Description

Book Synopsis
A guide to principles and methods for the management, archiving, sharing, and citing of linguistic research data, especially digital data.

Doing language science depends on collecting, transcribing, annotating, analyzing, storing, and sharing linguistic research data. This volume offers a guide to linguistic data management, engaging with current trends toward the transformation of linguistics into a more data-driven and reproducible scientific endeavor. It offers both principles and methods, presenting the conceptual foundations of linguistic data management and a series of case studies, each of which demonstrates a concrete application of abstract principles in a current practice.

In part 1, contributors bring together knowledge from information science, archiving, and data stewardship relevant to linguistic data management. Topics covered include implementation principles, archiving data, finding and using datasets, and the valuation of time and effort involve

The Open Handbook of Linguistic Data Management

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    A Hardback by Andrea L. Berez-Kroeker, Bradley McDonnell

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      Publisher: MIT Press Ltd
      Publication Date: 18/01/2022
      ISBN13: 9780262045261, 978-0262045261
      ISBN10: 0262045265
      Also in:
      Language: reference and general

      Description

      Book Synopsis
      A guide to principles and methods for the management, archiving, sharing, and citing of linguistic research data, especially digital data.

      Doing language science depends on collecting, transcribing, annotating, analyzing, storing, and sharing linguistic research data. This volume offers a guide to linguistic data management, engaging with current trends toward the transformation of linguistics into a more data-driven and reproducible scientific endeavor. It offers both principles and methods, presenting the conceptual foundations of linguistic data management and a series of case studies, each of which demonstrates a concrete application of abstract principles in a current practice.

      In part 1, contributors bring together knowledge from information science, archiving, and data stewardship relevant to linguistic data management. Topics covered include implementation principles, archiving data, finding and using datasets, and the valuation of time and effort involve

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