Transcript Information modeling, Information architectures theory and practice (Internet, Web, Grid, Cloud) Peter Fox Xinformatics – ITEC/CSCI/ERTH-4400/6400 Week 5, February 25, 2014

Information modeling,
Information architectures
theory and practice (Internet,
Web, Grid, Cloud)
Peter Fox
Xinformatics – ITEC/CSCI/ERTH-4400/6400
Week 5, February 25, 2014
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Contents
• Review of last class/ reading
• Class exercise in Information
Modeling (intro slides first)
• Information architectures theory
and practice (Reference,
Internet, Web, Grid, Cloud) and
class project definitions
• Next classes
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Information Models
• Conceptual models, sometimes called
domain models, are typically used to
explore domain concepts and often
created
– as part of initial requirements envisioning
efforts as they are used to explore the highlevel static business or science or medicine
structures and concepts
• Followed by logical and physical models
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Logical models
• A logical entity-relationship model is provable
in the mathematics of data science. Given the
current predominance of relational
databases, logical models generally conform
to relational theory.
• Thus a logical model contains only fully
normalized entities. Some of these may
represent logical domains rather than
potential physical tables.
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Physical models
• A physical model is a single logical model
instantiated in a specific information system
(e.g., relational database, RDF/XML
document, etc.) in a specific installation.
• The physical model specifies implementation
details which may be features of a particular
product or version, as well as configuration
choices for that instance.
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Physical models
• E.g. for a database, these could include index
construction, alternate key declarations,
modes of referential integrity (declarative or
procedural), constraints, views, and physical
storage objects such as tablespaces.
• E.g. for RDF/XML, this would include
namespaces, declarative relations, etc.
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Object oriented design
• Object-oriented modeling is a formal way of
representing something in the real world
(draws from traditional set theory and
classification theory). Some basics to keep in
mind in object-oriented modeling are that:
– Instances are things.
– Properties are attributes.
– Relationships are pairs of attributes.
– Classes are types of things.
– Subclasses are subtypes of things.
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Object model
• Class: a means of grouping all the objects which
share the same set of attributes and methods.
• An object must belong to only one class as an
instance of that class (instance-of relationship).
• A class is similar to an abstract data type.
• Class hierarchy and inheritance: derive a new class
(subclass) from an existing class (superclass)
– subclass inherits all the attributes and methods of the
existing class and may have additional attributes and
methods
– single inheritance (class hierarchy) vs. multiple
inheritance (class lattice).
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Core object models consist of:
• object and object identifier: Any real world entity is
uniformly modeled as an object (associated with a
unique id: used to pinpoint an object to retrieve).
• attributes and methods: every object has a state
(the set of values for the attributes of the object) and
a behavior (the set of methods - program code which operate on the state of the object).
• the state and behavior encapsulated in an object
are accessed or invoked from outside the object.
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Information Modeling
• Conceptual
• Logical
• Physical
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For example for relational DBs
Feature
Conceptual Logical Physical
Entity Names
✓
✓
Entity Relationships ✓
✓
Attributes
✓
Primary Keys
✓
✓
Foreign Keys
✓
✓
Table Names
✓
Column Names
✓
Column Data Types
✓
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Steps in modeling
•
•
•
•
•
•
•
Identify objects (entity) and their types
Identify attributes
Apply naming conventions
Identify relationships
Apply model patterns (if known)
Assign relationships
Normalize to reduce redundancy (this is
called refactoring in software engineering)
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Exercise!
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Not just an isolated set of models
• Most important for handling errors,
evolution, extension, restriction, …
where to do that:
–To the physical model? NO
–To the logical model? MAYBE
–To the conceptual model? YES IF
POSSIBLE
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Not just an isolated set of models
• To relate to and/ or integrate with
other information models:
–General rule – integrate at the highest
level you can (i.e. more abstract)
–Remember the cognitive aspects!
