate efforts to “reinvent the wheel” Learn from mistakes. Create better quality work product. Provide overview as well as details about a subject. Demonstrate relationships between content. Reduce complexity.

Taxonomy & Content Classification





Taxonomy requires a business processes

Taxonomies must change, gradually, over time if they are to remain relevant.

Maintenance processes need to be specified so that the changes are based on rational cost/benefit decisions.


Taxonomy change process overview

Working Copiesof CVs, maintain in

Taxonomy Tool

Site Search Tool

Portal

Project Archives

’

DMS’

Metatagging Tool

Search UI

2: NASA Taxonomy Teamdecides when to

update snapshots ofexternal CVs

4: Updated versions ofCVs to Consumers

NASA Taxonomy Governance Environment

3: Team adds value to snapshots through

definitions, synonyms, classification rules,

training materials, etc.

Internally CreatedCVs

Codes

NASA Competencies

CVs from otherNASA Sources

External StandardVocabularies

’

’

2: Taxonomy Team decides when to update CV snapshots

Taxonomy Facets

3: Team adds value via definitions, synonyms, classification rules, training materials, etc.

1: External controlled vocabularies (CVs) change on their own schedule

Taxonomy Governance Environment

4: Updated versions of CVs published to consumers

CV Consumers

CV Sources

Subject Codes

Expertise

Other Internal

External Standard

Site Search Tool

Portal

Working Papers

Web CMS

DAM

Tagging Tool

Search UI

Internally Created

Taxonomy Tool

CV = Controlled Vocabulary


Who should maintain the taxonomy?

The taxonomy (and metadata specification) should be produced by a cross-functional team which includes business, technical, information management, and content creation stakeholders.

The team should plan on maintaining the taxonomy as well as building it.

Maintenance will not (usually) be anyone’s full-time job. Exact mix of people on team will change.

It should be built in an iterative fashion, with more content and broader review for each iteration.


Taxonomy maintenance: Generic team charter

Taxonomy Team is responsible for maintaining: The Taxonomy, a multi-faceted classification scheme. Associated taxonomy materials, such as:

– Editorial Style Guides.– Taxonomy Training Materials.– Metadata Standard.

Team rules and procedures for change management. Taxonomy Team will consider costs and benefits of

suggested changes. Taxonomy Team will:

Manage relationship between providers of source vocabularies and consumers of the Taxonomy.

Identify new opportunities for use of the Taxonomy across the enterprise to improve information management practices.

Promote awareness and use of the Taxonomy.


Taxonomy team: Generic roles

Business Lead

Technical Specialist

Taxonomy Specialist

Content Specialist

Content Owners

Keeps committee on track with larger business objectives. Balances cost/benefit issues to decide appropriate levels of

effort. Obtains needed resources if those on committee can’t

accomplish a particular task.

Estimates costs of proposed changes in terms of amount of data to be retagged, additional storage and processing burden, software changes, etc.

Helps obtain data from various systems.

Committee’s liaison to content creators. Estimates costs of proposed changes in terms of editorial

process changes, additional or reduced workload, etc.

Suggests potential taxonomy changes based on analysis of query logs, indexer feedback.

Makes edits to taxonomy, installs into system with aid of IT specialist.

Reality check on process change suggestions.


Where taxonomy changes come from

experience

End User

Firewall

Taxonomy

Content TaggingLogic

ApplicationUI

TaggingUI

Tagging Staff

Taxonomy Editor

Staff notes

‘missing’concepts

Query log analysis

Requests from other parts of NASA

experience

End User

Taxonomy Team

FirewallFirewall

Taxonomy

Content TaggingLogic

TaggingLogic

ApplicationUI

ApplicationUI

TaggingUI

TaggingUI

Tagging Staff

Taxonomy Editor

Staff notes

‘missing’concepts

Query log analysis

Requests from other parts of the organization

Team Considerations

1. Business goals.

2. Changes in user experience.

3. Retagging cost.

Recommendations by Editor

1. Small taxonomy changes (labels, synonyms)

2. Large taxonomy changes (retagging, application changes)

3. New “best bets” content.

Application Logic


Taxonomy maintenance processes

Different organizations will need to consider their own change processes.

Organization 1: A custodian is responsible for the content, but checks facts with department heads before making changes.

Organization 2: Analysts suggest changes, editors approve, copyeditors verify consistency.

Organization 3: Marketing reps ask for a change, taxonomy editor makes demo, web representative approves it.

Change process MUST also consider cost of implementing the change

Retagging data. Reconfiguring auto-classifier. Retraining staff. Changes in user expectations.


Taxonomy maintenance workflow

Problem?

