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THE CONTRACTOR IS ACTING UNDER A FRAMEWORK CONTRACT CONCLUDED WITH THE COMMISSION
EARF: Capability Model and Building Blocks
Monica Scannapieco
ESTP Training Course “Enterprise Architecture and the different EA layers, application to the ESS context – Advanced course”
Rome, 11 – 14 October 2016
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Business Capability
• “An ability that an organization, person, or system possesses. Capabilities are typically expressed in general and high-level terms and typically require a combination of organization, people, processes, and technology to achieve.”
TOGAF
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Business Capability
• In a statistical organization:
• Methods
• Processes
• Standards
• Metadata
• IT Systems
• People skills
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Scope of the Business Capability Model
• Describes what the ESS member do by:
• Setting a common language for the business
• Enabling service identification, specification and design
• Supporting capabilties planning, in terms of selection and prioritization
• Supporting development and management of business capabilities
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Business Capability Model: the structure
• 3 abstraction levels: 0, 1 and 2
• Level 0:
• Strategy management
• Statistical production management
• Corporate support management
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Relationships with previously introduced standards
• Main relationship: GSBPM, GAMSO
• Mapping of the Business Capability Model to GAMSO
• Strategy management Strategy & Leadership
• Statistical production managementGSBPM/GAMSO Production
• Corporate support management-> Corporate Support
• In addition GAMSO «Capability Management»
• Detailed mapping available
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The ability to maintain and
consolidate strategic relations with
external stakeholders
The ability to: • set priorities, focus business
capabilities and resources • ensure that employees and other
stakeholders are working toward common goals
• establish agreement around intended outcomes/results
• assess and adjust the organization's direction in response to a changing environment.
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The ability to contribute to
policy development
The ability to: • manage a portfolio of projects
(PPM) • manage processes, methods, and
technologies used by project manager
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The ability of planning and
monitoring the performance of
processes
The ability to develop, maintain and end legal frameworks and ensure
compliance with the legal frameworks
The ability to maintain the necessary
human resources and optimize the
value of human resources
through hiring and
development activities
The ability to manage tasks and decisions
surrounding the ingestion, annotation, cataloguing, storage, retrieval and distribution of digital
assets
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The ability to manage
information through people
The ability to effectively purchase goods and
services from external suppliers for the
operation of statistical authorities
The ability to monitor and control that the data and metadata is
managed securely
throughout its lifecycle
The ability to plan, direct, monitor, organize
and control the monetary resources of the statistical authority
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The ability to explore and
innovate new statistics based on
existing and new data
source
The ability to design the statistical outputs, concepts, methods, collection
instruments and operational processes
required to produce statistics
The ability to gather data for
official statistics
The ability to manage
custodianship and ownership of data
and metadata
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The ability to check, clean,
and transform the collected
data and produce,
examine and make ready for dissemination
The ability to examine and make
sense of data before
dissemination
The ability to manage the
release of the statistical
products to users
The ability to perform quality assessments and put in place control mechanisms over the statistical value chain
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The ability to explore the
potential value of new data sources for improving existing
statistics or innovating to obtain new statistics
The ability to innovate i.e. create new statistical
products based on existing data sources and the exploration of
new data sources
The ability to participate in and influence
legislative work at the basis of OS production
The ability to effectively
develop methods and
tools to support the exploration and innovation
of new statistical products
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The ability to collect, assess and translate
user needs into statistical outputs
The ability to design
statistical output so that it
is valid and useful for the user based on
sound statistical
methodologies.
The ability to design statistical
production processes and
workflows in an effective and
flexible manner
The ability to develop,
maintain and enhance
methods to be delivered by
statistical processing
services supporting statistical production
The ability to design and
implement the necessary systems to deliver and
combine statistical processing
services and related rules for the production
of statistics
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The ability to conclude provision
agreements with
information providers to provide data according to requirements (timeliness,
confidentiality, ...).
The ability to manage the process of requesting,
receiving and testing data
from administrative sources as well as other data
sources (internet data, scanner data
…).
The ability to set up and
manage surveys through to their finalization and
transfer to processing and
analysis
The ability to enrich the
received data with metadata to support the
further processing and analysis as well
as the dissemination
of the statistical output
The ability to set up, maintain
and provide "register" services
supporting collection and integration of
data.
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The ability to manage data
(including personal micro data) efficiently
and securely through the
entire life cycle from data
collection to dissemination.
The ability to manage
metadata throughout the
production cycle
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The ability to efficiently
integrate data from different
sources, classify and code data,
review and validate the
data as well as edit the data and perform
imputations to improve the
information set quality.
The ability to derive new variables & units for the
statistical output
according to shared
methodologies.
