=== ires-2018-page-142.pdf === 129 Chapter X Dissemination A. Importance of energy statistics dissemination 10.1. The first fundamental principle of official statistics states, inter alia, that “official statistics that meet the test of practical utility are to be compiled and made available on an impartial basis by official statistical agencies to honour citizens’ entitlement to public information.”76 Dissemination is an activity for fulfilling this responsibility and refers to the provision to the public of statistical outputs containing data and related metadata. Energy data are usually disseminated by agencies responsible for energy statistics in the form of various statistical tables or by providing access to the relevant databases. However, country practices differ significantly in their effectiveness and further improvements in this area are necessary. 10.2. Dissemination policy. The dissemination policy should cover a number of issues, including (a) scope of the data for public dissemination, (b) reference period and data dissemination timetable, (c) data revision policy, (d) dissemination formats, and (e) dissemination of metadata and data quality reports. The dissemination policy should be user-oriented, reaching and serving all user groups (central government, public organizations and territorial authorities, research institutions and universities, private sector, media, general public, and international users), and provide quality information. While each user group has different needs and preferred data formats, the goal should be to reach all kinds of users rather than targeting specific audiences. Therefore, both publications and web sites should be designed as clearly as possible for the general public, as well as for researchers and the media. 10.3. Users and their needs. With the rapid developments in communication technologies, information has become a strategic resource for public and private sectors. Improving dissemination and accessibility of energy statistics is critical to users’ satisfaction. Effective energy data dissemination is not possible without a good understanding of user needs, as this in many ways predetermines what data should be considered for dissemination and in which formats. In this context, countries are encouraged to work closely with the user community by conducting vigorous outreach campaigns, including building stable and productive relationships with users and key stakeholders (for example, inviting interested users to become standing customers, actively helping users to find the statistical information they need and assisting them in the understanding of the role of energy statistics in sound decision making). In addition, the understanding of user needs and data requirements will assist in maintaining the relevance of the statistics produced. 10.4. Users satisfaction surveys. User satisfaction surveys are an important tool for detecting user needs and profiles. User feedback should be integrated into the planning process of official energy statistics in order to improve its effectiveness. It is recommended that countries conduct such surveys with the periodicity established by the responsible national agency. 76 Available from http://unstats .un.org/unsd/dnss/gp /fundprinciples.aspx.  === ires-2018-page-143.pdf === 130 International Recommendations for Energy Statistics (IRES) B. Data dissemination and statistical confidentiality 10.5. One important issue official statistics compilers face is the definition of the scope of data that can be disseminated publicly. The following elements should be taken into account when disseminating data. 10.6. Statistical confidentiality refers to the protection of data that relate to single statistical units, and which are obtained directly for statistical purposes or indirectly from administrative or other sources against any breach of the right to confidentiality. This implies the prevention of unlawful disclosure. Statistical confidentiality is necessary in order to gain and keep the trust of both those required to provide data and those using the statistical information. Statistical confidentiality has to be differentiated from other forms of confidentiality under which information is not provided to the public, such as, for example, national security concerns. 77 Ibid. 10.7. Principle 6 of the United Nations Fundamental Principles of Official Statistics provides the basis for managing statistical confidentiality. It states that “Individual data collected by statistical agencies for statistical compilation, whether they refer to natural or legal persons, are to be strictly confidential and used exclusively for statistical purposes.”77 10.8. Legal provisions governing statistical confidentiality at the national level are set forth in countries’ statistical laws or other supplementary governmental regulations. National definitions of confidentiality and rules for microdata access may differ, but they should be consistent with the fundamental principle of confidentiality. 10.9. Statistical confidentiality is protected if the disseminated data do not allow statistical units to be identified either directly or indirectly, thereby disclosing individual information. Direct identification is possible if data of only one statistical unit are reported in a cell, while indirect identification or residual disclosure may take place if individual data can be derived from disseminated data (e.g., because there are too few units in a cell, or because of the dominance of one or two units in a cell). To determine whether a statistical unit is identifiable, account shall be taken of all means that might reasonably be used by a third party to identify it. The Energy Statistics Compilers Manual will contain a separate section on the best country practices in this respect. 