20070328 Information Management

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Information about 20070328 Information Management

Published on February 18, 2009

Author: mumlan

Source: slideshare.net

Description

Presentation about challenges with Information management and Unstructured Information

UNSTRUCUTURED INFORMATION MANAGEMENT UNSTRUCUTURED INFORMATION MANAGEMENT  INSIDE THE BOX.... Optimization of accessibility for business value p y

AGENDA Obstacles to information access • Key success factors for information  Key success factors for information • access How can an organization make sense  • of its unstructured information?  of its unstructured information? The information management  • tongue  Practical examples of information a  • retrieval solution that combines  different technologies to assist sense  making ki

AGREEMENT ON  BASICS: INFORMATION VALUE CHAIN LEVEL OF SYNTHESIS (ANALYSIS) AND  CONTEXT ( ) FUTURE PAST PASSIVE PRESENT ACTIVE PROACTIVE Contextualized Consequences Categorized Connections Calculated Conversations DATA INFORMATION INTELLIGENCE Corrected Chances Condensed Compared Connections Calculated Intelligence becomes information when not needed Data becomes information when asked for Information becomes data when not needed INFORMATION VOLUME

AGREEMENT ON BASICS:  THE CONTENT UNIVERSE More information will be produced in 2007 than in the previous 300,000 years combined.  More information will be produced in 2007 than in the previous 300 000 years combined Unstructured Digital Print External Structured Internal Unstructured  external Semi Structured  Internal It l Structured Internal

OBSTACLES FOR EFFECTIVE INFORMATION ACCESS the challenges are greater inside the box than outside... The user‐ CTO/CIO‐ leadership divide leadership divide Content creation  p process ‐ Format 8/16 behavior & 8/16 behavior &  culture The Microsoft  Syndrome Single keyword... Technology The Google  g Syndrome Communication Languages

THE USER‐CTO/CIO‐ THE USER‐CTO/CIO‐LEADERSHIP DIVIDE WE HAVE CREATED A COMPUTERIZED, INTERACTIVE ARTIFICIAL INTELLIGENCE PROFILING INTRANET WONDERFUL. MAKE SOME DEVICE FOR THE COMPANY WITH PHOTOCOPIES AND ROUTE IT ENTITY EXTRACTION AGENTS AND AROUND. VIZUALIZATION. VIZUALIZATION I CALL IT THE ”I- I- BUT I REALLY ONLY ASKED CENTER” AND IT CONTAINS A BASIC FOR THE NAME OF THE TAXONOMY WITH A USER GENERATED MANAGER IN OUR ITALIAN FOLKSONOMI FUNCTION! COMAPNY

OVERVIEW – THE USER ‐CTO/CIO‐ OVERVIEW – THE USER ‐CTO/CIO‐LEADERSHIP DIVIDE The different stakeholders within an organization use different lenses when they look at information.   The challenge is to find  ONE infrastructure that accommodates all these disparate needs‐ so that by  the end of the day, it serve the same purposes – fulfilling the business objectives. • Looks for the big picture • Strategic intentions and objectives are not always communicated  well STRATEGIC • Not agile users of systems and technology, and if... Decisive  LEVEL • Information flows are selective • Financial driven • Focused on answers • Infrastructure focused. OPERATIONAL • Turf battles about resources and solutions (Priority) y • IT‐driven, not user driven LEVEL • Focused on integrated tasks  • Day to Day struggle Day to Day struggle • Actual information needs for solving questions TACTICAL  • User and content driven LEVEL • The devil is in the details • Foused on one task  d k

OVERVIEW – OVERVIEW – CONTENT CREATION PROCESS Microsoft Office suite might be  one of the worst enemies for corporate repository retrieval. Add  Adobe and some dysfunctional CRM‐systems to this and you have a challenge • Usually sees only carefully tailored reports in one single format  STRATEGIC that is easy to digest LEVEL • Rarely contributes to the knowledge repository  OPERATIONAL • Connections,  cross‐unit , cross stakeholder challenges. • Different solutions  ‐ we need to this our way.... LEVEL TACTICAL  • I want to use the same tools that I have at home • It is good to recycle from old documents and PowerPoints LEVEL