The ability to calculate the
necessary weights and
aggregates and prepare output
data for analysis and
dissemination using shared
methodologies and processes
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The ability to manage the release of statistical
output as well as
accompanying content
according to release
schedules so that users have predictable and equal access to
data
The ability to make statistical output data and
metadata flexibly
available for manual and machine-to-
machine access through multiple channels
The ability to promote the
statistical output for
potential users and notify the
press and other stakeholders
about statistical output
The ability to author and manage the
distribution of content related to the statistical
output. This includes press
releases, interpretations,
and reports
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The ability to set up, execute,
monitor, and evaluate control mechanisms in the production
process to ensure a high
quality of statistical
output
The ability to assess the quality of statistical
processes as well as output according to
shared standards and
practices
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The ability to validate outputs
as well as interpret &
explain outputs and finalize output for
dissemination using shared
methodologies and processes
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Use Cases: ESS governance
• Which business capabilities are in scope for the ESS collaboration? Which ones are left to the individual members?
• Support the longer term development and management of business capabilities
• Identify very unique business capabilities that could be shared or leveraged upon by other ESS members rather than developed redundantly
• Support the scoping of centers of excellence
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Use Cases: ESS Enterprise Architects
• Use the business capabilities model to support statistical service identification, specification and design
• Use business capabilities to encourage stakeholders to think about the strategic business requirements first
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Use Cases: Usage by ESS Business Leaders
• Use the business capability model to take discussions with IT a step back and focus on what the key elements of the business are
• Identify the business’ key capabilities
• Break down silos between business units/organizations by identifying common business capabilities and common solutions
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Use Cases: Usage by ESS project leaders
• Axe projects around business capabilities
• Already in the project initiation request, always specify which capability/ies will be improved and how
• Align project outputs with business capabilities
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Use Cases: Usage by IT leaders
• Gain stability in technology design
• Use the business capability model as a communication tool to represent a consistent view of what the ESS and its members do
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Building Blocks
• Building Blocks (BBs): represent (potentially re-usable) components of (IT) capability that can be combined with other building blocks to support ESS business solutions
• TOGAF BB’s characteristics:
• package of functionalities defined to meet the business needs across an organization;
• has a type, such as actor, application, or data entity;
• has a defined boundary;
• may interoperate with other, inter-dependent, BBs.
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BBs positioned
wrt GSBPM
processes
Latest version: Quality
assessment and Data supplier registry
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Primary Data Storage
• Data storage where the primary data from production are stored in a design that supports large amounts of data and the flexible addition of new data sources
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Dissemination Data Storage
• Data storage where the data and statistics for dissemination and publication are stored
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Metadata management
• System that manages the entire life cycle of reference, structural, and process metadata. This will form a key building block and prerequisite for the value of sharing the statistical services and dissemination
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Collaboration
• This is an ESS platform that allows a collaborative way of working across the various phases of the statistical processes
• It should support specialized communities and the structured collaboration on developing new statistical processes
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Catalogue of reusable solutions and standards
• The storage of methods, resources and tools should
• support the design of statistical production
• make sure that new statistics are designed in uniform ways so to support swift implementation by ESS members, according to agreed-upon quality standards
• be integrated with the ESS unified metadata management system
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Statistical processing
• Statistical processing services will be made available by members of the ESS to the community either on a voluntary or mandatory basis
• Examples of such services would be validation of data, specialized tests, aggregation, etc.
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Consumer management and tracking
• To support a consistent surveying of users of statistical data, a shared service used for querying user satisfaction should be made available to the members of the ESS
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Design of collection instruments
• Design of collection instruments so they can be produced faster and in a more coherent way across ESS members and statistical Business Functions
• Ways to achieve this are the use of harmonized expression languages to build the surveys and harmonized structures for capturing data
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Process Orchestrator
• As a key element in the ESS a system should be made available that can orchestrate the statistical processing services into production processes and support the design and management of these processes
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Data exploration and analysis platform
• Scalable platform for exploration and analysis of potentially very large data sets, with possible privacy requirements
• The platform provides sophisticated features to manipulate and aggregate data and display the results of the analysis to support exploration as well as analysis
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Data collection service
• Service that allows the collection of the data and metadata, and loads it in the primary data storage
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Dissemination
• ESS-wide platform that enables the dissemination of statistical output. The platform’s set up and composition reflects the policy & political priorities the ESS participants have agreed upon
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ESS Data exchange
• Platform that provides a bridge between ESS members and provides exchange services e.g. service message routing, service catalogue, message transformations etc.
• Members should still implement member-specific integration platforms to support internal service integration
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Identity and access management (IAM)
• Trust-based Identity and access management relying on legal, organizational, semantic and technical interoperability agreements between ESS participants
• Such agreements include joint definition of access levels and access criteria; harmonized security requirements.
