In GAMSO v1.1, under Corporate Support, there is a box called "Manage information and knowledge"

Manage information and knowledge

These activities include the ownership or custody of records, documents, information and other intellectual assets held by the organisation and the governance of information collection, arrangement, storage, maintenance, retrieval, dissemination, archiving and destruction. They also include maintaining the policies, guidelines and standards regarding information management and governance. These include:

  • Manage documents and records, including archiving and destruction
  • Manage knowledge
  • Manage information standards and access rights
  • Manage metadata and data

 

In GSBPM v5, Metadata Management is an overarching process.

Metadata Management

115. Good metadata management is essential for the efficient operation of statistical business processes. Metadata are present in every phase, either created or carried forward from a previous phase. In the context of this model, the emphasis of the over-arching process of metadata management is on the creation, use and archiving of statistical metadata, though metadata on the different sub-processes themselves are also of interest, including as an input for quality management. The key challenge is to ensure that these metadata are captured as early as possible, and stored and transferred from phase to phase alongside the data they refer to. Metadata management strategy and systems are therefore vital to the operation of this model, and these can be facilitated by the GSIM.

116. The GSIM is a reference framework of information objects, which enables generic descriptions of the definition, management and use of data and metadata throughout the statistical production process. The GSIM supports a consistent approach to metadata, facilitating the primary role for metadata envisaged in Part A of the Common Metadata Framework3 "Statistical Metadata in a Corporate Context", that is, that metadata should uniquely and formally define the content and links between objects and processes in the statistical information system.

117. Part A of the Common Metadata Framework also identifies the following sixteen core principles for metadata management, all of which are intended to be covered in the over-arching Metadata Management process, and taken into the consideration when designing and implementing a statistical metadata system. The principles are presented in four groups:

Metadata handling

    1. Statistical Business Process Model: Manage metadata with a focus on the overall statistical business process model.
    2. Active not passive: Make metadata active to the greatest extent possible. Active metadata are metadata that drive other processes and actions. Treating metadata this way will ensure they are accurate and up-to-date.
    3. Reuse: Reuse metadata where possible for statistical integration as well as efficiency reasons
    4. Versions: Preserve history (old versions) of metadata.

Metadata Authority

  1. Registration: Ensure the registration process (workflow) associated with each metadata element is well documented so there is clear identification of ownership, approval status, date of operation, etc.
  2. Single source: Ensure that a single, authoritative source ('registration authority') for each metadata element exists.
  3. One entry/update: Minimise errors by entering once and updating in one place.
  4. Standards variations: Ensure that variations from standards are tightly managed/approved, documented and visible.

Relationship to Statistical Cycle /Processes

    1. Integrity: Make metadata-related work an integral part of business processes across the organisation.
    2. Matching metadata: Ensure that metadata presented to the end-users match the metadata that drove the business process or were created during the process.
    3. Describe flow: Describe metadata flow with the statistical and business processes (alongside the data flow and business logic).
    4. Capture at source: Capture metadata at their source, preferably automatically as a by-product of other processes.
    5. Exchange and use: Exchange metadata and use them for informing both computer based processes and human interpretation. The infrastructure for exchange of data and associated metadata should be based on loosely coupled components, with a choice of standard exchange languages, such as XML.

Users

      1. Identify users: Ensure that users are clearly identified for all metadata processes, and that all metadata capturing will create value for them.
      2. Different formats: The diversity of metadata is recognised and there are different views corresponding to the different uses of the data. Different users require different levels of detail. Metadata appear in different formats depending on the processes and goals for which they are produced and used.
      3. Availability: Ensure that metadata are readily available and useable in the context of the users' information needs (whether an internal or external user).

 

 

1ISO 9000:2005, Quality management systems – Fundamentals and vocabulary. International Organization for Standardization
2A suitable global framework is the National Quality Assurance Framework developed by a global expert group under the United Nations Statistical Commission. See: http://unstats.un.org/unsd/dnss/QualityNQAF/nqaf.aspx
3See: http://www.unece.org/stats/cmf/PartA.html

 

 

Questions: How do we manage having Metadata Management in both GAMSO and GSBPM? Does the inclusion in GAMSO mean that it should not be in GSBPM? 

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4 Comments

  1. InKyung Choi

    19 Sep, 2017

    Feedback from Danny Delcambre (19th September, 2017); following is an excerpt from document GAMSO_GSBPM_delineation_for_metadata_management_activities.docx.

     

    From what is said [see comparison in the attached file], and especially the description from GAMSO, the conclusion that seems to emerge is that the limit between GAMSO and GSBPM is to be based on the level of centralization of metadata management. What is centralized, thus having a character of corporate support, should belong to GAMSO, what is done at production-unit level should belong to GSBPM. This distinction seems to fit exactly with the distinction institutional issues / process-related issues mentioned at our June teleconference.

