Metadata and Taxonomies The Best of Both Worlds

Tom ReamyChief Knowledge Architect

KAPS Group

Knowledge Architecture Professional Services

http://www.kapsgroup.com

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Agenda

Taxonomy Good, Metadata Bad– To Metadata or not to Metadata– Issues and Approaches to Metadata

Taxonomies, Browse, Facets, and Metadata– Strengths and Weaknesses– Uses and Value of Each

Knowledge Architecture Solutions– Putting the Pieces Together: Why, Who, How– Deep Personalization and Other Advanced Applications

Conclusion – How do I get there from here?

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Metadata about Metadata: Two Sources

Global Corporate Circle DCMI 2003 Workshop– Importance of Metadata– Difficulty of implementation and justification

KAPS Group Experience– Consulting, Taxonomy & Metadata, Strategy – Knowledge architecture audit– Partners – Inxight, Convera, etc.– Intellectual infrastructure for organizations

• Knowledge organization, technology, people and processes• Search, CM, portals, collaboration, KM, e-learning, etc

EContent October Article – To Metadata or not to Metadata

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Taxonomy Good, Metadata Bad

To Metadata or not to Metadata That is the Question Whether ‘tis nobler in the mind to suffer the slings and

arrows of outrageous search results Or to take up metadata against a sea of irrelevance And by organizing them find them?

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To Metadata or not to Metadata?

Why Not Metadata?– Costly - $200K to set up, maintenance costs– Difficult to do

• Missing, incorrect, confusing, inconsistent• Poor quality metadata can make search worse

Why Metadata?– Not doing Metadata is more expensive

• $8,200 an employee a year– Ways to lower the cost – not all custom jobs– Need more sophisticated ROI – stories, business needs,

requirements

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Metadata Approaches: 4 Not So Good Alternatives

Metadata, we don’t need no stinking metadata– Condemned to wander search results lists forever– Need to answer these people

KA Team – Consultants– Costly, Still need to maintain

Automatic metadata (clustering & categorization)– Uneven, poor quality

Author generated metadata– Uneven quality, inconsistent– Cultural – getting authors to want to do it

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Knowledge Architecture Solutions: The Right Context

No one solution– Can’t answer content questions from perspective of content alone – need to understand users and activities and organization

Context – understanding your context– Match amount of metadata to value– Match type of metadata to content and use– Lower the cost and increase the value

The problem is not that metadata initiatives have been too complex, it’s been that they have been too simple.

– Metadata is more than adding keywords as an afterthought For same or less effort, you can go from metadata that makes

search worse to a set of solutions

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Taxonomies, Browse, Facets, and MetadataVariety of Structures A hierarchy does not a taxonomy make

– Thesaurus (BT, NT, Related Terms), Controlled Vocabulary– Catalog, Index, site map, Partonomy, Ontology, – Classification, Semantic Network– Knowledge Map, Topic Maps, Paradigm, Prototype

4 Basic Structures– Formal Taxonomy – Aristotle & Linnaeus

• Concept of Species, Is-A-Kind-Of (Part)– Browse Taxonomy

• Yahoo – hierarchical classifications– Metadata

• Dublin Core – Titles, Descriptions, Keywords, +– Facets/Entities

• Products, Companies, People, Events, Geography

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Taxonomies, Browse, Facets, and Metadata Four Basic Structures Units of Organization

– Taxonomy – Concepts– Browse Taxonomy – web site or content collections – Facets – Entities– Metadata – variety of values

Metadata – After or About Data– Not just documents – objects, art works, events, etc– Characteristics about the objects– Characterization of content (meaning) within object

It’s All Metadata to Me!– Browse – reverse metadata– Facets - metadata fields or sub-domains of Keywords– Taxonomy – Controlled Vocabulary

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Taxonomies, Browse, Facets, and Metadata Strengths and Weaknesses

Formal Taxonomy Strengths– Fixed Resource - Little or no maintenance– Communication – share ideas, build on others– Infrastructure Resource

• Controlled vocabulary and keywords• Indexing – conceptual relationships

Weaknesses– Difficult to develop and customize– Don’t reflect user’s perspective

• User’s have to adapt to language

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Taxonomies, Browse, Facets, and Metadata Types of Taxonomies – Yahoo Browse

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Taxonomies, Browse, Facets, and Metadata Strengths and Weaknesses Browse Taxonomy Strengths

– Browse better than search• Context and discovery

– Easiest Structure to Develop

Browse Taxonomy Weaknesses– Mix of Organization

• Catalogs, Alphabetical listings, Inventories– Vocabulary and Nomenclature Issues– Difficult to maintain– Poor granularity and little relationship between parts.