OVERVIEW – OVERVIEW – THE DREAM OF A COMMON LANGUAGE Even if you think you speak the same language, you don´t.  Even if you search in your language you  wont find everything that is written in the language you think is your own. • Corporate language ( spoken /written) • The client/customer language (spoken/written) STRATEGIC • The management buzz language • The industry tounge y g LEVEL • Culture • Lingua Searcha OPERATIONAL • Culture LEVEL • The vertical languages‐ and how to integrate the The vertical languages and how to integrate the • Vertical language TACTICAL  • ”Street speak” LEVEL • Popular names

OVERVIEW – OVERVIEW – LINGUA SEARCH IN REALITY One way of assisting both search engines and humans in finding the relevant answers is to match  documents against different set of defined universe. A taxonomy define the organizational environment  on a high level. An  organizational taxonomy should be aligned to the business objectives and  STRATEGIC strategies.  ( Category, bucket, silo, domain) A taxonomy can be used in the  content creation process by meta‐tagging the documents. LEVEL A controlled vocabulary assist in the classification on a more detailed  level in a domain, than the overarching taxonomy. The controlled set can  level in a domain than the overarching taxonomy The controlled set can be of different size depending on the complexity of  the defining term.   A  OPERATIONAL controlled vocabulary  can assist in automatic tagging of articles. The  relationships in a domain is called an ontology. LEVEL An ontology assist in creating relations between different entities and  provide a context by linking words and docuements to eachother. End user generated vocabularies can assist in  sense making an  knowledge sharing  on the very detailed level  but also on a  TACTICAL  macro/document level  ( folksonomy) by  dynamically map and  assist in  validation, quality and relation control  a on micro level. LEVEL

CONCEPT: TAXONOMY •Taxonomy is the science of classification according to a pre‐ determined system, with the resulting catalogue used to provide a  conceptual framework for discussion, analysis, or information  retrieval. retrieval •A systematic way of classifying knowledge •A hierarchical structure of concepts A hierarchical structure of concepts TAXONOMY •A common language for sharing knowledge •An artificial, formal construct acting as a symbolic model of an  information domain •In theory the development of a good taxonomy takes into In theory, the development of a good taxonomy takes into  account the importance of separating elements of a group (taxon)  into subgroups (taxa) that are mutually exclusive, unambiguous,  and taken together, include all possibilities.  •In practice, a good taxonomy should be simple, easy to remember,  and easy to use. 

•Group content into a controlled set of  categories  TAXONOMIES  AGAIN? •There is no inherent relationship among the  categories ‐ they are co‐equal groups with labels •The structure is one of ‘membership’ in the  taxonomy •List of industries List of industries •Lists of countries or states Energy    Environment   Education   Crime       Transport  Trade   Labor   Agriculture •Lists of currencies Faceted taxonomy architecture looks like a  •Controlled vocabularies star.  Each node in the star structure is  •List of security classification values associated with the object in the center.   associated with the object in the center Metadata is one type of faceted taxonomy A hierarchical taxonomy is  Each attribute is a facet of a content object  represented as a tree  Creator/Author architecture. The tree consists of  architecture The tree consists of Title Publication Date, etc nodes and links. The  relationships become  ‘associations’ with meaning.   Meanings in a hierarchy are fairly  limited in scope – group  li it d i membership,  Type, instance.  In a hierarchical  taxonomy, a node can have only  In a network one parent.      taxonomy each node can have more than one parent. Any item in a this structure can Network taxonomies allow us to be linked to any other design complex thesauri thesauri, item. item Links can be ontologies, concept maps, topic meaningful & maps, knowledge maps, different. knowledge representations