    This distinction can also be expressed in other terms. Horizontal metadata systems (including metadata-driven architectures) which impact large parts of the production system should be considered as institutional, not only because of their horizontal character, but also because changes to such systems are very heavy to implement and very costly, thus requiring a high-level decision-making process. In this sense, the activity is closer to strategic management than to operational management. Metadata systems which are used in one statistical domain only ("silo" system) are generally maintained at production unit level and this corresponds more to GSBPM.

    Examples of GAMSO-related activities cover (these activities can be overlapping to a certain extent):

    • Centralized development of standards, methodologies, concepts, classifications and code lists (including geospatial) that are consumed by multiple processes.
      • Management and maintenance of central metadata repositories (including cartographic databases) (based on the general principles defined in the Common Metadata Framework, e.g. manage metadata with a focus on the overall statistical business process model; promote active metadata; promote reuse). Metadata are generated and processed within each phase, there is, therefore, a strong requirement for a metadata management system to ensure the appropriate metadata retain their links with data throughout the GSBPM. This includes process-independent considerations such as metadata custodianship and ownership, quality, archiving rules, preservation, retention and disposal.
      • Design and development of metadata driven systems.
      • Design of the structure of reference metadata frameworks (including process metadata), and associated documentation.
      • Design of SDMX Metadata Structure Definitions for national and international data exchange.
      • Develop archiving tools and repositories.
      • Draft governance of information collection, arrangement, storage, maintenance, retrieval, dissemination, archiving and destruction, as well as documentation relating to centralized metadata tools.

    Examples of GSBPM-related activities cover (these activities can be overlapping to a certain extent):

    • Select all relevant metadata, ready for use later in the statistical business process.
    • Prepare metadata descriptions of collected and derived variables and classifications.
    • Produce metadata on the editing and imputation process.
    • Fill in reference metadata framework (SDDS, DQAF, SIMS, etc.).
    • Match local databases to SDMX Metadata Structure Definitions.
    • Check that metadata and paradata (process metadata) associated with statistical outputs are present and in line with expectations.
    • Ensure that metadata to be disseminated do not breach the appropriate rules on confidentiality.
    • Collate supporting information, including interpretation, commentary, technical notes, briefings, measures of uncertainty and any other necessary metadata.
    • Update output systems: format metadata ready to be put into output databases; load metadata into output databases.
    • Gather evaluation inputs: It may take many forms, including process metadata (paradata), etc.
    • Archiving of statistical metadata.
    • Ensure that metadata presented to the end-users match the metadata that drove the business process or were created during the process.
    • Ensure that users are clearly identified for all metadata processes, and that all metadata capturing will create value for them.

     

  2. Essi Kaukonen

    29 Sep, 2017

    Dear Colleagues,

    Metadata has an important role in the statistical production processes, especially when we talk about metadata-driven processes. Hence, we support the idea of keeping the Metadata Management as an overarching process in the GSBPM. Furthermore, quite many organisations already use the GSBPM-model but do not implement the GAMSO-model. Hence, in our opinion, Metadata Management should be clearly visible in the GSBPM-model as it is today in the version 5.0.

    How about the idea of giving those Corporate Support activities, which are most closely related to the statistical production a special place in the GAMSO-model nearby “Production”? Following, these activities could then be included in both models?

    Essi Kaukonen
    Statistics Finland / Standards and Methods

  3. Steven Vale

    01 Oct, 2017

    I agree with Danny about making the distinction between metadata management specific to a process (so implicitly within GSBPM) and more centralised, corporate metadata management. The same holds true for data management and quality management, and possibly some other over-arching processes.

    My comment on Issue #23 (GSBPM and GAMSO) could also be relevant for this discussion.

  4. InKyung Choi

    02 Oct, 2017

    (Feedback from Australian Bureau of Statistics (ABS); 2 October, 2017)


    Metadata Management - GAMSO/GSBPM     . 

    The ABS perspective is similar to the feedback provided by Danny Delcambre in terms of "centralization" (likely to be in GAMSO) vs Statistical Program specific activities (likely to be in GSBPM).
    Where Danny says "(these activities can be overlapping to a certain extent)", I am reading that as "overlapping across the two lists" as opposed to overlapping between dot points WITHIN a particular list.

    Overlapping across lists certainly fits the ABS experience.
    For example, a Statistical Program Design might either need to 

    • show how corporate standard variables and statistical classifications are reused, OR ELSE
    • justify why a deviation from standards is required (eg due to data sources, due to the needs of consumers of these specific statistics). 

    In this sense, obtaining sign off for a Statistical Program Design is probably primarily "within GSBPM" but some of the governance activities pre-suppose the existence of corporate metadata activities and experts.
    Similarly training on metadata related models, infrastructure and practices is likely to be managed and delivered "outside" GSBPM but is then the training/knowledge is applied within GSBPM.