Workshop: Geert Van Grootel - Implementation of Data Governance in a Multi-institutional Context

Integrating aspects of interoperability, policy
and governance
FRIS: a research information
infrastructure in Flanders
CASRAI Canada ReConnect14
November 19-21 2014 Ottawa

CASRAI ReConnect14, 19- 21 November 2014, Ottawa, Canada
Geert Van Grootel
Economy, Science & Innovation dept.
Flemish government
geert.vangrootel@ewi.vlaanderen.be

FRIS: Flanders Research Information Space
3
researchers
Research organisation
Investment
opportunities
projects
publications
patents
equipment
products
research data
facilitiesgovernment
funders
researchers
editors
libraries
data centres
research institutions
industry

Better Research Information:
correct, actual , complete
Open FRIS data for services and
application development
Maximum reuse of data
Maximum reuse of
components
Connect data silo’s
Reduce system costs
More information services
Policy monitoring:
efficient & effective
Increase strategic
intelligence
Flemish government Open
Data policy
FRIS Needs & drivers

The Information Providers Landscape
5
Universities
Research Institutes
Funding Agencies
Others
Strategic Research
Centers
University Colleges

The Challenge
 Information integration from sources with large difference in:
 Scope:
 research
 education
 data centre's
 services
 Scale:
 8 to >6.600 researchers
 Internal integration maturity
 Application silo’s
 HR
 Finance
 Asset management
 The library silo
 ERP
 CRIS System
 …

Goals
Implementation of FRIS information
principles and policy
 Information quality
 Completeness
 Accurate
 Timeliness
 Information is integrated
 360° view on all information dimensions

8
Architecture
Content
Changemgnt
Governance
ServicesUse
Populate
Build
Accelerate Innovation
E-government
Monitoring
Communication
Agreements
1. Information standards
2. Classifications, Reference data
3. ID’s
How to realise FRIS

A core element of the Architecture: FRIS Shared Services
Person Organisation
Project
Classifications
Research
Contribution
Reference
Data
Business
Rules
Data
Validation
Storage
Ingestion /
Consumption
Administration
User interface
Portal
User Interface
Institution
Services
Institution
Services

A core element of the Architecture: FRIS Shared Services

Goals
 Incremental information exchange
 Continuous flow of information driven by agreed state
  Consequence:
 reporting is realised on integrated FRIS data
 KPI’s continuously monitored
 Process alignment
 Information collection efficiency
 “I shall ask this only once” principle
 Master Data integration
 Reuse and sharing of master data
 Available on the FRIS shared services layer
 Reference data
 Agreed and managed semantics
 Available on the FRIS shared services layer

Goals
Semantics
 Shared and managed vocabularies for
 Terms
 Business objects
 Business rules
 KPI
 Reports
 Traceability from policy to data and back
 Policy Business rule  Validation
rule
 Validation rule compliancy 
Business rule Policy

FRIS requirements for semantic management
• What
• High level conceptual models
• Provider information models
• Business Rules
• KPI’s
• Reference data:
• Classifications, allowed value sets,
• Codes and code sets
• Data Validation Rules
• Exchange formats and reporting standards
• CERIF
• CASRAI

• How
• Collaborative management of information
models
• Collaborative management of classification
schemes and code sets
• Machine readable classification schemes and
codes sets
• Machine readable information models including
business rules in anticipation of automated
validation of exchanged information.

Who
 EWI
 Policy developers
 Monitoring group
 Enterprise Architect and team
 CIO
 FRIS Information architect
 FRIS services functional analyst
 IT developer
 Operations:
 Data validation
 Report design
 KPI implementation
 Information providers
 Roles very comparable to EWI
 Subject matter experts

FRIS Information Modelling Stack
Principles, Guidelines, Governance structures
High Level Conceptual models
Governance models
Meta
model
Information models
Data base schemes
Code SetsClassification Schemes
Information templates
Business Rules
Governance Implementation
Information
Modeling

Tools
Methodology
Organisation
DATA GOVERNANCE
Proactively managing your data, to
support your business

“The Information “modelling” stack problem”
Technology
Application
Business
Information Behavior Structure
ProcessesInformation
Data
Organisation
Products &
Services
Applications
Technical Infrastructure
Business
Functions

Enterprise Information Architecture
20
BusinessApplicationTechnology

Terminology,
Profiles and
Objects
Terminology,
Profiles and
Objects
Model(s)Model(s)
Data Formats
and Exchange
Protocols
Data Formats
and Exchange
Protocols
Software Implementation and Developers
Modeling and
Exchange Experts
Business: daily users to
subject matter experts

Can we have a business communication with this?
The CERIF Model

Data modelling vs Concept Modelling
Person Research
Contribution
Pers-
ResCont
is involved with
of
Pers_ResCont_code
• auth
• edit
• Illus
• publ

Terminology,
Profiles and
Objects
Terminology,
Profiles and
Objects
Model(s)Model(s)
Data Formats
and Exchange
Protocols
Data Formats
and Exchange
Protocols
Software Implementation and Developers
Modeling and
Exchange Experts
‘Essentially, all models are
wrong, but some are useful’
George E. P. Box

25
Managing Complexity

Business Vocabularies & Business Rules
• Can Business vocabularies be realised without structure?
• Even without a formal modelling framework we need structure
• Everything is a concept
• All concepts are equal but some are more equal than other
• Frame discussions and communication
• Appoint the responsible actor
• ….

