BestWorstPractices presented

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Published on December 4, 2007

Author: Cubemiddle

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Metadata Best and Worst Practices:  Metadata Best and Worst Practices Ron Daniel, Jr. Joseph Busch Overview of Talk:  Overview of Talk Introduction Who we are Where we see corporate use of DC going Best & worst practices, and the current state Reminders on creating catalog records Remainder of Talk: Where we see corporate use of metadata and Dublin Core in 5 years What’s the current state of corporate metadata and Dublin Core? How do we get there from here? What to avoid along the way? Outline:  Outline Introduction One Potential Future for Corporate Metadata Basic Vision Limitations Current State of Corporate Metadata Areas for Greatest Improvement Worst Practices Conclusion Enterprise Metadata Layers:  Enterprise Metadata Layers Source: Todd Stephens, www.rtodd.com Using DC elements for Integration Metadata:  Legend: ? – 1 or more * - 0 or more Using DC elements for Integration Metadata dc:type=“recipe”, dc:format=“text/html”, dc:language=“en” Limitations of Previous View:  Limitations of Previous View Set of top-level applications very limited The ROI of these applications will ultimately drive the development of ‘enterprise’ metadata. Provides only one perspective on a very complex problem. Does not show: Practices used to create and maintain the information Tools used to create and maintain the information Growth of the system over time Cyclic nature of Semantic Metadata also being part of an Asset Collection … Based on our experiences, an organization’s culture and practices are vastly more important than the specific tools they select. Outline:  Outline Introduction One Potential Future for Corporate Metadata Current State of Corporate Metadata Areas for Greatest Improvement Worst Practices Conclusion Experiences with Corporate Metadata:  Experiences with Corporate Metadata “Integration Metadata” is an approach from a very sophisticated group within a sophisticated organization We encounter organizations at different levels of sophistication, which require different solutions. e.g. Entity Extraction software exists out-of-the-box, but is best applied when the entities are known. Will the organization be able to build and maintain such lists? To start to asses an organization’s level of metadata sophistication, we have begun to define a Metadata Maturity Model, based on similar ideas from software development. What’s a Maturity Model?:  What’s a Maturity Model? Began with the very pragmatic question: How can we predict the likelihood of a software development effort succeeding or failing? This question has led to the development of “Maturity Models”, the assumption being that more “mature” development shops will have a higher likelihood of success. Best-known is the CMMI (Capability and Maturity Model – Integrated) from the Software Engineering Institute at Carnegie Mellon University. Categorizes organizations into one of five maturity levels. Does it work? “…compared with an average Level 2 program, Level 3 programs have 3.6 times fewer latent defects, Level 4 programs have 14.5 times fewer latent defects, and Level 5 programs have 16.8 times fewer latent defects”. Michael Diaz and Jeff King – “How CMM Impacts Quality, Productivity,Rework, and the Bottom Line” Model is very complex and expensive to measure. Some accuse it of restraint of trade because of the impact on small software shops. CMMI Structure:  CMMI Structure Source: http://chrguibert.free.fr/cmmi Maturity Models are collections of Practices. Main differences in Maturity Models concern: Degree of Categorization of Practices Descriptivist or Prescriptivist Purpose Early levels look at planning, later levels look at metrics. At the Other Extreme, The Joel Test:  At the Other Extreme, The Joel Test Developed by Joel Spolsky as reaction to CMMI complexity Positives - Quick, easy, and inexpensive to use. Negatives - Doesn’t scale up well: Not a good way to assure the quality of nuclear reactor software. Not suitable for scaring away liability lawyers. Not a longer-term improvement plan. The Joel Test Do you use source control? Can you make a build in one step? Do you make daily builds? Do you have a bug database? Do you fix bugs before writing new code? Do you have an up-to-date schedule? Do you have a spec? Do programmers have quiet working conditions? Do you use the best tools money can buy? Do you have testers? Do new candidates write code during their interview? Do you do hallway usability testing? Scoring: 1 point for each ‘yes’. Scores below 10 indicate serious trouble. Source: http://www.joelonsoftware.com/articles/fog0000000043.html