1. Leveraging Metadata to Improve Findability, Records Management, and Compliance in SharePoint Martin Garland, President marting@conceptsearching.com

4. Search

5. Compliance & Records Management

6. Privacy and Security Exposures

7. Collaboration

8. Manual Metadata Approach will fail

9. The ROI of Managing Unstructured Content Assets

10. Benefits of metadata consistency, automated classification and taxonomy management

11. Technology Suite

12. Roadmap to SharePoint 2010

14. Product launched in 2003

15. Focus on management of structured and unstructured information

16. Privately held and profitable – no funding

17. Growth rate of 35% in 2008 and in excess of 100% for 2009

18. Founders and management team with company since inception

19. Technology

20. Automatic concept identification, content tagging, auto-classification, taxonomy management

21. Only statistical vendor that can extract conceptual metadata

22. 2009 and 2010 ‘100 Companies that Matter in KM’ (KM World Magazine)

23. KMWorld ‘Trend Setting Product’ of 2009

24. Locations: US, UK, & South Africa

25. Client base: Fortune 500/1000 organizations

26. Managed Partner under Microsoft global ISV Program - “go to partner” for Microsoft for auto-classification and taxonomy management

27. Microsoft Enterprise Search ISV , FAST Partner

29. Inconsistent, subjective, costly

30. Inability to harvest and reuse intellectual capital

31. Lack of organizational memory – most organization’s don’t know what they already know

32. Semantic identification of concepts

33. Vocabulary Normalization

34. Inability to share expertise and knowledge across geographic and cultural barriers due to inconsistent nomenclature

35. Inability to deliver consistency across global boundaries and even within practice areas

36. Folksonomy dilutes metadata value

37. Search alone does not deliver ‘findability’

38. Inability to manage knowledge assets so that relevant information can be found and used

39. Retrieval of information based on keywords or proximity does not deliver relevance as to what concepts the document contains

40. Continuously replacing your search engine will not fix search

42. Most information retrieval technologies are less than 22% accurate for both precision and recall

43. Ideal is to have them balanced

44. Recall is the retrieval of all items that are relevant to the query

45. Precision is the retrieval of only those items that are relevant to the query

46. Higher precision leads to missing items that may be relevant but use a different vocabulary

47. Higher recall leads to the retrieval of too many items that may be unrelated to the query Automatic Concept Identification has the ability to increase precision with no loss of recall

49. Deliver a robust content management approach maximizing SharePoint technologies

52. Preserve record integrity

54. Improve information sharing and expert identification reducing rework and recreation

55. Integration with external repositories, web sites delivering a single searchinterface

57. Users can’t navigate to information. Taxonomies provide consistent guided navigation for end users to extract relevant information even in external content. Taxonomy navigation is 36%-48% faster and more efficient than lists.

58. Vocabulary normalization across diverse geographies and cultures causes issues and inhibits sharing of knowledge and expertise due to nomenclature.

59. Case Study: Fortune 500 firm realized that search alone did not solve findability issues. Implemented conceptClassifier to secure and manage content in a policy-compliant manner, eliminated end user tagging, delivered the ability to rapidly build and deploy taxonomies, and to normalize vocabulary across global boundaries.KNOWLEDGE WORKERS CHALLENGES ~ 15% of their time is spent duplicating information. ~ 25% of their time is spent searching. ~ 40% can not easily find the information they require to do their job. The cost to a 500 employee company is $2.4 million per year in inefficiencies and lost productivity. Gartner Group

61. Ensures adoption to any enterprise regulation for external agencies or where compliance is mandatory

62. Easy Integration with Microsoft Records Center. Ensures the long term usefulness of the records and enforcement of life cycle management.

