It is often desirable to attach specific attributes to utterances. For example, valid section breaks are - and. They start with three dashes and a smaller-than sign, followed by an identifier for the section break, and end with a greater-than sign and three dashes. Section breaks occur between two utterances, separated from those utterances by newline characters. The other is using sections: sections segment the data. One is using persistent class instance identifiers, which will be discussed below. There are two approaches to represent meaningful grouping of utterances. A source can be seen as a logistical necessity, but sources do not have meaning: in the ROCK standard, whether two utterances are in the same source or not is not relevant. It is also possible to split up data over several sources, or combine data from multiple data collections in one source. For example, different interview transcripts may be stored in different sources (i.e. different plain-text files). Often, utterances will be sentences, but not necessarily.Ī source will often, but not necessarily, contain data that is somehow related. In the ROCK standard, utterances are separated by a newline character (“ \n”), which means that every line in a source is an utterance. These data are segmented into the smallest codable unit which is called an utterance. Sources are plain-text files that contain qualitative data. These files normally follow the conventions set out in this chapter. Qualitative data files that implement the ROCK standard can be recognized by their extension. In this chapter, the vocabulary explained in Chapter 10 is used to describe the ROCK standard. In addition, this enables all existing qualitative data analysis programs to import data files in this format and to export to this format. This open standard enables development of programs or scripts to perform specific functions that are not yet present in any of the existing applications that support the ROCK format. In other words, coded transcripts should be readable as is. The aim of the ROCK is to provide a standard that enables researchers to exchange data and analyses in a format that is readable even without running any specific software. It follows the principles that also guided the development of the Markdown and YAML standards: prioritizing human-readability while retaining machine-readability. The ROCK standard has been developed as an open standard for qualitative data analysis.
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