|Vanevert, F - UNIVERSITY OF MINNESOTA|
|Spaans, E - EARTH COSTA RICA|
|Krieger, S - UNIVERSITY OF MINNESOTA|
|Carlis, J - UNIVERSITY OF MINNESOTA|
Submitted to: Agronomy Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: October 20, 1998
Publication Date: N/A
Interpretive Summary: Field researchers in the agricultural sciences have always struggled with the problem of data storage and retrieval. Typically information from experiments resides in some combination of field notebooks, computer files, and human memory Subsequent retrieval for analysis and interpretation is often cumbersome, particularly as time passes, and often information is lost. Also, it is difficult to link data with auxiliary information, such as descriptions of equipment and sensors, sensor calibration history, and site characteristics Modern database hardware and software has the potential to solve these problems. We used data modeling methods, developed in the computer science field, to systematically design a database for the storage of data from agro-ecological experiments. It provides a formal way to preserve all relevant information from such experiments, and we describe in detail how that information is stored and organized. The resulting database will be useful to researchers in many areas of the agricultural and environmental sciences for storing and retrieving data.
Technical Abstract: Data from agro-ecological experiments are typically stored in a collection of minimally documented computer files, with additional information entered into field or lab books. As a result of this fragmentation of data and lack of proper documentation, information may be lost and data manipulation is generally cumbersome, error-prone and difficult to automate. Modern database technology has the potential to resolve these issues. Storing experiment data in a database solves the problem of fragmentation because all data are in the database; the problem of documentation is solved by making the relations between different items of information explicit during the design of the database; and the problem of manipulation is solved by the powerful query languages available with modern database management systems. As a first step in the construction of a generally applicable database for use in agro-ecological research, we used a formal method to design a data model that explicitly describes the types of information ( entities') one may want to remember about experiments and the relationships between these entities. The data model described here consists of 40 entities and 56 relationships. The entities are classified in the following five categories: (1) measurements; (2) equipment used to make measurements; (3) objects on which measurements are made; (4) statistical design of experiments; and (5) field operations. We describe in detail how the information from several common types of measurements is stored using the proposed data model and conclude that the data model adequately describes the information that scientists in agro-ecological disciplines need to remember about their experiments.