Less detail is easier to understand
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(Information) Architecture
• Definition:
– “is the art of expressing a model or concept of
information used in activities that require explicit
details of complex systems” (wikipedia)
– “… I mean architect as in the creating of
systemic, structural, and orderly principles to
make something work - the thoughtful making of
either artifact, or idea, or policy that informs
because it is clear.” Wuman
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More detail to connect us
• “The term information architecture describes
a specialized skill set which relates to the
interpretation of information and expression
of distinctions between signs and systems of
signs.” (wikipedia, emphasis added)
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Meaning not deep thought
• “Information architecture is the categorization
of information into a coherent structure,
preferably one that the most people can
understand quickly, if not inherently.
• It's usually hierarchical, but can have other
structures, such as concentric or even
chaotic.” (wikipedia)
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Familiar example – learning portal
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And relation to design?
• “In the context of information systems design, information
architecture refers to the analysis and design of the data
stored by information systems, concentrating on entities, their
attributes, and their interrelationships.
• It refers to the modeling of data for an individual database and
to the corporate data models an enterprise uses to coordinate
the definition of data in several (perhaps scores or hundreds)
of distinct databases.
• The "canonical data model" is applied to integration
technologies as a definition for specific data passed between
the systems of an enterprise.
• At a higher level of abstraction it may also refer to the
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definition of data stores.” (wikipedia)
Art or skill?
• Form follows function (Sullivan) – who put
this into effect in building structures, homes?
• Based on two previous foundations classes,
information theory and signs, it should be
clear that the answer is ‘yes’ (both).
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Design theory
• Elements
– Form
– Value
– Texture
– Lines
– Shapes
– Direction
– Size
– Color
• Relate these to previous class, signs and
relations between them
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Examples
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Remember this one?
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Principles of design
• Balance
– Balance in design is similar to balance in physics
• Gradation
– of size and direction produce linear perspective.
– of color from warm to cool and tone from dark to
light produce aerial perspective.
– can add interest and movement to a shape.
– from dark to light will cause the eye to move
along a shape.
• Repetition
– with variation is interesting, without variation
repetition can become monotonous.
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Balance, gradation, repetition
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Principles of design
• Contrast
– is the juxtaposition of opposing elements e.g. opposite
colors on the color wheel - red / green, blue / orange etc.
– in tone or value - light / dark.
– in direction - horizontal / vertical.
– The major contrast in a painting should be located at the
center of interest.
– Too much contrast scattered throughout a painting can
destroy unity and make a work difficult to look at.
– Unless a feeling of chaos and confusion are what you are
seeking, it is a good idea to carefully consider where to
place your areas of maximum contrast.
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Contrast
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Principles of design
• Harmony
– in painting is the visually satisfying effect of
combining similar, related elements. e.g. adjacent
colors on the color wheel, similar shapes etc.
• Dominance
– gives a scene interest, counteracting confusion
and monotony
– can be applied to one or more of the elements to
give emphasis
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Harmony, Dominance
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Principles of design
• Unity
– Relating the design elements to the idea being
expressed in a rendering reinforces the principal
of unity.
– E.g. a scene with an active aggressive subject
would work better with a dominant oblique
direction, course, rough texture, angular lines etc.
whereas a quiet passive subject would benefit
from horizontal lines, soft texture and less tonal
contrast.
– in a painting also refers to the visual linking of
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various elements of the work.
Unity
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Color
• Primary Colors - Red, Yellow, Blue - these colors
should not be intermingled, they must be bought
together in some other form
• Secondary Color - Orange, Violet, Green, these
colors are created by mixing two primaries.
• Intermediate Colors - Red Orange, Yellow Green,
Blue Violet, etc.; mixing a primary with a secondary
creates these colors.
• Complementary Colors - are colors that are
opposite each other on the color wheel. When
placed next to each other they look bright and when
mixed together they neutralize each other.
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Wheels
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Color applied
• Harmony is when an artist uses certain
combinations of colors that create different looks or
feelings
• Analogous Colors are colors that are next to each
other on the color wheel for example red, red
orange, and orange are analogous colors.
• Triadic Harmony is where three equally spaced
colors on the color wheel are used for example,
Yellow, Red, Blue is a triadic harmony color
scheme.
• Monochromatic is where one color is used but in
different values and intensity.