10.10. General rules for protecting confidentiality normally require that the following two factors be taken into account when deciding on the confidentiality of data: (a) number of units in a tabulation cell, and (b) dominance of a unit’s or units’ contribution over the total value of a tabulation cell. The application of these general rules in each statistical domain is the responsibility of national statistical authorities. 10.11. Methods of protecting confidentiality. As the first step in statistical disclosure control of tabular data, the sensitive cells need to be identified. Sensitive cells are those that tend to directly or indirectly reveal information about individual statistical units. Once they have been identified, the most common practices used for protecting against the disclosure of confidential data include: (a) Aggregation. A confidential cell in a table is aggregated with another cell and the information is then disseminated for the aggregate and not for the two individual cells. This may result, for example, in grouping (and disseminating) data on energy production at higher levels of SIEC that adequately ensure confidentiality; (b) Suppression. Suppression means removing records from a database or a table that contains confidential data. This method allows statisticians to not publish the values in sensitive cells, while publishing the original values in other cells (called primary suppression). Suppressing only one cell in a table means, however, that  === ires-2018-page-144.pdf === 131 Dissemination the calculation of totals for the higher levels to which that cell belongs cannot be performed. In this case, some other cells must also be suppressed in order to guarantee the protection of the values in the primary cells, leading to secondary suppression. If suppression is used to protect confidentiality, then it is important to indicate in the metadata which cells have been suppressed because of confidentiality; (c) Other methods. Controlled rounding and perturbation are more sophisticated techniques for protecting confidentiality of data. Controlled rounding allows statisticians to modify the original value of each cell by rounding it up or down to a near multiple of a base number. Perturbation represents a linear programming variant of the controlled rounding technique. 10.12. Statistical disclosure. Statistical disclosure control techniques are defined as the set of methods used to reduce the risk of disclosing information on individual units. While application of such methods occurs at the dissemination stage, they are pertinent to all stages of the process of statistical production. Statistical disclosure control techniques related to the dissemination step are usually based on restricting the amount of data or modifying the data release. Disclosure control methods attempt to achieve an optimal balance between confidentiality protection and the provision of detailed information. On the basis of available international guidelines78 and national requirements, countries are encouraged to develop their own statistical disclosure methods that best suit their specific circumstances. 10.13. An issue of balance between the application of statistical confidentiality and the need for public information exists. Balancing the respect for confidentiality and the need to preserve and increase the relevance of statistics is a difficult issue. It is recognized that legislation on statistical confidentiality has to be carefully considered in cases where its rigorous application would make it impossible to provide sufficient or meaningful information to the public. In official energy statistics, this issue is of particular importance, as in many countries the production and distribution of energy are dominated by a very limited number of economic units. 10.14. The setup of energy balances illustrates the challenge for official energy statistics. If, for instance, the transformation block of an energy balance cannot be published due to confidentiality, the quality of such a balance significantly deteriorates, since it will no longer be possible to have an internally logical energy balance showing the energy flows from production and imports/exports through transformation to final consumption. The question is how to make it possible to publish energy balances if there are few units in one part of the balance. The confidentiality issues have to be addressed. 10.15. Application of confidentiality rules in energy statistics. While recognizing the importance of the general rules on statistical confidentiality, countries should implement them in such a way as to promote access to data while ensuring confidentiality, and thus ensure the highest possible relevance of energy statistics, taking into account their legal circumstances. In this regard, it is recommended that: (a) Any information deemed confidential (and that needs to be suppressed) be reported in full at the next higher level of energy product (or energy flow) aggregation that adequately protects confidentiality; (b) Data that are publicly available (e.g., from company reports, publicly available administrative sources) be fully incorporated and disseminated; (c) Permission to disseminate certain current data, with or without a certain time delay, be requested from the concerned data reporters; 78 See, for example, Principles and Guidelines for Managing Statistical Confidentiality and Microdata Access, background document prepared for the Statistical Commission at its thirty-eighth session in 2007, available from http://unstats .un.org/unsd/statcom/sc2007 .htm.  === ires-2018-page-145.pdf === 132 International Recommendations for Energy Statistics (IRES) (d) Passive confidentiality be considered an option. Passive confidentiality occurs when data are made confidential only at the request of the concerned economic entity and the statistical authority finds the request justified based on the adopted confidentiality rules; (e) Proposals be formulated for including in confidentiality rules the provision that data can be disseminated if this does not entail excessive damage to the concerned entity. This implies, consequently, that the rules to determine whether or not “excessive damage” might take place are clearly defined and publicly available. C. Reference period and dissemination timetable 10.16. Reference period. It is recommended that countries make their energy data available on a calendar period basis compatible with the practice adopted by the statistical authority of the compiling country in other areas of statistics, preferably according to the Gregorian calendar and consistent with the recommendations set out in this publication. For international comparability, countries that use the fiscal year should undertake efforts to report annual data according to the Gregorian calendar. 10.17. Data dissemination timetable. In producing statistical information, there is usually a trade-off between the timeliness with which the information is prepared and the accuracy and level of detail of the published data. A crucial factor, therefore, in maintaining good relations between producers of energy statistics and the user community is developing and adhering to an appropriate release schedule. It is recommended that countries announce in advance the precise dates on which various series of energy statistics will be released. This advance release schedule should be posted at the beginning of each year on the website of the national agency responsible for the dissemination of the official energy statistics. 10.18. The most important elements that should be taken into account in determining the compilation and release schedule of energy statistics include: (a) The timing of the collection of initial data by various source agencies; (b) The extent to which data derived from the major data sources are subject to revisions; (c) The timing of preparation of important national economic policy documents that need energy statistics as inputs; and (d) The mode(s) of data dissemination (press release, online access, or hard copy). 10.19. Timeliness is the amount of time between the end of the reference period to which the data pertain, and the date on which the data are released. The timeliness of the release of monthly, quarterly and annual energy statistics varies greatly from country to country, mainly reflecting different perspectives on timeliness, reliability, accuracy and trade-offs between them, but also the differences in available resources and in the efficiency and effectiveness of the statistical production process. From the user perspective, the value of energy data increases significantly when they are released with the shortest possible delay. Countries should undertake systematic efforts to comply with this user demand. However, taking into account both policy needs and prevailing data compilation practices, countries are encouraged to: (a) Release their monthly data (e.g., on totals of energy production, stocks and stock changes), within two calendar months after the end of the reference month, at least at the most aggregated level; (b) Release their quarterly data within three calendar months after the end of the reference quarter; and (c) Release their annual data within fifteen calendar months after the end of the reference year.  === ires-2018-page-146.pdf === 133 Dissemination 10.20. The early release of provisional estimates within one calendar month for monthly data on specific flows and products and within nine to twelve calendar months for annual data is encouraged, provided countries are capable of doing this. 10.21. If countries use additional information for the compilation of annual energy statistics, the data for the fourth quarter (or for the twelfth calendar month) should be compiled and disseminated in their own right and not be derived as the difference between the annual totals and the sum for the first three quarters (or eleven calendar months) in order to provide undistorted data for all months and quarters. D. Data revision 10.22. Revisions are an important part of the compilation of energy statistics. While the compilation and dissemination of provisional data often improve the timeliness of energy statistics and its relevance, the provisional data should be revised when new and more accurate information becomes available. Such practice is recommended if countries can ensure consistency between provisional and final data. Although, in general, repeated revisions may be perceived as reflecting negatively on the reliability of official energy statistics, an attempt to avoid this by producing accurate but untimely data will ultimately fail to satisfy users’ needs. Revisions affect both annual and short-term energy statistics but they are often more significant for short-term data. 10.23. In general, two types of revisions are distinguished: (a) routine, normal or concurrent revisions that are part of the regular statistical production process and which aim to incorporate new or updated data or to correct data or compilation errors; and (b) major or special revisions that are not part of the regular revision schedule and which are conducted in order to incorporate major changes in concepts, definitions, classifications and changes in data sources. 