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Introduction
Efficient interchange of data among researchers, especially for use in simulation models and other decision support tools, requires use of a common vocabulary and strategy for organizing data. The agricultural research community increasingly encounters research problems that require interdisciplinary collaboration. Physiologists and molecular biologists work together to develop a better understanding of the genetic control of productivity-related traits. Agronomists, soil scientists and irrigation specialists combine efforts in order to increase the efficiency of crop water use. In such collaborations, ready data interchange is essential. Genomic data are widely available through publicly accessible databases (Blanchard, 2004). Daily weather records and soil profile data are increasingly available through the Internet. The International Research Institute for Climate Prediction recently developed two daily weather data download options in ICASA format that can be accessed from the ICASA web site (www.icasa.net/weather_data). Efforts are also underway to make the “World Inventory of Soil Emission Potentials” (WISE) database developed by the International Soil Reference and Information Centre in The Netherlands available for crop model applications. Field research data, however, are seldom available through public databases. Although there have been various initiatives to develop systems for reporting and storing data from field research, e.g., van Evert et al. (1999a; 1999b); Bostick et al. (2004), to date, no system is widely accepted as a standard.
Among the largest sustained effort to promote the use of standards in relation to field research has been that of the International Consortium for Agricultural Systems Analysis (ICASA), and one of its predecessors, the International Benchmark Soils Network for Agrotechnology Transfer (IBSNAT). As early as 1983, the IBSNAT project developed data standards to be used both to document experiments and to provide input for models or other software tools (Uehara and Tsuji, 1998). The standards and their implementation in ASCII files facilitated interactions among experimenters and modellers (Hunt et al., 1994; Jones et al., 1994). They were extensively used by experimenters and modellers using the DSSAT system (Tsuji et al., 1994) and were adopted by the Global Change and Terrestrial Ecosystem project (GCTE) for use in documenting experiments and regional yield investigations (GCTE, 1996). Within GCTE, the standards greatly assisted model comparisons (Goudriaan, 1996; Jamieson et al., 1998; White et al., 2003) that led to model improvements. To promote actual interchange of data, ICASA has also developed the ICASA Data Exchange (IDE; www.icasa.net/data_exchange/) where ICASA members can store and share experimental data.
Experience with the IBSNAT standards and files showed that they contained ambiguities and lacked fields to characterize certain crops and management practices. Members of ICASA and other organizations thus defined a revised set of standards that were intended to be unambiguous, easily processed by a broad range of software tools, and more inclusive of crops and production practices (Hunt et al., 2001). Use of this initial draft of the ICASA standards and associated ASCII files highlighted further issues that needed attention before wider use, as for example in the DSSAT software, could be promoted with confidence. Furthermore, diverse stakeholders requested that the standards be defined not only for the “flat” ASCII file format but also for formats such as relational databases and eXtensible Markup Language (XML). Thus, the ICASA standards have been reformulated, with greater emphasis on standardizing vocabularies and establishing relations among variables. This somewhat parallels efforts to develop data ontologies in other branches of plant and agricultural sciences (The Plant Ontology Consortium, 2002; FAO, 2004).
The goal of the ICASA standards, following the thrust of the earlier IBSNAT standards, is to provide a reliable, portable, and flexible structure both for documenting field experiments (or their equivalents in greenhouses or growth chambers) and for specifying realistic conditions for running dynamic simulation models. For documentation, it is desirable to have sufficient detail on weather, soil, crop cultivars, weeds, diseases, pests, and crop management to permit a full reproduction of the experiment and to conserve any information measured or noted during or at the end of the experiment. Often, the variables defined within the standards are taken as indicating the required degree of detail, the “minimum dataset” (Nix, 1984), for experimental documentation. We emphasize, however, that because of the diversity of experiments, the list of variables documented within the current standards should not be interpreted as a “minimum dataset”. Indeed, since the standards can be extended to accommodate new variables, and the implementation files contracted by omitting variables, the standards are better viewed as describing a “flexible dataset” concept that should be moulded to the needs of specific lines of research or decision support.
This document provides an overview of the most recent revision, which represents the ICASA Version 1.0 standards. It presents various examples as implemented in ASCII file format and briefly discusses progress in implementing the standards in databases and XML. A number of ASCII implementations of the new standards have been developed and will be used in the next official release of the DSSAT software (Jones et al., 2003; Hoogenboom et al., 2004). The standards are expected to evolve over time, mainly through addition of new variables. Updates to the definitions will be posted at the ICASA web site, www.icasa.net/standards/.