SO WHAT IS IT? Concept Definition (one interpretation) What is it good for? Taxonomy is the science of classification according to a  Provides a  top structure  Taxonomy predetermined system used to provide a conceptual framework  for storing and retrieving for discussion, analysis or information retrieval. f di i li if ti ti l A controlled vocabulary is an organized lists of words and  Assist in tagging retrieving Controlled phrases, or notation systems, that are used to initially tag  documents vocabulary content, and then to find it through navigation or search. This  g g means that a CV is a type of metadata that functions as a subset  of natural language. An ontology is a model that represents a set of concepts within a  An ontology defines a  gy p p gy Ontology domain and the relationships between those concepts. A  domain domain ontology (or domain‐specific ontology) models a specific  domain, or part of the world. It represents the particular  meanings of terms as they apply to that domain. Most  g y pp y ontologies describe individuals (instances), classes (concepts),  attributes, and relations User generated input Socially constructed classification schemes . User‐generated  Folksonomy metadata  metadata ”tactical level” tactical level Information that describes, or supplements, the central  data.  Can provide some context, Metadata but not always.

TECHNOLOGY CHALLENGES Sounds great, I read Yeah whatever, that portals will change our as long as I need your signature for life and will connect the I will have this on the corporate information hidden gems in my CV, and no one software acquisition I love this our company. interferes with portal Will be great to tell my pr j ct project approach! h! our board that we What a have a Intelligence Portal! change! IT staff too often get carried away with adding functionality and data that the end user  just does not need. j td t d Organizations need to look beyond technology and its architecture when  implementing tools, and consider a much broader integrated focus that  p g , g simultaneously addresses organizational and process issues

OVERVIEW – OVERVIEW – TECHNOLOGY CHALLENGES One of the most common challenges among  we have noticed among our clients is to store and  retrieve information in various formats in one user‐friendly environment that also is open for further  exploration in various tools.  • Tools offered on the market as “ the solution  are often expensive  Tools offered on the market  as  the solution” are often expensive and the ROI is low EXPENSIVE • Maintenance costs are high. • Lock in situation once ”the” solution is in place. The outside world  move on move on • Tools are crowded with technical solutions and gadgets that makes  simple tasks cumbersome  and time consuming. COMPLICATED • High threshold for training High threshold for training • IT‐driven, not user driven • Not targeted to the organizational objectives g g j NOT ALIGNED TO  NOT ALIGNED TO • Old information/SYSTEMS that crowds the space and slows down  BUSINESS the “solution”

DIFFERENT TECHNOLOGIES ASSIST IN THE INFORMATION TO  INTERPRETATION  VALUE CHAIN Interpretation of new  Visualization insights through  insights through applications Taxonomy Expertise Relationships Alerts / Profiling Extract valuable  Clustering g Classification Summarization insights through  i i ht th h mining techniques Feature Extraction Language Identification Search / Retrieval (Indexing)  Search / Retrieval (Indexing) Access the available  Document Filters information Connectors (Spiders, Crawlers) C (S id C l) Stored information Databases Content Management File Repositories 1 6

SUMMARY User generated validation,  quality control and  contextual  rights A search/ retrival fuction  that is open  and that accomadates contextual search  A content management /creation structure &  p py philosophy A basic taxonomy (simple) An information audit – who needs what and when and why? Communcation of   business/orgaizational objectivess g j

EXAMPLES

READ IN DEPTH, IN CONTEXT The chart below shows GM’s stock price, credit spread and related news article volume over time.  The chart is also  Th h t b l h GM’ t k i dit d d ltd ti l l ti Th h t i l annotated by headlines on days with big moves in the chart, providing a multi‐dimensional overview and suggesting  what news may have affected GM’s market prices or vice versa 1 9

PATENTS The search result for  “ethanol” provides related  “h l” id ld patents, structured data  about the compound and its  taxonomy belonging, charts  illustrating patent  publication trends and the  most relevant inventors,  grantees and legal  representatives as well as  related compounds,  keywords, processes,  reactions and subclasses.   Every item is clickable for  drill‐downs and equivalent  360‐degree views.  2 0

FIND KEY CLUSTERS OF PEOPLE The visualisation tools can be  used to cluster the most  prominent inventors (and /or any  i ti t ( d/ other entity/term type) around a  specific company (deduced from  the patent data) for competitive  p ) p intelligence purposes 2 1

LIVE DEMO

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