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IT security
• Secure hosting and networking services e.g. to share statistical microdata, access to flexible computing capacity
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Data Supplier registry
• This BB contains information on potential data providers
• It also contains Service Level Agreement with them
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Mapping business capabilities and BBs
BBs in their totality support
all phases required in the production of
statistics, from data collection
to dissemination &
evaluation
BBs realize crucial services and
capabilities which range across several statistical phases. Examples of BBs
overarching multiple phases are metadata
management and Identity & Access
Management
Most ESS EARF BBs are
supporting 2 or more business
capabilities
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Mapping BBs to standards ESS EARF Building Blocks Business Information Application
Catalogue of reusable solutions and standards BPMN
Identity and access management (IAM) ISO/IEC 27001
Secured IT services
ISO/IEC 27001
Metadata management
GSBPM
GSIM
SDMX (IM)
DDI
ISO 11179
SDMX (Registry
and web services)
Statistical processing
GSBPM
BPMN
GSIM
SDMX (IM)
DDI
CSPA (services)
SDMX
(messages, web
services)
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Mapping BBs to standards Design of collection instruments
GSBPM
GSIM
DDI
XBRL
SDMX (IM)
DDI
XBRL
XForms
Data collection
GSIM
SDMX (IM)
DDI
XBRL
CSPA
SDMX
Primary data storage GSBPM GSIM
Process Orchestrator
GSBPM
BPMN
GSIM
SDMX (IM)
VTL
CSPA (services)
SDMX
(messages, web
services)
Data exploration and analysis VTL
Dissemination data storage GSBPM
GSIM
SDMX (IM)
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Mapping BBs to standards Dissemination
GSBPM
GSIM
SDMX (web
services, registry)
DDI
BPMN
SDMX (XML,
JSON)
DDI (micro data)
RDF (LOD)
ESS Data exchange GSBPM
GSIM
SDMX (IM)
DDI
SDMX
(messages, web
services, registry)
DDI, encryption
PGP
GSBPM
GSIM
SDMX (IM)
DDI
SDMX
(messages, web
services, registry)
DDI, encryption
PGP
GSBPM
GSIM
SDMX (IM)
DDI
SDMX
(messages, web
services, registry)
DDI, encryption
PGP
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Relationship with previously introduced standards
• Beyond the discussed relationship with GSIM and GSBPM, a relationship with CSPA exists, namely:
• Building blocks support SOA basis of CSPA
• Building blocks (as seen) are intendend to list re-usable blocks that are
• at a higher level within the Application Layer wrt to CSPA services
• CSPA services, covering also «implementation» can be intended to be at a lower level of the Application Layer
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Use Cases: ESS governance
• Forms a point of reference for discussions regarding the prioritization and governance of ESS initiatives
• Identifies focus areas for Vision 2020 initiatives
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Use Cases: ESS Enterprise Architects
• Use as a reference in discussion related to projects: evaluation of possible redundancies and conflicts between ESS projects as well as between ESS projects and NSI, respective Eurostat- specific projects
• Design, revise and compare reference architectures of the individual ESS members amongst each other and with the overall ESS EARF
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Use Cases: ESS Enterprise Architects
• Design, revise and compare information system architectures of the individual ESS members amongst each other and with the overall ESS EARF
• Document ESS EARF building blocks e.g. in an ESS EARF architecture repository
• Maintain the architecture repository as a catalogue of reusable assets
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Use Cases: Usage by ESS Business Leaders
• Use as reference in the discussion of the formation and prioritization of projects with IT
• Identify synergies between business projects reusing the same building blocks
• More tangibly scope business projects
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Use Cases: Usage by ESS project leaders
• Use as reference in framing and forming projects to define which ESS EARF BBs are affected by the project
• Search for reusable ESS EARF BBs and interoperability solutions
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Use Cases: Usage by IT leaders
• Use as reference in comparison with ESS member-specific architectures
• Help to create, manage and rationalize the ESS members’ versus ESS-wide building block portfolios
• Structure the architectural implications of statistical subject matter domain-specific ESS projects
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Towards a governance model for EARF
• Four types of scenarios where BBs can be used:
• Autonomous: NSIs design and operate BBs without coordination with other ESS members
• Interoperable: NSIs have the autonomy to design and operate their own BBs, as long as they have the ability to exchange information and operate together effectively (Coordination through interoperability)
• Replicated: NSIs implement identical BBs (Coordination through replication)
• Shared: NSIs access and share common SOA services
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Grouping BBs by governance approach
• Shared
• ESS Data exchange
• Collaboration
• Consumer management and tracking
• Catalogue of reusable solutions and standards
• Interoperable
• Identity and access management
• Replicated
• Design of collection instruments
• Process Orchestrator
• Data collection service
• Primary data storage
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Grouping BBs by governance approach
• Shared or Replicated
• Data exploration and analysis platform
• Data supplier registry
• Quality assessment
• Dissemination platform
• Statistical processing
• Shared or Replicated or Interoperable
• Dissemination data storage
• Metadata management
• IT Security