Problem?

Yes

Yes No

No

Suggest new name/category

Review new name

Taxon-omy

Copy edit new name

Add to enterprise Taxonomy

Analyst Editor Copywriter Sys Admin

Taxonomy Tool


Sample taxonomy editor: Data Harmony

Hierarchy Browser

Standard Term Info


Taxonomy editing tools vendors

Abi

lity

to E

xecu

telo

whi

gh

Completeness of VisionVisionariesNiche Players

Most popular taxonomy editor is

MS Excel

An immature area– No vendors are in

upper-right quadrant!

MultiTes is widely used, cheap with

functionality

High functionality

/high cost products ($100K+)


Taxonomy maturity model

Taxonomy governance processes must fit the organization.

As consultants, we notice different levels of maturity in the business processes around content management, taxonomy, and metadata.

Honestly assess your organization’s metadata maturity in order to design appropriate governance processes.

The following slides present results from a survey of metadata and taxonomy practices at 87 organizations. How does your organization compare?


2005 Maturity survey: Search practices

n=87Not current

practiceBeing

developed In practiceFormer practice

NA or Unknown

Search Box in standard place on all web pages. 20% (12) 11% (7) 62% (38) 2% (1) 5% (3)

Search engine indexes multiple repositories in addition to web sites. 25% (15) 21% (13) 44% (27) 2% (1) 8% (5)

Spell Checking. 31% (19) 18% (11) 38% (23) 0% (0) 13% (8)

Synonym Searching. 41% (25) 23% (14) 30% (18) 0% (0) 7% (4)

Search results grouped by date, location, or other factors in addition to simple relevance score. 37% (22) 20% (12) 37% (22) 0% (0) 7% (4)

Queries are logged and the logs are regularly examined 31% (19) 25% (15) 31% (19) 5% (3) 8% (5)

Common queries identified, 'best' pages for those queries are found, and search engine configured to return them at the top. (Best Bets) 46% (28) 25% (15) 21% (13) 0% (0) 8% (5)

Advanced computation of relevance based on data in addition to the text of the document. 43% (26) 16% (10) 25% (15) 0% (0) 16% (10)

A faceted search tool, such as Endeca, has been implemented for the organization's external site or product catalog search. 68% (41) 7% (4) 10% (6) 0% (0) 15% (9)

A faceted search tool, such as Endeca, has been implemented for the organization's internal website(s) or portal. 57% (34) 15% (9) 17% (10) 0% (0) 12% (7)


2005 Maturity survey: Metadata practices

n=87Not current

practiceBeing

developed In practiceFormer practice

NA or Unknown

Metadata standards are developed for the needs of each system with no overall attempt to unify them. 22% (13) 12% (7) 37% (22) 20% (12) 10% (6)

An Organization-wide metadata standard exists and new systems consider it during development. 37% (22) 37% (22) 20% (12) 0% (0) 7% (4)

The Organization-wide metadata standard is based on the Dublin Core. 52% (30) 16% (9) 21% (12) 0% (0) 12% (7)

Multiple repositories comply with metadata standard. 52% (31) 20% (12) 17% (10) 0% (0) 12% (7)

A Cataloging Policy document exists to teach people how to tag data in compliance with organizational metadata standard. 48% (29) 20% (12) 20% (12) 0% (0) 12% (7)

The Cataloging Policy document is revised periodically. 48% (29) 15% (9) 17% (10) 0% (0) 20% (12)

A centralized metadata repository exists to aggregate and unify metadata from disparate sources. 57% (34) 17% (10) 17% (10) 0% (0) 10% (6)

Metadata is manually entered into web forms. 15% (9) 12% (7) 61% (36) 3% (2) 8% (5)

Metadata is generated automatically by software. 38% (23) 18% (11) 27% (16) 2% (1) 15% (9)

Metadata is generated automatically, then reviewed manually for correction. 48% (29) 18% (11) 17% (10) 2% (1) 15% (9)


2005 Maturity survey: Taxonomy practices

n=87 Not current practice

Being developed In practice

Former practice

NA or Unknown

Org Chart Taxonomy - One based primarily on the structure of the organization. 36% (21) 10% (6) 34% (20) 5% (3) 15% (9)

Products Taxonomy - One based primarily on the products and/or services offered by the organization. 37% (22) 10% (6) 32% (19) 5% (3) 15% (9)

Content Types Taxonomy - One based primarily on the different types of documents. 28% (16) 21% (12) 40% (23) 5% (3) 7% (4)

Topical Taxonomy - One based primarily on topics of interest to the site users. 20% (12) 36% (21) 34% (20) 3% (2) 7% (4)

