2010 Analysis of existing metadata case studies

Alice Born (Statistics Canada),

Joza Klep (Statistical Office of the Republic of Slovenia)

METIS Work Session March, 2010

Existing case studies

17 existing cases studies from :

Albania (ALB), Australia (AUS), Austria (AUT), Canada (CAN), Croatia (HRV), Czech Republic (CZE), Finland (FIN), Germany (DEU), Latvia (LVA), Netherlands (NLD), New Zealand (NZL), Norway (NOR), Portugal (PRT), Slovenia (SVN), South Africa (ZAF), Sweden (SWE) and the United Nations Industrial Development Organization (UNIDO)

Available from the METIS-wiki

http://www1.unece.org/stat/platform/display/metis/

Scope of analysis

• In response to participants’ requests,2010 analysis focuses on:

Section 1 and Section 2.4 Strategies for implementation

Section 4

System and design issues

Section 5

Organizational and workplace culture issues

Section 6

Lessons learned

Metadata strategies

• Template: Explanation of the overall strategy for managing metadata across the organization.

• For example, the mandate/programme providing framework for the project, and basic metadata management principles used.

1. implicit metadata strategies

2. explicit metadata strategies

Implicit metadata strategies (part of wider context)

• New business architecture

• Architecture for datawarehouse

• SOA funcitionality

• Process-oriented production

• Finding and interpreting statistical data

• Formal process for standardization

Explicit metadata strategies - examples

• Strategy for End-to-End Management of ABS Metadata - Australia• Strategically, our metadata management system forms part of a

larger system of applications called the End-to-end Statistical Data Management Facility (ESDMF). Metadata driven system is inevitable because metadata is used and generated at every stage of the statistical production process - South Africa

• The Business Model Transformation Strategy (BmTS) is designing a metadata management strategy that ensures metadata - New Zealand

• One of the primary objectives of the Integrated Metadatabase (IMDB) is to inform users on concepts, methodologies and data accuracy. The IMDB provides the metadata to support the statistical products released by Statistics Canada's Dissemination Division, and relates to the interpretability in the Agency's quality assurance framework - Canada

Explicit metadata strategies - examples

• To standardize definitions across all statistical activities; to move the production of statistics closer to the subject-matter experts in order to speed up the statistical survey life cycle; to present statistics on internet along with its context in order to make statistics understandable and available to users of all types, i.e. to extend the use of statistics beyond the usual statistical publications - Croatia

• Systematic use of metainformation inside and outside the SIS as a tool for internal and external integration. SMS is focused on the SPP. The model used for definition of a statistical variable ensures its standard description from the beginning up to the end of LCST - Czech Republic

Explicit metadata strategies - examples

• there are several projects - independently planned and implemented - that involve a centralised metadata management. Taken together, these projects form the work plan for the next 2-3 years. The task is to combine the projects in a way that at least the outline of a common metadata strategy starts to emerge - Germany

• The strategy focuses on establishing a conceptual framework, clear roles and responsibilities, and a stepwise development involving integration and linkage of systems - Norway

• In 2002 after thoughtful analysis of data and metadata flows, Integrated Metadata Driven Statistical Data Management System (further IMD SDMS) was created - Latvia

Implementation Strategy (2.4)

• Most countries reported a “step-wise” implementation

• Also reported: – swinging of pendulum– integration of previously existing legacy

systems into an Integrated Metadata System– »big-bang« with a subsystems implementation

strategy

Implementation Strategies – Stepwise approached

• from a set of static web pages to definitions of concepts variables and classifications

• Five surveys as pilots• new metadata in parallel with general modificitaion of

statistical data system• systems by systems, first classifications • new development projects should act according to the

new business architecture

Implementation Strategies – “swinging of the pendulum”

• from »big bang« (cathedral projects) – to »opportunistic ("piggybacking" on other projects ) and incremental with a broad »master plan«

• development of a "2020 Vision" encapsulating longer term ABS aspirations. Having clearly defined the state the ABS aspires to reach longer term, the next step would be to determine the most appropriate strategy for moving forward.)

• these two considerations informed the development of the "SESAME Framework" (Standards Enabled Shared Active Metadata Environment) in 2008

Australia

Implementation Strategies – integration of previously existing legacy systems into the IMS

• In order to minimize the complexity of the complete system, the individual components (subsystems) should be able to work independently, communicating with each other and the central "Registry" by means of a web service and program interface layer

Austria

Implementation Strategies

»big-bang« with a subsystems implementation strategy

Czech Republic

System and design issues

Section 4 of case study template

4.1 IT Architecture

4.2 Metadata Management Tools

4.3 Standards and formats

4.4 Version Control and Revisions

4.5 Outsourcing v.s. in-house development

4.6 Sharing software components and tools

Tools and standards (4.2 and 4.3)

ISO-IEC 11179 59%

SDMX 47% (in use, planning to use)

