Draft Chapter 9: Data Dissemination
7th Oslo Working Group, Helsinki 2012
Maluta Robert Kwinda
Deputy Director: Energy Data and Integrity
Department: Energy
South Africa
Topics to be covered
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Overview
Data (Coverage, Periodicity and Timeliness)
Reference Period
Dissemination Schedule
Confidentiality
Revision policy
Dissemination format and access
Meeting users´ needs
Overview
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Provides information on background, objectives and content of the Chapter
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Touches on 7 key dimensions of an effective data dissemination system:
- Data (coverage, periodicity and timeliness);
- Reference period;
- Dissemination Schedule;
- Confidentiality;
- Revision policy;
- Dissemination Format and Access; and
- Meeting User needs.
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These dimensions are explained in detail and are basically the content of this Chapter
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More content may stilll be added on receipt of further inputs.
Data
Coverage
• Coverage measures the extent to which statistical units account for the
entire population.
• Information on coverage promotes interpretability of statistical findings as
well as correct usage of micro data.
• Often readily available in metadata documentation
• Disseminated as part of metadata accompanying statistical releases
Data
Periodicity
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Refers to the frequency of compilation of the data.
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Is determined by various factors, including but not limited to:
- needs for analysis.
- ease of compilation.
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Periodicity should as much as possible aligned to availability of data in recognition of
longer compilation periods.
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Periodicity is usually expressed in terms of divisions in the calender and the divisions
can be represented by year, semester, quarter, month and even a day.
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In many systems, priodicity can be the same whereas timeliness may vary according to
data availability and economic sensitivity attached to various data elements.
Data
Timeliness
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Refers to the lapse of time between reference peiod and dissemination time.
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Critical for usability/relevance of the data ( old data are useful for projection
but more recent data are more useful and reflective of current situation)
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It has implications on various intenal actvities. Including preparation of
accompanying commentatry , printing and preparation of CD-ROM´s.
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Timeliness can be affected by many factor including delays in the provision of
data due to varying reporting peiod (calender vs. fiscal year). In such nstnces.
Reasonable time stretch should be worked out.
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Improvements in timeliness should not compromise data quality, rather
incremental improvements over time syncronised with improvement on data
quality management systems should be the objectice.
Reference period
• Referes to the time period for which statistical data are collected or
calculated.
• May be a calender year, fiscal year, semester, quarter, a month or even a
day.
• Should be distinguished from publication time: the publication year may
actually be much later than the reference year.
Dissemination schedule
• Ideally, a dissemination schedule should be released to the media well in
advance (even a year prior dissemination).
• Must be made accessible to all users through release to general media and
internet sites.
• Prior to embargo/scheduled time, statistics should be kept confidential.
• Advance access should be confined to certain individuals on the basis of
genuine needs: for preparation of commentaries on social and economic
conditions as may be reflected by the statistics.
• Advance access should be limited to a very short period ( 3 to 4 days)
Confidentiality
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Confidentiality covers aspects ranging from IT security to disclosure
restrictions both within and between agencies.
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Information about confidentiality should be documented and disseminated.
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Statistical releases may include information on how confidentiality is
managed.
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Publications on website can be used to describe how confidentiality is assured,
including statements on the legal basis for data dissemination.
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Employees and end users of micro-data should enter into formal
confidentiality agreements with the statistical agency.
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Data should be at a level of disaggregation which does not compromise
confidentiality of individual information or records.
Revision policy
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Revisions may be as a result changes in the undelying data.
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They should be aimed at improving the quality and integrity of the statistical
information
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Commonly made to incorporate improvements in the statistical framework:
Concepts, definition, classifications, conversions, data sources and compilation
methodology.
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Information about revisions should be communicated and well in advance through
publication of revision schedule.
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The possible impact of major methodological or framework changes on key
statistical figures should be clearly articulated in the revision schedule.
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Metadata which normally accompany staistical releases should describe revision
policy for each data category.
Dissemination format and access
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Sustainable flow of comprehensive, reliable, accessible and timely energy
statistics is vital for energy planning and policy formulation.
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Statistics of common public interest can be disseminated through press
releases, posting of the statistics on the websites, Release of hardcopies,
Production of CD-ROM products for key users and subscribers, online
interactive systems which enable users to build statistical tables to thier own
requirements and provision of data enquiry service, including customised data
tabulation service.
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Data quality statements and explanatory notes for key finding should be
should for part of the publication.
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Agencies must ensure that there are no barriers of access, i.e costs,
internet(not everyone has access to internet), etc
Meeting user needs
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Users vary from politicians, govenment agencies private sectors and research
institutes and data prodivers themselves.
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Users need to be properly identified, synthesised, undestood and prioritied.
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User needs are diverse and constantly changing and require proper management.
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Consultations and workshops with users should be carried out for the purposes of
establishing, among other things,
- How they use the statistics in their operation
- Availability of the statistics
- Adequecy of the statistics in terms of relevance, accuracy, consistency,
timeliness, level of disaggregation, accessibility etc.)
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Its improtant to identify those who are interrested in particular data sets and try to
manage users in groups. This can be achieved though web-based registration
forms and conventional mailing lists.
Questions?
Contact data:
Maluta Robert Kwinda
Department of Energy
Tel: +27124067536
E-Mail: Maluta.kwinda@energy.gov.za