ABS Issues for DDI Futures Bryan Fitzpatrick October 2012.

Slides:



Advertisements
Similar presentations
SDMX in the Vietnam Ministry of Planning and Investment - A Data Model to Manage Metadata and Data ETV2 Component 5 – Facilitating better decision-making.
Advertisements

Federal Department of Home Affairs FDHA Federal Statistical Office FSO Meeting of the OECD Expert Group on SDMX September, OECD, Paris Centralized.
Information Infrastructure: Foundations for ABS Transformation Stuart Girvan, Australian Bureau of Statistics MSIS Paris, April 2013.
Mogens Grosen Nielsen Statistics Denmark
Implementation of GSBPM, DDI and SDMX reference metadata at Statistics Denmark UNECE workshop 5-7 May 2015 Mogens Grosen Nielsen
DDI 3.0 Conceptual Model Chris Nelson. Why Have a Model Non syntactic representation of the business domain Useful for identifying common constructs –Identification,
SDMX and DDI: How Do They Fit Together in Practical Terms? Arofan Gregory The Open Data Foundation European DDI User’s Group 2011 Gothenburg, Sweden.
Codebook Centric to Life-Cycle Centric In the beginning….
1 Business Exchange Structures Concepts.
Environment Change Information Request Change Definition has subtype of Business Case based upon ConceptPopulation Gives context for Statistical Program.
Background Data validation, a critical issue for the E.S.S.
ESCWA SDMX Workshop Session: Role in the Statistical Lifecycle and Relationship with DDI (Data Documentation Initiative)
CES 2012 Paris 1 High Level Group for Strategic Developments in Business Architecture in Statistics Strategy Gosse van der Veen, Statistics Netherlands.
WP.5 - DDI-SDMX Integration
WP.5 - DDI-SDMX Integration E.S.S. cross-cutting project on Information Models and Standards Marco Pellegrino, Denis Grofils Eurostat METIS Work Session6-8.
NSI 1 Collect Process AnalyseDisseminate Survey A Survey B Historically statistical organisations have produced specialised business processes and IT.
Case Studies: Statistics Canada (WP 11) Alice Born Statistics UNECE Workshop on Statistical Metadata.
Survey Data Management and Combined use of DDI and SDMX DDI and SDMX use case Labor Force Statistics.
Statistics New Zealand Classification Management System Andrew Hancock Statistics New Zealand Prepared for 2013 Meeting of the UN Expert Group on International.
Statistics New Zealand Classification Management System Andrew Hancock Statistics New Zealand Prepared for 2013 Meeting of the UN Expert Group on International.
Using ISO/IEC to Help with Metadata Management Problems Graeme Oakley Australian Bureau of Statistics.
SDMX and DDI Working Together Technical Workshop 5-7 June 2013
Generic Statistical Information Model (GSIM) Thérèse Lalor and Steven Vale United Nations Economic Commission for Europe (UNECE)
3 rd Annual European DDI Users Group Meeting, 5-6 December 2011 The Ongoing Work for a Technical Vocabulary of DDI and SDMX Terms Marco Pellegrino Eurostat.
IMS Proof of Concept for Data Capture using Metadata Bryan Fitzpatrick Rapanea Consulting Limited June 2014.
Standardisation Informal summary of ABS Perspective.
The Adoption of METIS GSBPM in Statistics Denmark.
Technical Overview of SDMX and DDI : Describing Microdata Arofan Gregory Metadata Technology.
A Novel Approach to Architectural Recovery in Evolving Object- Oriented Systems PhD thesis Koen De Hondt December 11, 1998.
DDI-RDF Leveraging the DDI Model for the Linked Data Web.
Current and Future Applications of the Generic Statistical Business Process Model at Statistics Canada Laurie Reedman and Claude Julien May 5, 2010.
11 CORE Architecture Mauro Bruno, Monica Scannapieco, Carlo Vaccari, Giulia Vaste Antonino Virgillito, Diego Zardetto (Istat)
Environment Change Information Request Change Definition has subtype of Business Case based upon ConceptPopulation Gives context for Statistical Program.
InSPIRe Australian initiatives for standardising statistical processes and metadata Simon Wall Australian Bureau of Statistics December
Panel discussion questions for Session ii. Panellists Dan Gilman (BLS) – BLS are an associate member of the DDI Alliance Eric Rodriguez (INEGI) Achim.
United Nations Economic Commission for Europe Statistical Division High-Level Group Achievements and Plans Steven Vale UNECE
Statistical Metadata Strategy and GSIM Implementation in Canada Statistics Canada.
11 CORE Architecture Mauro Bruno, Monica Scannapieco, Carlo Vaccari, Giulia Vaste Antonino Virgillito, Diego Zardetto (Istat)
1 1 Developing a framework for standardisation High-Level Seminar on Streamlining Statistical production Zlatibor, Serbia 6-7 July 2011 Rune Gløersen IT.
DDI Methodology. Aims Purpose: To describe the study design specifications underlying the conduct of a research/business project. Possible coverage areas:
Eurostat SDMX and Global Standardisation Marco Pellegrino Eurostat, Statistical Office of the European Union Bangkok,
SDMX IT Tools Introduction
2.An overview of SDMX (What is SDMX? Part I) 1 Edward Cook Eurostat Unit B5: “Central data and metadata services” SDMX Basics course, October 2015.
GSIM Mapping to SDMX and DDI: Preliminary Findings and Status Arofan Gregory Metadata Technology METIS, May , Geneva.
Metadata Framework for a Statistical Data Warehouse
Role of the IMDB in the CBA and IM Strategy Presented to Information Management Committee Standards Division June
United Nations Economic Commission for Europe Statistical Division GSBPM and Other Standards Steven Vale UNECE
Modernisation Committee on Standards Priorities and future plans for 2015 and 2016 October 23, 2015.
>> Metadata What is it, and what could it be? EU Twinning Project Activity E.2 26 May 2013.
Metadata requirements for archiving structured data Alice Born Statistics Canada Joint UNECE/Eurostat/OECD Work Session on Statistical Metadata (9-11 April.
Metadata models to support the statistical cycle: IMDB
DDI and GSIM – Impacts, Context, and Future Possibilities
End-to-End Management of the Statistical Process An Initiative by ABS
Integrating Geospatial Elements into the ABS Information Model
The status of metadata standards and ModernStats models in SURS
Data Management: Documentation & Metadata
MSDs and combined metadata reporting
Survey phases, survey errors and quality control system
Using DDI to Automate Blaise Instrument Generation
Survey phases, survey errors and quality control system
Logical information model LIM Geneva june
Metadata in the modernization of statistical production at Statistics Canada Carmen Greenough June 2, 2014.
The Generic Statistical Information Model
The problem we are trying to solve
SISAI STATISTICAL INFORMATION SYSTEMS ARCHITECTURE AND INTEGRATION
Presentation to SISAI Luxembourg, 12 June 2012
Contributor Roles, Open Badges
Generic Statistical Information Model (GSIM)
Introducing the Data Documentation Initiative
DDI and GSIM – Impacts, Context, and Future Possibilities
Presentation transcript:

ABS Issues for DDI Futures Bryan Fitzpatrick October 2012

Use with Metadata Registry/Repository Store metadata once in MRR – probably as a Resource Package a “register/store” package, not a “use” package – use it by reference in all usage contexts We would like options for references everywhere – particularly in schemes Variable Schemes can reference Variables no other schemes can include items by reference

GSIM GSIM essentially aims to be the umbrella metadata context for Statistical Offices – based on the GSBPM – lots of things Statistical Offices want to help improve their processes Not really attempting to define “Actionable” metadata – happy to leave that mainly to DDI and SDMX – looking to them to “fill in” under GSIM

General GSIM Structures GSBPM-based – At lot of emphasis at the Specify Needs/Design stages – A lot of emphasis on the statistical structure Programs, Cycles, Activities Important “Context” metadata areas – in some ways analogous to DDI Groups and Sub-Groups Design away from “Silos” – explicit recognition of Data Resources separate Statistical Activities

General GSIM Structures Design away from Survey-centric focus – even-handed model for data acquisition survey, administrative, internet, other Process focus – DDI is very weak in this area – GSIM thinking is still evolving, incomplete Abstract Processes, Configured Processes, Executing Processes Base Processes on BPMN – but issues around designing for Process reuse – issues around linking to metadata – issues around configuring for statistical areas Functional metadata – DDI is good on instruments, weak elsewhere – GSIM will need metadata in all functional areas sampling, editing, imputation, derivation, weighting, confidentialising,... lots of thinking still to be done – probably mostly needs expression evaluation

General GSIM Structures Conceptual and Classifications – GSIM wants more sophisticated models for classification management critical area for Statistical Offices – management of evolution of large formal classifications » eg Industry, Occupation, Commodity – still need to for less formal, simple classifications Data Structures – attempt for model integration of unit-record and table structures DDI Unit Record model is good probably prefer SDMX model for tables maybe need to cope with more than file structures – Data integration

Context Metadata We see this as really important – I like the DDI Group/Sub-Group/Study Unit structure it encapsulates the context – We need a generalisation of that structure need to hold – statistical metadata of all types – process metadata and process configurations – “dataset” links – all mostly as MRR URNs – responsible units and people – “template” Study Units (generalised) – “Role-Forward” is big issues for statistical organisations Context metadata enables automation of this Also enables automation of the overall processes

Some nit-picking Annoying things in DDI – ordering of items in schemes can have contained items, items included from other schemes, perhaps included groups of items – but cannot order them! not important for some schemes (Concept, Variable) Critical for others (Code, perhaps Category) – Extensibility we always need options for including additional information in metadata DDI offering is Notes – not available in schemes and items » which is where you need tem we like SDMX Annotations – available everywhere – typed so conflicts do not arise

GSIM is important GSIM is the way Statistical Offices are planning to manage their business – if DDI want to be used in Statistical Offices underpinning GSIM is the obvious path – some tensions likely with data archive community but probably lots of commonality when you look closely (Some) Statistical Offices trying to manage the statistical process end-to-end – need “Actionable” metadata end-to-end ie DDI-type metadata