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Illustrata Deep Indexing: About

A guide to all aspects of searching, finding and using Illustrata Deep Indexing on the ProQuest Platform.

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Databases with Illustrata Deep Indexing - Natural Sciences

Databases with Illustrata Deep Indexing - Health & Medicine

Databases with Illustrata Deep Indexing - Science & Technology

Databases with Illustrata Deep Indexing - Social Sciences

 

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What is Illustrata Deep Indexing?

ProQuest IllustrataTM deep indexing is the innovative process by which ProQuest indexes the vital research data within published tables and figures, data that are often invisible to traditional bibliographic searches. Deep indexing categorizes the data variables and other content represented in tables, maps, photographs and other figures and allows efficient, precise and relevant retrieval, leading the researcher to the right choice of full text.

Why do we need Deep Indexing?

The rationale behind deep indexing is that the figures and tables represent the distilled essence of research.  By indexing representations of data, researchers can:

  1. Perform highly-focused searches, quickly – the user can quickly establish the relevance of an article to their research
  2. Find information that is otherwise hidden: Tables and graphs are very often invisible in traditional search environments
  3. Respond to the growing need for data: Tables and figures embedded within scholarly articles are often the distilled essence of the research – the closest thing to the raw datasets

Deep Indexing Process

Step 1.

Acquisition of Full Text article from relevant journal chosen according to the selection criteria. See ‘selection criteria’ box opposite for further details. Full Text would primarily be in hard copy or PDF format.

Step 2.

Image extraction is performed and the attribution is added to the image. Figure and Table captions as well as text referring to the image within the body text of the article are also extracted.

Step 3.

Complete citation metadata is collected for each table and figure: Author, Year, Title, Publication, Issue and page(s). 

Step 4.

Comprehensive Indexing is allocated via a combination of automatic and manual indexing. In addition to categorizing the format of each figure (e.g. scatter plot, line graph, and so on), ProQuest assigns subject, geographic, statistical and taxonomic descriptor terms, as appropriate. We also ensure the figure has the document type 'indexed image' applied to distinguish this from an article record.

Step 5.

All metadata components are compiled: article metadata, table/figure metadata, and the extracted image(s) before being loaded onto the ProQuest platform. 

 

Selection Criteria

Once a subject area has been broadly defined for example Natural Sciences, Social Sciences, Technology, or Health & Medicine the most important* academic journals matching the subject scope are identified and prioritized for inclusion. Other document types, such as monographs, will be added to ProQuest Deep Indexing as their additional value is evaluated.  Subject expertise of in-house editors, quantitative rankings and customer input are all used to construct the source list.  Product managers and sales staff are also key in the selection process. 

*”Most important” reflects the value to the researcher as defined as objectively as possible.