The structured Business Vocabulary
 Reasons for having structured vocabularies
Can express what we can know about the business
 In a language understood by the business
 Provides meaning (semantics) to all concepts of the business
Provides coherence for
 Business Rules
 Requirements
Openess
 Sharing across the organisation
Can be supported by tooling
 Management
 Workflows
 Storage
 Starting point for vertical integration

The components of structured Business vocabulary
 Business Term
 A Business Term is the name of a Business Concept. It is the
representation of a Business Concept by means of a word or
‘ordered set’ of words. A Business Term is used to refer to a
Business Concept and its meaning
28

 Business Concept
 A Business Concept is whatever can be thought of by the
business. Normally each Business Concept has an
unambiguous meaning expressed by an unambiguous
definition.
 A Business Concept can be taxonomically classified in
various sub classifications e.g. Business Object,
Classification, Business Rule, Code.
 A Business Concept is represented
by a Business Term
29

 Business Object
 A Business Object is a Business Concept, concrete or abstract,
that has the capability to influence behavior of a Business
System. Typical examples are Person, Organization, Project,
Location, Instruction, Account, etc.
 A Business Object is represented by
a Business Term
30

Classification
A Classification is a Business Concept that organizes and
manages business information by defining (hierarchical)
structures that provide classification categories that apply to one
or more Business Concepts and groups of Business Concepts
that apply to multiple Business Concepts
A Classification is represented by a Business Term
31

Code
A (technical) Business Concept that is an identifier of a Business
Concept.
A Code is used to 'identify' or to 'refer to' a Business Concept.
A Code is represented by a Business Term
 e.g. BE identifies the concept “Belgium”
32

Business Rule
 A formula that defines or constrains some aspect of business.
• Intended to assert business structure or to control or influence the
behavior of the business.
• Describe the operations, definitions and constraints that apply to
an organization.
• Can apply to people, processes, corporate behavior and
computing systems in an organization, and are put in place to
help the organization achieve its goals.
• May be informal or even unwritten, writing the rules down clearly
and making sure that they don't conflict is a valuable activity.
• When carefully managed, rules can be used to help the
organization to better achieve goals, remove obstacles to market
growth, reduce costly mistakes, improve communication, comply
with legal requirements, and increase customer loyalty.
 A Business Rule is represented by a Business Term
33

Information Model Pattern
 Information Model Pattern
 The Information Model Pattern defines the generic structure of the type of
information you may be interested in when describing a concept.
 This is the high level conceptual data architecture which represents
the fundamental business objects and the relations between each
other and the environment and the principles guiding its design and
evolution (TOGAF 9.1 ISO 42010, IEEE 1471).
34

FRIS Meta model
Project
Person
Organisation
Location
Electronic
Location
Physical
Location
Book
Book
Contribution
Journal
Contribution
Journal
Research
Contribution

The FRIS Business Object structure
FRIS Business
Object
Identifier
Issuing
Authority
Provenance
Property
Classification
Taxonomical
Functional
Relationship
Life Cycle

A concrete FRIS Business Object: Person

The structured vocabulary implemented

Business Rules
 Business Rules implementation is fairly new in FRIS
 Examples of structural business rule constraining the components
of a FRIS Business objects
 Mandatory properties
The following properties of Book Contribution In Book are
mandatory: Title, Publication Date, Book Title, ISBN, Publisher
Name, Start Page, End Page andPublication Date.
 Author Order Rule
The author order is known and represented by a
natural number indicating the position of an author in the author list.
 Published Book Identifier Rule
A Book classified as Published Book has at least one ISBN identifier
 Identifier Composition Rule
An Identifier always has a known Issuing Authority and Provenance.

Business Rules
 The Business Rules are expressed in natural language
 Is under de jurisdiction of the Business
Creation
Revision
Deprecation
 Business Rules tend to remove degrees of freedom
 Type of rules
Definitional Rule
 An Identifier always has a known Issuing Authority and Provenance.
Behaviour Rules
 A Journal Article must be deposited in the institutional archive no
later than 3 moths after the publication date

Business Rules and Business vocabulary
Business Rules are maintained as integral part of the
Business vocabulary environment.
As much as possible with formal relationships to all
relevant terms
Coherence
Completeness
Traceability

Business Rule Traceability
 The following properties of Book Contribution are
mandatory: Title, Start Page, End Page.

Business Rule Traceability

Terminology,
Profiles and
Objects
Terminology,
Profiles and
Objects
Vocabularies
Business Objects
Classifications
Business Rules
Vocabularies
Business Objects
Classifications
Business Rules

Governance Organisation

Governance Implemenation

Governance implementation
“Workflow”

TOOLS
The Law of the Instrument:
“ If you only have a hammer, everything looks like a nail”

Tool Scope
One tool for all,
all for one tool

Usage

Data Governance Implementation Strategy

FRIS Data Governance Center Operating Model fragment

FRIS Data Goverance Operating model fragment

What has been realised so far
FRIS Business Objects
 Identifiers
 Properties
 Classification
 Taxonomies
 Functional Classifications
 Relationships
 Life Cycle

What has been realised so far
Codes, Codes sets and management
Business Rules
 Policy
 Rule types
 Versioning
 Implementation roadmap dependant
 Context dependant

Roadmap 2015
 Implement complete governance
structure in Data Governance Center
 Roles and responsibilities
 Workflows
 Design
 Implementation
 Implement Data Governance Center
Validation Rules

Roadmap 2015
 Integrate the Data Governance Center API with
FRIS services layer
 Reference Data
 Classifications
 Allowed values
 Rule based data validation
 Integration of Business Rules – Data Rules stack
in Data Governance Center with the DataFlux
validator services
 KPI development.

Why do we want manage semantics?

Alignment ... Do we speak the same language!
We will create an
Open Research
Information Space
for all stakeholders
So we need
an open
standard
and a triple
store
open
office
concept ?
So we need
“openminded”
personel

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