Data are a key ingredient for any rating approach. In general, data are characteristics or information, usually numerical, that are collected through observation. In a most rating systems, data is a set of rating-relevant values of qualitative or quantitative variables about one or more persons or objects. To assure valid and reliable rating, each datum (singular of data) as a single value of a single variable is important.
Our workshop deals with how data is measured, collected and reported, and analyzed, whereupon it can be visualized using graphs, images or other analysis tools. We want to improve how some existing information or knowledge is represented or coded in some form suitable for better usage or processing.
Raters today make use of computers like never before. Powerful computers can produce large amounts of erroneous data or information in a short time. Garbage in, garbage out (GIGO) is the concept that flawed, or nonsense input data produces nonsense output or “garbage”. As in computer science, the GIGO concept applies to rating systems too.
Raw data (“unprocessed data”) is a collection of numbers or characters before it has been “cleaned” and corrected by researchers. Raw data needs to be corrected to remove outliers or obvious instrument or data entry errors (e.g., typos). Data processing commonly occurs by stages in a rating process, and the “processed data” from one stage may be considered the “raw data” of the next stage in a given rating approach.
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