Ecologists increasingly use the Internet to exchange digital resources (Figure 1). The term digital resource encompasses computer models, algorithms, and software as well as data, information, and knowledge. These latter three are concepts defined differently across fields. For ecologists, data typically are the measurements or observations determined through direct study, as in a controlled experiment, a field survey, or minor
Grouped and processed
Figure 1 Digital resources. Digital resources include a wide variety of objects that range from raw and unprocessed to meaningfully interpreted, grouped, and highly processed forms. Column A shows objects relating to ecological data. Column B shows objects typically associated with libraries. Column C shows objects created by ecological modelers and developers.
manipulation of other data. Information is produced when data are placed into context (such as being part of a data set or set of experiments, particularly when designed to answer hypotheses) or manipulated. In an experiment one collects data, then transforms or combines it for analysis or aggregation in order to test hypotheses. Both data and information may be stored and manipulated digitally in databases, though ecologists often use spreadsheets for this purpose. Knowledge is the result of interpreting or synthesizing information; it is the conclusion of the hypothesis-testing process. Ecological knowledge is largely found in the scientific literature as publications; however, it is also possible to store knowledge in knowledge bases, analogous to databases. Identification keys or guides used or created by ecologists fall into the knowledge category.
Ecological data may consist of measurements or observations of individual organisms or specimens (often termed biodiversity data), measurements of their environment, or measurements of temporal processes. Some of the ecological data are geospatial, making reference to specific locations on the Earth. Ecological information similarly spans scales, as the context for data can range from a single population to all the ecosystems on Earth.
Metadata describes the context of the data or information or knowledge, such as its source, experimental details, scope, and provenance. Thus a data set, a publication, and a database can all have metadata. Algorithms, models, and software applications also have metadata.
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