DDI 29%

Neuchâtel 35%

Oracle database 29%

.NET 53%

PC-Axis 18%

Metadata system components

GSPBM 29%

Corporate metadata system 41%

Collection management system 12%

Data archiving 29%

Survey metadata (passive) 59%

Process metadata (active) 35%

Dataset registry 29%

Metadata system components

• Data element registry 59%• Classification system 76%• Classification coding system 12%• Questionnaire development tool 24%• Questions and response choices 41%• Questionnaires 65%

Architecture and development (4.1, 4.4 and 4.5)

• Service-oriented architecture (SOA) and enterprise service bus – 35% +

• In-house development – 59% and mixed 29%

• Sharing of software – being discussed by NSOs (UN Statistical Commission, MSIS)

Organisational and workplace culture issues

Section 5 of case study template

5.1 Overview of roles and responsibilities

5.2 Training and knowledge management

5.3 Partnerships and cooperation

Subject-matter expert 82%

IT experts 76%

Methodologist 65%

Dissemination expert 47%

Standards 29%

Project manager 24%

Business analyst 12%

Terminologist 9%

One organizational metadata unit 47%

Roles (5.1)

Training (5.3)

• Methods– Intranet 35%– Manuals 24%– Workshops 47%– New employees 18%

Partnerships and cooperation (5.4)

• ALB – worked with Statistics Sweden• AUS – global partnership in software development,

implementation of SDMX, DDI • AUT – University of Vienna, participation in METIS • CAN – participation in METIS • HRV – worked with Statistics Sweden • CZE – internal • FIN - participation in METIS, INSPIRE (spatial metadata) • DEU - participation in METIS, Statistics Norway and

Swiss Federal Statistical Office

Partnerships and cooperation (5.4)• LVA – metadata workshops delivered by Sweden,

Norway and Finland• NLD - participation in METIS • NZL - participation in METIS • NOR - participation in METIS, Neuchâtel, Scandinavian

collaboration• PRT – visits to CAN, advice to SVN and African

countries, SDMX Eurostat Workforce• SVN - participation in METIS, PC- Axis Reference Group• ZAF – visited AUS, NZL, LAV, Ireland and advice from

CAN • SWE – member of Neuchâtel, PC-Axis Nordic Cooperation

Lessons learned: Main themes

• Top management involvement

• Significant change/framework

• Quality of metadata

• Complexities of metadata

• Find a common language

• Project management

• International cooperation

Top management involvement

• It is a challenge to formulate a convincing business case for metadata

• Business issue rather than IT• All high-level units given a role • Metadata strategy – official mandate• All steps of statistical data processing for different

surveys allow standardization, while each survey may require complementary functionality

Significant change/framework

• Recognize that this is a major change• Communication strategy• Allow business areas to influence implementation• Integrate with business processes• Statisticians love frameworks so having one makes life a

lot easier• Reference to formal documents like the metadata- and

IT-strategy is important (approved by the board of directors)

Quality of metadata

• Some metadata is better than no metadata - as long as it is of good quality

• Depends on cooperation, motivation and competencies of metadata authors

• More efficient to start documenting the metadata right at the outset of any new survey design

• Authors need to know and understand the how and why of metadata

• Releasing metadata on the internet improves metadata quality

Complexities of metadata

• Not one ideal structure/format• Communication of complex metadata principles is a

challenge• Papers for the METIS sessions and the common

metadata framework (especially the case studies) have proven very useful, as they provide arguments for discussions with statisticians and top management

• Fundamental principles of metadata management, which have been defined by experts during recent years (i.e., In part A of the common metadata framework) will become more and more commonly accepted standards and state of the art for the production and dissemination of statistical information

• Other metadata standards provide opportunities

Find a common language

• Applying externally recognised and supported standards has a lot of benefits - including as a means of building upon a wealth of intellectual efforts and experiences from others

• Use a metadata framework as common language• Training of statisticians, not only in the use of

applications but also, and above all, about the concepts underlying the system and workflow of procedures

• Harmonization between subject areas

Project management

Make simple prototypes as early as possible to get input from users, written requirements are to abstract

The advantages and disadvantages of a metadata model can often only be properly evaluated once an it-system is in place

»Translation« from »statistical language« to »IT language« can cause misunderstandings

• Keep in control of outsourced development activities, supplier may have difficult time understanding the statistical business

Usability testing• Opportunity costs caused by the non-existence of

centralized end-to-end metadata systems are rarely found in accounting systems

International cooperation

• Might help to understand the subject of metadata management

• Similarity of the statistical process is important for IT personnel

• Building on existing international knowledge minimises risks and maximises return on investment

• SMS is increasingly expected to interoperate with metadata management as practised in other communities (eg geospatial, academic/research) and sectors

Future work• New case studies in METISwiki – looking

for countries to add their case studies

• Convergence on the use of key metadata standards and metadata models– Can we move to more harmonization in

implementation across countries?– Further analysis on comparing architectures

• Suggestions for improving template

• Add tables to WP on METIS website