63. Automatic assignment of Records Retention codes

64. Optional updating of Content Type based on the metadata contained within the documents

65. Case Study: US Air Force Medical Service eliminated all manual metadata tagging and uses conceptClassifier to automatically generate semantic metadata, assign record retention codes based on the metadata within the content, automatically change the Content Type and migrate documents to the RMCOMPLIANCE & RECORDS MANAGEMENT CHALLENGES ~ The average cost of manually tagging one item is estimated at $4.00 - $7.04 ~IDC estimates that only 50% of content is correctly meta-tagged ~ It costs and organization $180 per document to recreate it when it is not tagged correctly and cannot be found ~ Poor information quality costs organizations 10% to 20% of operating revenues

67. Migrates content to a secure location where Windows Rights Management Services is applied to the file in the new location

68. Optionally can change the Content Type during the classification process

69. The taxonomy standardizes the process of identifying all possible privacy data exposures at the time of content creation and modification (digital and handwritten).

70. Case Study: conceptClassifier for SharePoint extracted 2,000+ documents with sensitive information, from a redacted sample pilot data set. By human error, these 2,000 records contained real social security numbers and real employee information. These documents were identified in the proof of concept to the client in front of executive management.DATA BREACHES & EXPOSURES CHALLENGES ~ Average cost of a data breach is $6.3 million and ranges from $225K to $35 million. ~ Average cost per exposed record is $197 and ranges from $90-$305 per record. ~ 70% of breaches were due to a mistake or malicious intent by an organization’s own staff. ~ Healthcare provider - $7 million, TJX Companies - $256 million, ValueClick - $2.9 million.

72. Generate weighted results from diverse repositories such as human resources records, time and billing, project documentation, content authorship, team structures, user profiles

73. Results are generated based on the most experienced and knowledgeable individual for that specific topic or skill set aggregated from diverse repositories

74. Single logical view for expertise search across diverse information stores

75. Removes geographical boundaries through vocabulary normalization

76. Case Study: Professional Services firm with over 39K employees across 36 countries uses conceptClassifier for expert identification to identify and utilize in-house consultants for projects as opposed to outsourcing – increasing utilization of staff by 5% to 10%Collaboration and Enterprise 2.0 ~ Nearly 80% of executives believe collaboration is important but needs to be managed ~Email storage costs $500GB per year – a Fortune 100 manufacturing company saved $2.6 million per year by implementing collaboration solutions ~ Up to 90% of content from premium paid publication database services is available for free on-line ~ Only 25% of executives describe their organization as effective at sharing knowledge across boundaries

77. A Manual Metadata Approach Will Fail 95% Of The Time

79. Average return on investment minimum of 38% and runs as high as 600% (IDC)

80. Apply consistent meaningful metadata to enterprise content

81. Incorrect meta tags costs an organization $2,500 per user per year – in addition potential costs for non-compliance (IDC)

82. Guide users to relevant content with taxonomy navigation

83. Savings of $8,965 per year per user based on an $80K salary (Chen & Dumais)

84. Use automatic conceptual metadata generation to improve Records Management

85. Eliminate inconsistent end user tagging at $4-$7 per record (Hoovers)

88. Search will return results based on the concept even if the exact terms are not contained in the document (i.e. ‘coronary artery surgery’, ‘heart surgery’)

89. Metadata can be used by any search engine index or any application/process that uses metadataTriple Baseball Three Heart Organ Center Bypass Highway Avoid

91. Automatic identification, extraction, and tagging of content with concepts

92. Intelligent auto-classification based on concepts not keywords

93. Enterprise class Taxonomy Management, uniquely based on concept identification

94. Integration

95. A technology platform that runs natively in SharePoint 2007 and 2010

96. Microsoft Enterprise Search, FAST ESP

97. Microsoft Office

98. Windows Server 2008 R2 FCI

99. Component – Automatic Conceptual Metadata Generation

100. Automatically generates and extracts metadata including keywords, acronyms, and multi-word terms that form concepts and convey meaning

101. Component – Automated Classification

102. Rules based categorization module

103. Real-time classification of individual pieces of content aligned to defined business structure(s)

104. Automatically classifies documents to multiple nodes in multiple taxonomies

105. Highly scalable, fast real-time classification

106. Classifier may be called via web services, or by other related applications (e.g.: FAST pipeline stage)

108. Hierarchical taxonomy structure with ontological features and ability to import standard structures such as OWL and RDF