• Web Site unit of organization– No foundation for standards

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Taxonomies, Browse, Facets, and Metadata Strengths and Weakness

Metadata Strengths– Variety of Fields supports variety of applications, user

behaviors – Well developed best practices

Metadata Weaknesses– High Cost of Implementing– Inconsistent values– Studies show little value in search

• Have to do it completely and correctly to get any value

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Taxonomies, Browse, Facets, and Metadata Strengths and Weakness

Facets Strengths– Orthogonal Categories – easier to understand what

goes in what bin and why– Combination of formal (partonomy) and browse– Automatic Software works

Facets Weaknesses– High Cost – adding structure to facets– Can be overwhelming – 30 or more facets

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Knowledge Architecture SolutionsMetadata

Look beyond authors adding keywords to influence search results

Value from All Fields– Titles and Descriptions – balance of system and description– Publisher and author – automated and easy– DocumentObjecttype – FAQ’s, Policy Doc – supports user

behavior– Audience – target information, agents – no need for search– Facets – additional fields to support multiple use

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Knowledge Architecture SolutionsMetadata Keywords – most difficult

• Common terms, unique terms, aboutness terms• Need to do it right and completely to get real value

Keywords - Need Taxonomy, Controlled Vocabulary – Enhance quality, consistency– Supports author generated metadata

Value from other applications– Alerts and variety of personalization schemas– Data and Text Mining– Inter-application communication

Controlled Vocabularies– Form, Format, Language, Audience, etc.– Structured – taxonomies– Multiple subjects = multiple taxonomies

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Knowledge Architecture SolutionsMetadata

Tools– Content Management, Metadata Management

People– Central – evaluate and select taxonomies

• Facilitate use of controlled vocabulary taxonomies• Monitor and measure use of metadata and taxonomies

– Authors – select from list is better, easier• Automated support and work flow

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Knowledge Architecture SolutionsTaxonomies General Intellectual Resource

– Powerful Vocabulary, Glossary, Index– Standards, Naming Conventions – Communication Tool

Pre-defined Taxonomies vs. Custom Taxonomies– Pre-defined – Cross Organization Communication– Custom – specialized vocabularies– Best – Standard, Pre-defined taxonomies that are customized according to a

set of established best practices Value from Taxonomies

– Indexing documents – to a very granular level – automatic– Cross application communicaiton – exchange meaning, not just bits– Dynamic Classification – structured search results

• Works even while advanced search does not• Not Browsing

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Knowledge Architecture SolutionsBrowse Taxonomies

Limited Depth (User’s set the limit)– Navigation to collections of content, web sites– Limited Content – single web site or section of web site

• Best for homogenous audience, common vocabulary, view

Limited Rigor– Search and Browse better than either– Broad, multiply defined categories give poor results

Combine with Facets and Taxonomies– Categories as clusters of taxonomy levels

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Knowledge Architecture SolutionsFacets

Combine Browse and Search– Structured results not advanced search– More flexible than navigation browse– Still Limited Depth – combine with classifications

Combine with Taxonomies– Added structure, especially subject areas

Selection of Facets – Ontology, Personalization See Flamenco Project

– http://bailando.sims.berkeley.edu/flamenco.html

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Knowledge Architecture SolutionsFacets

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Knowledge Architecture Solutions Integration: It’s All Metadata to Me!

Metadata the framework for value from Taxonomy and Facets

Metadata, Taxonomies, and Facets add value and structure to search

Taxonomy adds structure to Facets and Metadata Facets add formal extensibility to Taxonomy Facets add structure to Metadata and Browse Taxonomies Integrated solution – the right mix for variety of applications

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Knowledge Architecture Solutions: The Right Context

Content – structured & unstructured, external & internal– Publishing Policy and Procedures– Metadata, taxonomies and controlled vocabularies

• Standards and Best Practices

Business processes and requirements Technologies – search, portals, CM, applications

– CM is the right time for adding metadata, • Automation, distributed work flow

– Analytics based on meaning, not clicks– Look at the entire range of applications

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Knowledge Architecture Solutions: People

Communities of users and information behaviors Variety of authors, subject matter experts, publishers Central Team supported by software and offering services

– Creating, acquiring, evaluating taxonomies, metadata standards, vocabularies

– Input into technology decisions and design – content management, portals, search

– Socializing the benefits of metadata, creating a content culture– Evaluating metadata quality, facilitating author metadata– Analyzing the results of using metadata, how communities are using– Research metadata theory, user centric metadata – Design content value structure – more nuanced than good / poor

content.

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Knowledge Architecture Solutions: Why?

Metadata as add on to a search engine purchase will fail Most cost effective way to produce valuable metadata Needed to implement any alternative approach

– Justification for metadata - measure and present realistic ROI– Supplement consultants– Integrate automated and author supplied metadata– Integrate content tiers into broader context

Needed for tailoring solutions to organizations

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Knowledge Architecture Solutions: Why?

Increase the value of creating metadata– Better quality metadata

• Categorization experts and subject matter experts– Beyond Search and relevance ranking

• Dynamic classification – intersection of 2 subjects• Applications – integrated metadata for portals, agents, etc

– Beyond content – people metadata:• Community personalization, information behaviors• Community categorization

Decrease the cost of creating Metadata– Start with Standards, Distributed System and Cost

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Knowledge Architecture Solutions: What if I can’t get there from here? First Step – Create an infrastructure strategic vision

– Including metadata standards KA Team – can be part time, needs official recognition Content Management is essential Don’t start with keywords Buy and customize taxonomies, controlled vocabularies Relevance ranking as last resort

– Best bet metadata– Browse and dynamic classifications– Faceted Displays

Think Big, Start Small, Scale Fast

Questions?

Tom Reamytomr@kapsgroup.com

KAPS Group

Knowledge Architecture Professional Services

http://www.kapsgroup.com