SISAI STATISTICAL INFORMATION SYSTEMS ARCHITECTURE AND INTEGRATION WORKING GROUP 3rdMEETING 13-14 MAY 2013 ITEM 2.6 Cross-cutting project on standards and information models including the integrated use of DDI and SDMX

E.S.S. cross-cutting project on Information Models and Standards SISAI 3 Meeting 14th of May 2013 Marco PELLEGRINO (Eurostat) Denis GROFILS (Eurostat)

ESS.VIP programme Transformation programme for the modernisation of the production systems in the European Statistical System (ESS) through: moving towards more common solutions and shared services and environment economies of scale and efficiency gains, sharing costs WORK Vs CHANGE? Context : Production of European Statistics European statistical system : a complex system with many production lines (NGOs and Eurostat) Long tradition of output harmonisation (legal framework) Tradition of cooperative developments (ESSnets) ICT changes and IT rationalisation in many organisations

ESS.VIP business and information principles Maximum reuse of existing process components and segments Metadata driven processes allowing adaptation and extension to other contexts New business process built as a sequence of modular process steps / services Information objects structured according to available information models and stored in corporate registries/repositories in view of reuse Adherence to industry and open standards as available (e.g. Plug & Play)

ESS.VIP Programme components Projects in statistical domains Technical cross-cutting projects Frameworks and administrative mechanisms ADMIN Information models and standards Communication NAPS Network for information exchange Governance PRIX Data warehouses Human resources ESBRs Shared services Sharing costs Financial resources SIMSTAT Legal framework ICT Programme management Common data validation policy Several dependencies

Information Models Standards Objectives: To ensure that ESS.VIP have access to a set of agreed-upon standards supporting the modernisation of statistical production processes. To increase coherence between standards, at the same time ensuring that these are consistent with best practices and recommendations from the international community. To define information models that can be used across the ESS to model structural metadata for micro-data and aggregated data. To set up guidelines for designing and documenting business processes. To provide support mechanisms (e.g., capacity-building and training).

Phases 2013 2014 2015+ Q1-2 Q3-4 1.1. Review of ESS.VIP project requirement   1.2. Recommendations to ESS.VIP 2. Analysis of standards and models 3. Proposal for an integrated standard to handle micro-data and aggregated data 4. Business process description 5. Maintenance and further enhancement of standards 6. Capacity building

Which standards and models? Re-use existing resources Link to on-going initiatives (e.g. Sponsorship on Standardisation, ESSnets, GSIM and DDI-SDMX mapping)

The SDMX-DDI approach SDMX-DDI dialogue (2010-2013) Initiative of the SDMX Secretariat through its Technical Working Group HLG project: Frameworks and Standards for Statistical Modernisation Approach to using SDMX and DDI interchangeably Implementations being investigated and prototyped (not “if”, but “how”) Most often, this is done in the context of the Generic Statistical Business Process Model (GSBPM) Idea of “industrialised” statistical production Strong emphasis on process management Informal meetings (2010-2013) between members of SDMX and DDI communities, looking for ways in which the standards could be used together effectively Initiative of the SDMX Secretariat through its Technical Working Group

Generic Statistical Business Process Model DDI DDI SDMX

GSBPM, DDI and SDMX: towards a complete picture?

Characterizing the Standards: DDI DDI Lifecycle can provide a very detailed set of metadata, covering: The study or series of studies Many aspects of data collection, including surveys and processing of microdata The structure of data files, including hierarchical files and those with complex relationships The lifecycle events and archiving of data files and their metadata The tabulation and processing of data into tables (Ncubes) It allows for a link between microdata variables and the resulting aggregates

Characterizing the Standards: SDMX Describes the structure of aggregate/dimensional data (“structural metadata”) Provides formats for the dimensional data Provides a model of data reporting and dissemination Provides a way of describing and formatting stand-alone metadata sets (“reference metadata”) Provides standard registry interfaces, providing a catalogue of resources Provides guidelines for deploying standard web services for SDMX resources Provides a way of describing statistical processes

SDMX Process Metadata Data validation and editing, SDMX Registry, DSD and data set, MSD, metadata set, Web services Process Metadata DDI has much more detailed metadata at the level of the study, because it is intended to describe the full process of data production (the data lifecycle) DDI provides more complete descriptions of the processing of data SDMX provides more architectural components, to support reporting/collecting and exchange SDMX provides generic mechanisms to support foreseen and non-foreseen use cases (categorisation, HCL, MSD) Similarities: Both standards use a similar mechanism for structuring URN identifiers Both standards use a similar model for identifiable, versionable, and maintainable things Both have a concept of an owning agency There is a very similar set of rules about versioning and maintenance Both standards use “schemes” as packages for lists of like items Both standards are designed to support reuse, and have similar referencing models

DDI and SDMX DDI offers a very rich model for the documentation of micro-data SDMX offers a very integrated exchange platform for statistical outputs (IT architectures, tools, web services) When people think about using SDMX and DDI together, they make assumptions Microdata (and tabulations) can be described using DDI A transformation could be applied to produce SDMX to describe the aggregates/tables There is a straight mapping from DDI to SDMX Interestingly, this conceptual model is not how the use of DDI and SDMX together is being approached in reality The Devil is in the details! The combined use of both standards could allow a higher level of integration of the complete production process No «one size fits all» solution But: The devil is in the detail!

Analysis of use cases The SDMX TWG has been defining a set of relevant use cases where the two standards could be compared and, if possible, used together: Survey data collection Administrative and register data Combined use of DDI and SDMX Micro-data access and on-demand tabulation of micro-data Metadata and quality reporting

Survey data: the proposed approach Process a (CSV) micro-data file accompanied by a DDI instance with both structural and processing metadata Import data file based on structural info Derive new variables Aggregate data Output aggregated SDMX data files Structured according to a Data Structure Definition (+MSD?) Comprising dimensions, attributes and measures Each taking their semantic and representation from a Variable Without loss of metadata!

The challenge Is not about which "flavour" of XML we use (XML doesn’t really matter) It’s about data and metadata! If I am using SDMX, but I am sent DDI, a simple transformation could give me the same payload of data and metadata. Vice-versa for SDMX users Conventions will need to be established regarding identifiers and the way the unit record files are structured There will need to be agreed models for each business case At the end, users would not really care whether DDI or SDMX is used, as long as the system supports the use cases!

The vision: combining DDI and SDMX Mixing the two standards within an implementation, allowing for the expression of the same metadata in both standards, so that the information could be transformed from one format to the other Metadata stored and indexed in such a fashion that it can be expressed either as SDMX or DDI on an as-needed basis The actual format used for metadata storage may be neither SDMX nor DDI, so long as it can be expressed using both standards Standards-agnostic Metadata Repository and Registry Portal for data and metadata discovery GSIM to be implemented through a combination of SDMX and DDI?

Generic Statistical Information Model (GSIM) Dedided on the conceptual framework, now we can focus on “how to” implement (methods, technoology) We have decided on the conceptual framework (GSBPM, GSIM). Now we can focus on “how to” implement (SDMX, DDI, RDF, etc.)

GSBPM, DDI and SDMX: towards a complete picture?

Marco.Pellegrino@ec.europa.eu Denis.Grofils@ec.europa.eu Feedback is welcome Comments on the IMS cross-cutting project: - on relevance and timeline - on open issues (IT infrastructure) - on how to move forward (task-force, sprint?) Expressions of interest in participating Marco.Pellegrino@ec.europa.eu Denis.Grofils@ec.europa.eu