10.24. With respect to routine revisions, it is recommended that countries develop a revision policy that is synchronized with the release calendar. The description of such a policy should be made publicly available. Agencies responsible for official energy statistics may decide to carry out a special revision, in addition to the normal statistical data revisions, for the purpose of reassessing the data or investigating in depth some new economic structures. Such revisions are carried out at longer, irregular intervals. Often, they may require changes in the time series going as far back as its beginning to retain methodological consistency. It is recommended that these revisions should be subject to prior notification to users to explain why revisions are necessary and to provide information on their possible impact on the released outputs. 10.25. Countries are encouraged to develop a revision policy for energy statistics that is carefully managed and well coordinated with other areas of statistics. That policy should be aimed at providing users with the information necessary for coping with revisions in a systematic manner. The absence of coordination and planning of revisions is considered a quality problem by users. Essential features of a well-established revision policy are predetermined release and revision schedules, reasonable stability from year to year, openness, advance notice of reasons and effects, easy access to sufficiently long time series of revised data, as well as adequate documentation of revisions included in statistical publications and databases. A sound revision policy is recognized as an important aspect of good governance in statistics, as it will not only help the national users of the data but will also promote international consistency.79 The future Energy Statistics Compilers Manual will provide detailed information on good practices in revision policy. 79 For examples of good practices, see Organisation for Economic Co-operation and Development, Data and Metadata Reporting and Presentation Handbook (Paris, 2007), chapter 7.  === ires-2018-page-147.pdf === 134 International Recommendations for Energy Statistics (IRES) E. Dissemination formats 10.26. A key to the usefulness of energy statistics is the availability of data, and hence their broad dissemination. Data can be disseminated both electronically and in paper publications. It is recommended that energy statistics be made available electronically, but countries are encouraged to choose the dissemination format that best suits their users’ needs. For example, press releases of energy statistics must be disseminated in ways that facilitate re-dissemination by mass media; and more comprehensive or detailed statistics need to be disseminated in electronic and/or paper formats. Regular data dissemination should satisfy most, if not all user needs, and customized data sets would be provided only in exceptional cases. It is advisable that countries ensure that users are clearly made aware of the procedures and options for obtaining the required data. 80 For further details on data and metadata reporting, see Organisation for Economic Co-operation and Development, Data and Metadata Reporting and Presentation Handbook (Paris, 2007). 81 The SDMX technical standards and content oriented guidelines can provide common formats and nomenclatures for exchange and sharing of statistical data and metadata using modern technology. The dissemination of national data and metadata using web technology and SDMX standards is encouraged as a means to reduce the international reporting burden and to increase the efficiency of the international data exchange. For additional information on SDMX, see https://sdmx.org. 10.27. Dissemination of metadata. The provision of adequate metadata and quality assessments of energy statistics is as important to users as the provision of data itself. Countries are encouraged to harmonize their data with international standards, follow the recommendations provided in chapter IX on data quality assurance and metadata for energy statistics, and develop and disseminate metadata in accordance with the recommendations provided. Countries might wish to consider developing different levels of detail of metadata to facilitate access and use.80 F. International reporting 10.28. It is recommended that countries disseminate their energy statistics internationally as soon as they become available to national users and without additional restrictions. To ensure a speedy and accurate data transfer to international and regional organizations, it is recommended that countries use the SDMX 81 format in the exchange and sharing of their data.