During the research process, critical data and findings remain hidden, and researchers can spend countless hours hunting through journal articles for data specific to their needs. With traditional article-level and full-text searching of journal content, relevant data in tables is figures are hidden from view and not easily accessible. This is because specific information about tables and figures does not appear in any index—there were no indexing "hooks" in the title, abstract, or caption…until now.

Like its predecessor Illustrata: Natural Sciences, Illustrata: Technology offers groundbreaking deep indexing that pinpoints high-value tables and figures in journal articles. Through this new approach, researchers can instantly identify the findings that are critical to their specific work, and discover findings in unexpected sources. Records for each journal table or figure include a thumbnail image, caption, bibliographic details, detailed hyperlinked index terms, and subscription-sensitive article links.

Illustrata: Technology provides deep indexing that spans a wide range of subject areas including Materials Science, Aerospace, Engineering, and High Technology. And this powerful resource seamlessly integrates with the databases you currently subscribe to through the CSA Illumina platform.

Illustrata: Technology offers deep indexing for over 4.4 million images from more than 2,720 journals and is continuously growing.

Accolades for the initial module Illustrata: Natural Sciences include:

• 2008 CODiE Award Winner: Best Online Science or Technology Service
• A Library Journal Best Reference Pick of 2007
• CHOICE 2007 Outstanding Academic Title
• Ranked third in ten, just after smartphone and social networking innovations as: "…one of the most important products of the year (2007)…"—Paula Hane, Information Today

Illustrata was developed with researchers and librarians to improve the precision, efficiency, and relevance of searches. During the development of Illustrata, researchers were given access to a prototype and asked to comment on what they perceived as the potential uses and benefits of the system; such uses included:

• Gaining faster and more precise understanding of the work reported in articles by direct examination of the tables and figures
• Improving the efficiency of searching by providing more precise and smaller results sets
• Locating and retrieving data in particular formats or particular object types
• Making comparisons between their work and the work of others
• Assisting with writing of review papers, meta-analyses, proposals, and for generating hypotheses
• Supporting the transformation of practice and supporting the learning of new skills and methods, including how to effectively present results in tables, figures and graphs
• Use of objects by librarians to directly answer reference questions