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Color applied
• Warm colors are on one
side of the color wheel and
they give the felling of
warmth for example red,
orange and yellow are the
color of fire and feel warm.
• Cool colors are on the other
side of the color wheel and
they give the feeling of
coolness for example blue,
violet, are the color of
water, and green are the
color of cool grass.
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Reference architectures
• “provides a proven template solution for an
architecture for a particular domain. It also
provides a common vocabulary with which to
discuss implementations, often with the aim
to stress commonality.
• A reference architecture often consists of a
list of functions and some indication of their
interfaces (or APIs) and interactions with
each other and with functions located outside
of the scope of the reference architecture.”
(wikipedia)
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U.S. Federal Enterprise Arch
• E.g. The Federal Enterprise Architecture
Reference Model Ontology (FEA-RMO) is a
domain specific ontology of the Federal
Enterprise Architecture reference models.
• FEA-RMO directly translates the
Performance, Business, Service Component,
and Technical reference models into their
executable representation in OWL-DL.
– http://web-services.gov/fea-rmo.html
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FEA Domain model
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Figure 6-1 DRM Abstract Model
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Data Description
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Data Sharing
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Data Context
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IA=IM?
• Did we just examine an enterprise reference
architecture that was actually a domain
(conceptual) information model along with its
logical model?
• How about THAT!
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MVC
• Model
• View
• Controller
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Internet/ Intranet
• Communications versus information
architecture?
• http://www.slideshare.net/postwait/scalableinternet-architecture
• See the reading for this week, the role of the
Internet Engineering Task Force (IETF) and
architecture
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WWW
• Design for the web (Tim Berners Lee)
• “Principles such as simplicity and modularity
are the stuff of software engineering;
decentralization and tolerance are the life and
breath of Internet. To these we might add the
principles of least powerful language, and the
test of independent invention when
considering evolvable Web technology.”
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Original design issues
• See http://www.w3.org/DesignIssues/Overview.html
• Here are the criteria and features to be considered:
– Intended uses of the system.
– Availability on which platforms?
– Navigational techniques and tools: browsing, indexing,
maps, resource discovery, etc
– Keeping track of previous versions of nodes and their
relationships
– Multiuser access: protection, editing and locking,
annotation.
– Notifying readers of new material available
– The topology of the web of links
– The types of links which can express different
relationships between nodes
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Original design issues
• These are the three important issues which
require agreement between systems which
can work together
– Naming and Addressing of documents
– Protocols
– The format in which node content is stored and
transferred
• Implementation and optimization
– Caching , smart browsers, knowbots etc., format
conversion, gateways
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Web architectural elements
URI
HTML
HTTP
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Common Gateway Interface
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Client – Server and multi tier
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Web page/site architecture
• Hierarchies, we call them levels:
– Top level (the main page)
– Second (and further) level (via navigation)
– Balancing the levels
• Remember your use case, the actors, the
resources, the information model, information
entropy, the signs, ...
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CEDAR 1.0 circa 1990
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CEDAR 2.0 circa 1994
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2000
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Multi-tiered Interoperability
People
Agency Policy
Makers
System Scientists
Politicians
Decision-level semantic mediation: high-level vocabularies that facilitate policy-level
decision-making
Integrated
Applications
Inter-disciplinary
Data Visualization
Apps
Semantic
interoperability
Integration
Frameworks &
Methodologies
Eco & other system
Assessment Apps
Application-level semantic mediation: mid-level vocabularies that facilitate the interoperability of system models and data products
Sof t ware,
Tools&Apps
Disciplinespecific
model(s)
Semantic
interoperability
Dataproduct
Generator
Semantic query,
hypothsis and
inference
Information/
Science Apps
Query,
access and
use of data
Data-level Semantic mediation: lower-level vocabularies applied to each data source
for a specific science domain of interest
Data
Repositories
Federal
Repository
Commercial
Database
Researcher
Private
Database
Other Data
Sources
Metadata,
schema,
data
... ... ...
Grid
• “One of the main strategies of Grid
computing is to use middleware to divide and
apportion pieces of a program among several
computers, sometimes up to many
thousands.
