University of Leicester

Visualising the hidden world of internal research papers.

Nebuli – University of Leicester Library

Nebuli applied augmented intelligence to unearth University of Leicester‘s hidden world of knowledge within their library’s research papers and research datasets.

Key services

  • Deep data mining.

  • Knowledge discovery.

  • Data pre-processing.

  • Data segmentation.

  • Data visualisation.

Market

  • Academic Research.

Nebuli - University of Leicester Case Study

Since Nebuli is independent of any data formats, platforms and languages — allowing easier and faster cross-disciplinary and cross-regional data integrations and interoperability – it allowed the University of Leicester (UoL) Library team to facilitate the revelation of hidden knowledge and undiscovered trends within their research papers and Excel sheets of citations.

Nebuli helped the UoL’s library to visualise the hidden world of their internal research papers, facilitating new interdisciplinary and interdepartmental R&D collaborations.

Nebuli’s Key Role:
  • Data preprocessing (cleansing and convergence) of the library’s unlabelled database – generated from 13,000 preselected research papers.

  • Data segmentation, with a particular focus on identifying communities within the same database. This process allowed the university to identify and connect researchers and departments with similar subject interests, including those working in seemingly unrelated research.

  • Applying Nebuli’s smart search API for full-text and abstracts across similar documents, generating a unique measure of similarity.

  • Providing users with augmented intelligence tools that evaluate the quality of the defined groups, generating keywords that represent the content of each group.

Outcomes and Objectives:

Nebuli helped the UoL’s library to visualise the hidden world of their internal research papers, facilitating new interdisciplinary and interdepartmental R&D collaborations and identification of new funding opportunities.

3D representation (generated by UoL’s internal systems) of Nebuli’s advanced data segmentation capabilities, combining such parameters as areas of interest, time tendency/trends, authors’ contributions, institutions’ contributions, citation scoring and much more.

In addition, this model was combined with downloaded libraries from PubMed (comprising over 30 million citations) and are currently working on indexing further open online libraries, such as Google Scholar and Archive.org.

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