109. Rapid taxonomy creation and maintenance

110. Automatic concept identification extracted from clients own content to populate taxonomy(s)

111. Class clues generated from client’s unique document corpus

112. Dynamic movement feedback

113. Maintenance via clue suggestion, integrated search, and instant feedback

114. Class weighting influenced by parent, child, sibling

115. AJAX based user interface

116. Taxonomy structure and classification results held in SQL database

117. Component - contentTypeUpdater

119. SOA compliant and delivered as Web Parts

120. API is based entirely on Web Services and all information is exchanged in XML T

121. Taxonomy formats are based on Web Ontology Language (OWL). Since the server is stateless it also works with all failover and load balancing hardware and software.

123. There is no way to automatically generate metadata when it is created or ingested

124. Same problem with end users adding inconsistent metadata

125. Taxonomy management is a manual process

126. Taxonomy maintenance requires significant resources to maintain and change as business changes

127. Enterprise Metadata Management

128. Properties (current flat lists) become hierarchical “Term Sets” –

129. Term Sets provide capability for faceted search and hierarchical navigation: Regions Country/State, Business Unit/Departments, Band Names/Album Names, TV Show Titles/Characters

130. conceptClassifier fully supports SharePoint 2010 EMM as the primary location for taxonomy definitions with no need to Import/Export

132. Provides taxonomy browse capabilities based on the nodes within the corporate taxonomy(s)

133. Provides accurate metadata filters such as numeric range searching and wildcard alphanumeric matching

134. Improves search outcomes by placing conceptual metadata in the FAST Search index to increase relevancy of search results

135. Enables import of FAST Entities into the conceptClassifier taxonomy manager to fine-tune them with metadata generated from your own content and nomenclature

136. Runs natively as a FAST Pipeline Stage eliminating integration and customization issues

138. Initially deployed conceptClassifier to power Knowledge Portal with over 65K users

139. Controlled vocabulary consists of over 27K unique keywords, metadata, and multi-word fragments generated by conceptClassifier

140. Have expanded use of technology to provide the following:

141. Automatically organize data assets prior to migration to SharePoint - identifies duplicates, PII, PHI before migration

142. Automatically extract metadata and classify to the various taxonomies

143. Provide Microsoft Enterprise Search and FAST indexes the conceptual metadata to improve findability

144. Identification and location of sensitive information (PII, PHI, Confidential) and migrates content to new location where Windows Rights Management Services are applied

145. Automatically tags and classifies content based on semantics contained within the actual document of record and optionally updates the Content Type

146. Eliminates end user tagging issues

147. Records are declared in a consistent manner

148. Only real records are migrated to the RM system

149. Only real records are managed for disposition

150. All other content stays in the collaborative portal

151. Freedom of Information Act (FOIA) compliance

153. DoDD 5015 (Records Management)

154. USAF Privacy Act Program & HIPAA

155. Freedom of Information Act (FOIA)Distribution Statement A: Approved for public release; distribution is unlimited. 311 ABG/PA No. 09-488, 16 Oct 2009

156. Screen Shots

158. Browsable taxonomy navigation via Concept Searching Web Part

160. Taxonomy Browse

162. Content is automatically classified to one or more nodes in one or more taxonomies

163. Documents are automatically classified to multiple categories

165. Enforces governance, policies, and drives workflows in line with business processes

166. Enables different taxonomies to be assigned to different Content Types

168. Content automatically tagged with semantic metadata stored in custom properties

169. Content automatically classified to corporate or departmental taxonomies

170. Delivers governance at the desktop, improves ECM

172. SharePoint

173. Web Sites

174. Exchange Public folders

175. File stores

176. Can also include RSS feeds

178. Content will be automatically classified to one or more nodes based on concepts within the content

179. Reduces time to develop, build, and maintain a taxonomy by as much as 80%

181. Suggest Clues for Class

182. Search the document corpus and identify documents that are about the new node to be included or excluded