Aspects of Search and Metadata Maturity:  Aspects of Search and Metadata Maturity We are collecting business practices around metadata and taxonomy, and categorizing them by Area and Level “Limiting” Processes are harmful practices which interfere with maturity. So what’s the state of the art?:  So what’s the state of the art? Started a survey to find out Search Practices:  Search Practices Metadata Practices:  Metadata Practices Taxonomy Practices:  Taxonomy Practices Future Surveys:  Future Surveys Future surveys will cover other process areas: Team structure and job roles Metrics Categorization and metadata editing tools To participate, or stay informed of results, see link on our homepage – www.taxonomystrategies.com Outline:  Outline Introduction One Potential Future for Corporate Metadata Current State of Corporate Metadata Areas for Greatest Improvement Worst Practices Conclusion Data Quality Practices:  Data Quality Practices Data quality practices for descriptive metadata trail those from standard data management. How many of us implement practices like those in the Data Management Scorecard? For Integration Metadata to take hold, these will become more important. Not Adopted Fully Adopted Excerpt from Data Management Scorecard, Baseline Consulting What could possibly go wrong with a little edit?:  What could possibly go wrong with a little edit? ERP (Enterprise Resource Planning) team made a change to the product line data element in the product hierarchy. They did not know this data was used by downstream applications outside of ERP. An item data standards council discovered the error. If the error had not been identified and fixed, the company’s sales force would not be correctly compensated. “Lack of the enterprise data standards process in the item subject area has cost us at least 30 person days of just ‘category’ rework.” Source: Danette McGilvray, Granite Falls Consulting, Inc. 20 Taxonomy governance environment:  Published Facets Consuming Applications Custodians Notifications Change Requests & Responses ISO 3166-1 Other External ERP Other Internal Vocabulary Management System … ’ ’ Intranet Nav. DAM … Taxonomy governance environment Taxonomy Governance Environment 2: Team decides when to update facets within Taxonomy 3: Team adds value via mappings, translations, synonyms, training materials, etc. 1: External vocabularies change on their own schedule 4: Updated versions of facets published to consuming applications Outline:  Outline Introduction One Potential Future for Corporate Metadata Current State of Corporate Metadata Areas for Greatest Improvement Worst Practices Conclusion Worst Practices:  Worst Practices Building a taxonomy before knowing: How it will be shown to users, and what that UI will cost How the data will be tagged, and what that tagging will cost The benefits it is supposed to achieve Tools, then Requirements, then Purpose “Use it or lose it” budgeting Throwing good money after bad Sourcing part of the taxonomy from someplace that changes it without warning No consideration of metrics How to estimate costs— Tagging :  How to estimate costs— Tagging Inspired by: Ray Luoma, BAU Solutions Consider complexity of facet and ambiguity of content to estimate time per value. Estimated cost of tagging one item. This can be reduced with automation, but cannot be eliminated. Is this field worth the cost? Sample ROI Calculations:  Sample ROI Calculations Inspired by: Todd Stephens, Dublin Core Global Corporate Circle Ongoing cost of tagging due to 15% content growth. Outline:  Outline Introduction One Potential Future for Corporate Metadata Current State of Corporate Metadata Areas for Greatest Improvement Worst Practices Conclusion Future of DC within Corporations:  Future of DC within Corporations Dublin Core receiving considerable attention within corporations Implementations are happening, but not universally What will help cross the chasm? Tie-ins with standard tools, such as Google Enterprise, SAP, … Integration metadata, not new metadata! Continued presence of DCMI Documents, tools, case studies, presence I Innovators EA Early Adopters C Chasm P Pragmatists (Early & Late Majority) T Traditionalists Source: Moore, G. A. Crossing the Chasm, 1991 Technology Adoption Curve # Adopters Time Questions?:  Questions? Thank you! Controlled item: Communications plan:  Controlled item: Communications plan Stakeholders: Who are they and what do they need to know? Channels: Methods available to send messages to stakeholders. Need a mix of narrow vs. broad, formal vs. informal, interactive vs. archival, … Messages: Communications to be sent at various stages of project. Bulk of the plan is here

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