• Grid computing involves computation in a
distributed fashion, which may also involve
the aggregation of large-scale cluster
computing based systems.” (wikipedia)
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“What is the Grid?”
• A Three Point Checklist, Ian Foster lists these
primary attributes:
– Computing resources are not administered
centrally
– Open standards are used.
– Nontrivial quality of service is achieved.
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Open Grid Services Architecture
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Statefull versus stateless
• A key distinction between Grids and Web
environments is state, i.e. the knowledge of
‘who’ knows and remembers ‘what’
• Increasingly there is a need for maintaining
some form of state, i.e. reducing information
entropy in web and internet-based
architectures
• Thus, enter the need for ‘state for a defined
purpose’…
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Cloud
• "a computing capability that provides an
abstraction between the computing resource
and its underlying technical architecture (e.g.,
servers, storage, networks), enabling
convenient, on-demand network access to a
shared pool of configurable computing
resources that can be rapidly provisioned and
released with minimal management effort or
service provider interaction.” (wikipedia)
• Logical extension of virtualization
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• Often tied to the cost model
Primary Benefits of Cloud Computing
• To deliver a future state architecture that captures the promise of Cloud
Computing, architects need to understand the primary benefits of Cloud
computing
• Decoupling and separation of the business service from the infrastructure
needed to run it (virtualization)
• Flexibility to choose multiple vendors that provide reliable and scalable
business services, development environments, and infrastructure that
can be leveraged out of the box and billed on a metered basis—with no
long term contracts
• Elastic nature of the infrastructure to rapidly allocate and de-allocate
massively scalable resources to business services on a demand basis
• Cost allocation flexibility for customers wanting to move CapEx into
OpEx
• Reduced costs due to operational efficiencies, and more rapid
deployment of new business services
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Software as a service (SaaS)
• A SaaS provider typically hosts and manages
a given application in their own data center
and makes it available to multiple tenants and
users over the Web.
• Some SaaS providers run on another cloud
provider’s PaaS or IaaS service offerings.
• Oracle CRM On Demand, Salesforce.com,
and Netsuite are some of the well known
SaaS
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Infrastructure as a service (IaaS)
• is the delivery of hardware (server, storage and
network), and associated software (operating
systems virtualization technology, file system), as a
service. It is an evolution of traditional hosting that
does not require any long term commitment and
allows users to provision resources on demand.
• Unlike PaaS services, the IaaS provider does very
little management other than keep the data center
operational and users must deploy and manage the
software services themselves--just the way they
would in their own data center. Amazon Web
Services Elastic Compute Cloud (EC2) and Secure
Storage Service (S3) are examples of IaaS
offerings.
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Platform as a service (Paas)
• is an application development and deployment platform
delivered as a service to developers over the Web.
• facilitates development and deployment of applications without
the cost and complexity of buying and managing the underlying
infrastructure, providing all of the facilities required to support
the complete life cycle of building and delivering web
applications and services entirely available from the Internet.
• consists of infrastructure software, and typically includes a
database, middleware and development tools.
• A virtualized and clustered grid computing architecture is often
the basis for this infrastructure software.
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Platform as a service (Paas)
• Some PaaS offerings have a specific programming language
or API.
• For example, Google AppEngine is a PaaS offering where
developers write in Python or Java.
• EngineYard is Ruby on Rails.
• Sometimes PaaS providers have proprietary languages like
force.com from Salesforce.com and Coghead, now owned
by SAP
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Simple cloud architectures
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More complex clouds
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More details…
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Cloud domain decompostion
By functional domain
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Towards a reference architecture?
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Back to IMs as IAs
• What would an information model
architecture of cloud (X-as-a-service)?
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Discussion
• About architecture in general?
• Design?
• Internet, web, grid, cloud?
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What is next
• Reading for this week
– Architectures
– Design
– Color
• Week 6 – Information Integration, Life-cycle
and Visualization and your first view of the
group projects
• Spring break
• Then … presentations
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Data-Information-Knowledge
Ecosystem
Experience
Data
Creation
Gathering
Information
Presentation
Organization
Knowledge
Integration
Conversation
Context
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