ESS EA TF Item 2 Enterprise Architecture for the ESS

Transcription

1 ESS EA TF Item 2 Enterprise Architecture for the ESS Document prepared by Eurostat (with the support of Gartner INC) 1.0 Introduction The members of the European Statistical System (ESS) have set up a Vision regarding the future of the ESS and the cooperation between its members. The ESS reference business architecture should be an anchor model for Vision implementation: It should enables the mapping of projects and provide general guidance to implementation project through identifying border conditions and interoperability condition, standards for implementation as well as principles for deciding on future investment and designing where relevant collaborative projects. The purpose of this document is to propose an approach to extend the reference business architecture prpoposed by the "ESSnet of Standardisation" in the ESS context, in view of allowing expressing the level of ambitions of ESS cooperation in different functional domains. The approach is to link the business model (for sake of simplicity limted to GSBPM phases) with supporting architecture building blocks organized by EA layers (see figure 1). For each architecture building block the level of ambition for ESS collaboration should be stated and where relevant a domain architecture can be developed together with scenario for collaboration in the ESS. 1

2 2.0 Architectures builing blocks The Fig 2 represents key supporting architecture building blocks which are derived from the ESS Vision It propose a a high-level functional and holistic view on the various components needed to support the statistical value chain, as defined in the Generic Statistical Business Process Model 1. The graph further distinguishes between the various typical layers of an Enterprise Architecture i.e. business, data, application and technology architecture (Togaf 2 terminology). The architecture notation standard that is used is Archimate The list is tentative and should be consolidated 1 GSBPM, Version 5.0 December 2013, Joint UNECE/EUROSTAT/OECD Work Session on Statistical Metadata (METIS) ( 2 TOGAF: The Open Group standard enterprise architecture methodology and framework 3 Archimate: an open and independent enterprise architecture modeling language from The Open Group 2

3 The description of the identified building blocks are provided in table 1 Architecture building block Description Potential benefits 3

4 Collaboration platform for statistical experts Storage of methods Statistical services End user satisfaction surveying Design of collection instruments Legacy based National production systems National production systems 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. The storage of methods should support the design of statistical production and make sure that new statistics are designed in uniform ways so to support swift implementation by ESS members, according to agreed-upon quality standards. Should be integrated with the ESS unified metadata management system. Statistical business 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. 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. Service that supports the design of collection instruments so they can be produced faster and in a more coherent way across ESS partners and statistical domains. Ways to achieve this are the use of harmonized expression languages to build the surveys and harmonized structures for capturing data. The architecture should support that, for the foreseeable future,members of the ESS will have legacy production and dissemination systems that will need to work as part of the to-be architecture. The architecture should support that a number of members of the ESS will use individual production systems that can interact with other elements in the architecture Support the joint development of new statistics Share good practice between members of the ESS Knowledge sharing and training facilities Support the exchange of good practice Support the rapid implementation of new statistics in the community Support quality management through coherent quality management practice and reporting A flexible architecture that can adopt quickly to changes Support the fast implementation of new statistics by reassembling existing ones Replicate good practice Share investments Support specialization Ensure consistent surveying of statistical users, both ex ante and ex post Support the identification of good practice in attracting users Share investments Greater re-usability of surveys across ESS partners and statistical domains Removal of redundancies between statistical surveys Faster statistical production cycles Greater comparability through more harmonized statistical outputs Adapt to investment cycles for the individual ESS members Adjust investment levels to budget constraints Support architectural requirements imposed by national governments / the European Commission Support the use of standard software packages. Adjust investment levels to budget constraints 4

5 Statistical production system Data collection service Dissemination Data Storage Primary Data Storage Dissemination Data Storage Unified metadata management system System providing all the functionalities to generate and produce statistics (reporting, designing statistical processes, statistical process orchestration, integration, imputation and validation services). Service that allows the collection of the data and metadata, and loads it in the primary data warehouse. This is a data storage that allows the dissemination of various outputs (including publication, data/metadata exchange). It provides for increasingly sophisticated features such as personalization of outputs, advanced visualization options, device/browser/platform independency, interactiveness (re-use and mash-up of data). Data is provided in open and/or linked formats. 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. Data Storage where the data and statistics for dissemination and publication are stored 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. Support the easy replication of statistical processes between members. Support the industrialization of statistical production. Support fast implementation of best practice and new staistics Uniform raw data formats Consistent branding increases user awareness and trust Unique entry point to European statistics (single portal) increases find-ability and visibility Greater usability Access to many more outputs provides users with greater opportunities to leverage data Standardization of DW Support the standardization of statistical production Ease of reporting Support for complex reporting Shared investment More efficient data handling Automation possibilities Less data manipulation, hence better data quality Support open data philosophy ESS Data exchange Platform Identity and Access Management (IAM) 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. Trust-based Identity and access management relying on legal, organizatonal, semantic and technical interoperability agreements between ESS participants. Such agreements include joint definition of access levels and access criteria; harmonized security requirements. Collaboration support Technical interoperability between systems Re-use of exising IAM solutions Re-enforcement of mutual trust Streamlining/simplification of IAM across the entire statistical value chain 5

6 Secured IT Services Secure hosting and networking services e.g. to share statistical microdata, access to flexible computing capacity Improved collaboration Respect of privacy and data sensitivity Infrastructure flexibility Rather than a directly implementable architecture, it should provide a guideline for future initiatives and solutions. It can serve to express the direction of where the ESS IT Landscape should evolve towards over the course of the next 5 to 10 years. This model will be an anchor model for further work downstream, such as gap analyses, the definition of implementation programmes, and the formation of IT and business development projects and initiatives. 3.0 ESS collaboration model The framework proposed draws on so called a federated approach for Enterprise architecture allowing to express the level autonomy at level of the different partners (Eurostat/NSIs) and an adaptable degree of sharing in planning and implementing, should this be feasible or more advantageous. In a federated architecture, we can discern four different approaches to consolidation of the building blocks: 1. Autonomous: Business processes and systems are designed and operated without coordination with processes or systems in other units. This applies to those architecture components that are distinct. 2. Interoperable: Coordination is through interoperability. NSIs/Eurostat have the autonomy to design and operate their own solutions, as long as they have the ability to exchange information and operate together effectively (of the solutions). 3. Replicated: Coordination is through duplication. NSIs/Eurostat have implemented identical business processes, solutions and information. 4. Shared: There are common business processes, a single instance of a solution and information that is shared by all the NSIs and Eurostat. The level of ambition of integration to be decided at strategic level can be represented by a colour codes on fig 2: 6

7 4.0 Next Steps The steps to be taken. 1. Find cummunalities with ESSnet on standardisation document on business architecture 2. Agree on the relevance of this modelling in the ESS context 3. Complete the list of architecture building blocks/functional compoents related to the Vision implementation 4. Identify next steps and responsibilities to get this model completed (top down vs bottom up) 5. Clarify the role of this model in Vision implementation projet formation 7