Knowledge reference for national forest assessments - information management and data registration
2. A basic Forest Resource Assessment scenario
While section 2.1 was concerned with basic issues of data storage and quality control, section 2.2 deals with the transformation of data into information. The transformations are often the result of a demand for specific information. Meeting demands has major implications for information management.
2.2.1 Information demand and supply
The demand for forest information has changed in recent years since forest policy underwent a shift in perspective from timber production to social, economic and environmental issues (Kelatwang 2002). Many of the new information needs were recognized in Agenda 21, and have been re-evaluated in light of advances in Internet technology. In an overview of the supply and use of information for forest policy, Janz and Persson (2002) indicate that ¿[t]here are serious shortcomings in the supply and use of information needed for policy making ¿ The main weakness is failure to connect supply to demand.¿ However, even when information exists, authorities may desire that it be kept secret. Success of a Forest Information System will depend on the degree to which information needs of potential users will be satisfied (Kohl and Romisch 2000). There is a need to ensure that the information requested at the international level can realistically be supplied by countries (Holmgren and Persson 2002).
2.2.2 Information aggregation and integration
While the focus of this chapter is on computer-related aspects of information management, the organization of printed and other information may be an essential pre-cursor to computer analyses, as in the FAO FRA ¿documentation room¿ (FAO 2000a). The task of coordinating, processing, harmonizing and managing forest related databases is necessary to avoid duplication of efforts: there may be ¿little comparability between surveys performed in different years even by the same agencies and ensuring compatibility of data across varying formats, map projections, boundaries, and scales even within a country is becoming a Herculean task (FAO 2001a).¿
Information to be provided by a forest information system varies according to the purpose and the scale for which it is used; information needed on the strategic and integrative level has to be aggregated in both thematic and spatial terms (Kohl and Romisch. 2000). Adjustment factors may need to be determined, and may be based on ancillary variables such as human population change or ecological zone (FAO 1998b, FAO 1999a). These should be described in the metadata (2.1.4 above), as in the UN-ECE/FAO Temperate and Boreal Forest Resource Assessment (TBFRA) (Varjo et al. 2000). As systems of nomenclature applied in national forest resources assessments are characterized by tradition and even identically named attributes may mask different concepts and definitions, a major concern of TBFRA-2000 was the comparability of data between countries and the reliability of aggregated results (ECE 2000). Development of adjustment factors is part of the harmonization process introduced in 2.1.4 above: harmonization is the process of making reports to different instruments comparable, for example through the use of common or comparable terms and definitions, standardized units for data and common reference years (Braatz 2002). In this process, it is critical that aggregation occur at an appropriate scale (Agarwal et al. 2002). The aggregation and harmonization processes facilitate identification of information gaps (FAO 2001a). Thomson and Schmoldt (2001) discuss ethical issues of information aggregation, transformation and reporting.
FRAs are often based on some kind of synthesis based on partial data plus expert opinion (FAO 2000b). For example, experts may be used to determine adjustment factors (FAO 1998b). While expert opinion can be subject to bias and imprecision, it will generally be better than no information at all. The Delphi Technique and Convergence of Evidence are two methods of dealing with expert opinion, and the information management system should include methods of tracking these opinions. The increasing reliance on surveys of stakeholders such as indigenous peoples should also be viewed as use of expert opinion. Thomson (2000) describes an information management system relating to a questionnaire used with Canadian First Nations. The system tracks the literature basis for each question, the range of responses, the inferences drawn (and by whom), and indicators derived.