Slicing and Dicing a Linguistic Data Cube

Background: Using A Data Cube To Integrate Complex Sets Of Linguistic Data

The clauses constituting a text can be analysed linguistically in various ways depending on the chosen perspective of a specific researcher. These different analytical perspectives regarding a collection of clauses can be integrated into a paper-based medium as a series of two-dimensional tables, where each table represents one clause and its multi-dimensional analysis.

This concept can be explained with a simplified grammatical paradigm and a very small micro-text consisting of only three sentences (e.g. Gen. 1:1a, 4c and 5a)¹:

• •

  Bre$it bara elohim et ha$amayim ve’et ha’arets (in the beginning God created the heaven and the earth)

• •

  Vayavdel elohim ben ha’or uven haxo$ex (and God separated the light and the darkness)

• •

  Vayiqra elohim la’or yom (and God called the light day)²

  • An interlinear multi-dimensional analysis of this text can be done as a series of tables (see Table 1).Table 1.

    A series of three two-dimensional tables, each containing a multi-dimensional linguistic analysis of one clause

    Key Terms in this Chapter

    Clause Cube: A clause cube is a three-dimensional data structure that integrates related linguistic data from various language modules.

    Data Warehousing: Data warehousing is the collection, cleaning and reformatting of large amounts of existing data into complex, multi-dimensional data structures, in order to facilitate data mining and exploration (finding patterns and trends hidden within the data). In a data warehouse of linguistic data (e.g. a clause cube) the analyses of various language modules are consolidated in one data structure in order to facilitate the exploration of patterns in and across the interrelated levels.

    Data Cube: A data cube is a multi-dimensional data structure that integrates related data.

    Rotation: Rotation refers to the presentation of various sides or views of a data cube. With reference to a clause cube it refers to the data shown on the “external” sides of the data structure.

    OLAP: On-line analytical processing refers to interactive computer processing to analyse data that has been stored in a database or data warehouse to reveal different and multi-dimensional views (Connolly & Begg, 2005, p. 1205). With reference to a clause cube it pertains to the advanced processing and comparison of linguistic data collected from various language modules.

    Dicing: Dicing may be used as a synonym for rotation, but with reference to a clause cube it refers to the extraction of detailed data “hidden” within the cube.

    Slicing: Slicing refers to the extraction of a subset of data stored in a three-dimensional data cube. With reference to a clause cube a slice may refer, for example, to one clause’s multi-modular analysis represented as a two-dimensional table.

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