Faceted Taxonomy - One which uses several of the approaches above. 32% (19) 29% (17) 34% (20) 0% (0) 5% (3)

The Taxonomy, or a portion of it, was licensed from an outside taxonomy vendor. 75% (44) 3% (2) 14% (8) 0% (0) 8% (5)

The Taxonomy follows a written 'style guide' to ensure its consistency over time. 47% (28) 22% (13) 20% (12) 0% (0) 10% (6)

The Taxonomy is maintained using a taxonomy editing tool other than MS Excel. 35% (21) 17% (10) 40% (24) 2% (1) 7% (4)

The Taxonomy was validated on a representative sample of content during its development. 28% (17) 22% (13) 33% (20) 3% (2) 13% (8)

A Roadmap for the future evolution of the Taxonomy has been developed. 38% (23) 40% (24) 13% (8) 0% (0) 8% (5)

Strategies LLCTaxonomy

May 14, 2007 Copyright 2007 Taxonomy Strategies LLC. All rights reserved.

Questions?

Mike Lauruhn415-378-2747

[email protected]

Donna Fritzsche312-804-5629

[email protected]

Joseph A. Busch415-377-7912

[email protected]

Ron Daniel Jr925-368-8371

[email protected]


Taxonomy 1-2-3: Webography (1)

H. Chen, S. Dumais. “Bringing order to the web: automatically categorizing search results.” Proceedings of CHI 2000. pp. 145-152. http://research.microsoft.com/copyright/accept.asp?path=http://research.microsoft.com/~sdumais/chi2001.pdf&pub=ACM

Sue Feldman. “The high cost of not finding information.” 13:3 KM World (March 2004) http://www.kmworld.com/publications/magazine/index.cfm?action=readarticle&Article_ID=1725&Publication_ID=108

P.R. Hagen. Must search stink? Forrester Research, June 2000.

K. Hall. Content tagging strategies. Giga Information Group, February 2001.

M. Hearst, A. Elliott, J. English, R. Sinha, K. Swearingen & K. Yee. “Finding the flow in website search.” 45 Communications of the ACM (Sept 2002) http://www.ischool.berkeley.edu/~hearst/papers/cacm02.pdf

J. Morrison. “How to create effective taxonomy.” ZDNet Asia, August 18 2004. http://www.zdnetasia.com/builder/program/dev/0,39045513,39190441,00.htm


Taxonomy 1-2-3: Webography (2)

Jakob Nielsen. Web Design and Development.

Eric T. Peterson. “Home Depot uses Endeca to consolidate search and navigation, dramatically increasing conversion: case study.” Jupiter Research (July 11, 2005)http://www.jupiterresearch.com/bin/item.pl/research:casestudy/79/id=96483/

S. Phillips, E. Maguire, C. Shilakes. Content management: The new data infrastructure–Convergence and divergence out of chaos. Merrill Lynch, June 2001.

K.S. Taylor. "The brief reign of the knowledge worker," 1998. http://online.bcc.ctc.edu/econ/kst/BriefReign/BRwebversion.htm

Taxonomy & content classification: market milestone report. Dephi Group, 2002. http://www.delphiweb.com/knowledgebase/documents/upload/pdf/2176.pdf?session=%5Bg_sid%5D

Taxonomy Warehouse. www.taxonomywarehouse.com

Richard Saul Wurman. Information Architects (1996)


Vendors Taxonomy Editing Tools URLs

Knowledge Workbench www.convera.com/solutions/retrievalware/KnowledgeWorkbench.aspx

Cuadra STAR/Thesaurus www.cuadra.com/products/thesaurus.html

Thesaurus Master www.dataharmony.com/products/tm.htm

Knowledge Engineering Workbench

www.entrieva.com/entrieva/html_site/knowworkbench.htm

MetaTagger www.interwoven.com/products/content_intelligence/index.html

SmartDiscovery www.inxight.com/pdfs/Taxonomy_FinalWeb.pdf

MS Excel

Intelligent Topic Manager www.mondeca.com

MultiTes Pro www.multites.com

Taxonomy/Authority File Manager

www.nstein.com/epub/ncm-taxonomy.asp

Protégé http://protege.stanford.edu/

SchemaServer www.schemalogic.com

Synapticawww.factiva.com/products/taxonomy/synaptica.asp?node=menuElem1511

Taxonomy Manager www.teragram.com/solutions/taxonomy.htm

Term Tree www.termtree.com.au

Enterprise Vocabulary Server

www.webchoir.com/products/wvs.html

Designer www.wordmap.com/Enterprise/Taxonomy_and_metadata_management.html