Abstract:
INTRODUCTION : Digital text collections are increasingly being used. Various tools have been developed to allow researchers to explore such collections. Enhanced retrieval will be possible if texts are encoded with granular metadata.
METHOD : A selection of tools used to explore digital text collections was evaluated to determine to what extent they allow for the retrieval of words or phrases with specific attributes.
ANALYSIS : Tools were evaluated according to the metadata that are available in the data, the search options in the tool, how the results are displayed, and the expertise required to use the tool.
RESULTS : Many tools with powerful functions have been developed. However, there are limitations. It is not possible to search according to semantics or in-text bibliographic metadata. Analysis of the tools revealed that there are limited options to combine multiple levels of metadata and typically, without some programming expertise or knowledge of the structure and encoding of data, researchers cannot currently retrieve words or phrases with specific attributes from digital text collections.
CONCLUSION : Granular metadata should be identified, and tools that can utilise these metadata to enable the retrieval of words or phrases with specific attributes in an intuitive manner should be developed.
