Standards and Technology for Bringing Mathematics into the Information Age

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Standards and Technology for Bringing Mathematics
into the Information Age

• Robby Robson
• Eduworks Corporation
• and
• Department of Computer Science Oregon State
  University

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Introduction
It would appear that we have reached the limits
of what it is possible to achieve with computer
technology, although one should be careful with
such statements, as they tend to sound pretty
silly in 5 years. - John Von Neumann (ca.
1949)
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What Has Changed?

• The cost of transporting information is now low
• The ability to store and retrieve data is now
  high
• Barriers that have been exposed as artifacts
• Symbols must be created with a type ball
• People must meet in order to communicate
• You must go to a building to get a book
• You must meet with a mentor to get advice
• Your knowledge is all in your head

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What to Expect

• Division of labor
• Changes in production practices
• Amusing anachronisms
• Surprises that shouldnt have surprised us
• Poor predictions

But, we digress . . .
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Concrete Projects Goals

• Make all of mathematics available to
  researchers
• Create digital libraries of learning objects
• Make available to a global community
• What you want and what you need
• When you want it and when you need it
• How you want it and how you need it
• Where you want it and where you need it

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Good Questions to Ask

• How does our work relate to that of others?
• What is already available to help us meet our
  demands?
• How will we pay for all of this? (Not the topic
  today)

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Pictures to be Painted

• Enterprise Computing
• Content Management
• Learning Management
• Knowledge Management
• Enterprise Scale Architecture
• Standards

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Enterprise Computing

• Automation of Tasks Processes
• Financials
• Human Resources
• Enterprise Resource Planning
• Customer Relationships
• E-business
• Content, Learning Knowledge Management
• Co-management and Conflation of data about
  People, Places, and Things
• Deriving value from the ability to see and manage
  data and information

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Academic Enterprise Environment
Campus Portal
Sales Services
Alumni Relationships
Learning Management
Registrar Catalog
Library Information
Fundraising
Course Development
Physical Plant
Student Administration
Human Resources
Financial Information
University Press
Classroom Management
Institutional Data
Budget Process
File Servers, Databases, etc.
Internet, Intranet Internet II
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Content Management
Creation Acquisition

• Authoring
• Transformation
• Aggregation
• Metadata
• Roles Workflow
• Library Services
• Internationalization Localization

• Search Discovery
• Personalization
• Rights Roles Management,
• Caching Replication
• Page generation, formatting
• Sales Services

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E-Learning
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E-Learning E-Research
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E-Research?
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Factors of Scale

• Number of students at largest US higher education
  institutions About 100,000
• Open University in the UK 185,000
• UFI 280,000 with goal of 1,000,000. Becta (post
  16 non-HE in UK) goal of 6,000,000
• Global Enterprises on the scale of hundreds of
  thousands. (USPS has 750,000 employees, Wal-Mart
  has 1.2 million)
• China has projects targeting 40 million students

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The E-learning Content Lifecycle
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Learning Technology Standards

• Learning Object Metadata
• Packaging
• Run Time Communication
• Learner Information
• Enrollment Management
• Competencies
• Question Test Interoperability
• Schools Interoperability Framework

• Sequencing
• Higher level design
• DREL
• Quality
• Accessibility
• Architecture
• OKI

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EXAMPLE 1 SCORM RUNTIME COMMUNICATION
LMS
API Object supplied by LMS instantiates functions
Frame climbing code finds API Object
LMSInitialize() LMSGetValue() LMSSetValue() LMSFin
alize() error handling
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Example 2 Content Packaging
Package Interchange File (Zip Archive)
Manifest File
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Knowledge Management

• Explicit knowledge
• Documents, Educational Materials, Presentations,
  Journals, etc.
• Tacit knowledge
• Perspectives, Experiences, Practices
• KM seeks to capture, combine, distill, catalog,
  and publish both explicit and tacit knowledge
• TOOLS CMS, LMS, Knowledge Mapping, Recommender
  Systems, Portals, Taxonomies, Search Engines, etc.

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Enterprise Scale Architecture

• Scalable and Durable
• Modular
• Well understood and standardized interfaces
• Redundant
• Distributed
• Flexible and Extensible
• Modular
• Well understood and standardized interfaces
• Well understood and clearly separated layers
• Distributed

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OKI Example

• OKI Open Knowledge Initiative
• Architecture APIs Reference Models
• Design Partners
• Cambridge University
• Dartmouth College
• MIT
• North Carolina State University
• Stanford University
• University of Michigan
• University of Pennsylvania
• University of Wisconsin
• Coordinating with standards organizations

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Example OKI Service Framework
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Multiple OKI Servers Serving Different Content
But Sharing Some Enterprise Services
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Standards

• Interoperability
• Semantic interoperability
• Syntactic/System interoperability
• Human-Computer Interoperability
• Standards go hand-in-hand with architecture
• International in scope and nature

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Standards Development Process
RD Concepts
Spec Consortia
Programs, Test beds, Markets
Standards Bodies
ApprovedStandards
User Needs
Technical Trends
New products, Pilot Programs, Test beds
Consensus,Consolidation,Conformance
Specifications, Best Practice
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Comments On Relevant Consensus Standards Efforts

• MathML
• Metadata
• Digital Rights

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What Can Mathematics Projects Use?

• Commercial Enterprise Software
• Knowledge and expertise from other areas
• Standards for metadata, interoperability, content
  management, service layers, personal information,
  etc.

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What Can Mathematics Contribute?

• Everything associated with a community of
  practice
• Requirements
• Taxonomies
• Metadata application profiles
• MathML
• Appropriate business models
• Specialized software
• Knowledge Gained from Implementations and lessons
  learned

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Observations Recommendations

• Think Research Management System
• Start with an architecture (and stick to it)
• Dont separate research and education
• Think in terms of services, not goods
• Keep the end-user in mind, always
• Metadata, metadata, metadata
• Think in terms of re-usable objects
• Recognize that roles will change
• Spend your time on what you can influence
• If youre lost, ask for directions

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DISCUSSION

• rrobson_at_eduworks.com