Populous was used for creating a Kidney and Urinary Pathway Knowledgebase (KUPKB) as a part of the e-LICO project by Simon Jupp (EBI), Robert Stevens (University of Manchester), Julie Klein and Joost Schanstra (INSERM Toulouse).

The Kidney and Urinary Pathway Ontology (KUPO) need to be extended to include more kidney cells that were not in the Cell Type Ontology. One of the collaborators of the project and a kidney specialists was not and would not be an OWL or Protégé user – even the template of axioms to fill in was supplied. This is why spreadsheets were used as a way of collecting the classes that go into the predefined framework of properties. The goal for the KUPKB was to describe the anatomical location of the cells and the biological processes that they fostered. This is a simple template to put in a spreadsheet. However, it leaves the problem of which classes to put into the spreadsheet’s cells as users may have to go back and forth to the GO (or whatever) to choose cells, transcribe or cut-and-paste the ID or just make up terms as all this is too much like hard work.

This is where Populous comes in; it supports the scenario above, but puts menus in place that have the appropriate terms from the “supporting” ontologies in place. Populous also has support for OPPL, the Ontology Pre-processing Language, that takes rows from the spreadsheet, creates the axioms and squirts them into the growing ontology via the OWL API.

A mixture of OWL and RDF based technologies were used to create a resource for KUP biologists to query across many levels from gross KUP anatomy through cells to cell components, gene products and genes. KUPKB includes diseases and experiments (metabolomic, transcriptomic, proteomic) on various aspects of the KUP field. Instead of using use SPRQL in order to exploit the KUPKB the iKUP browser was build. The browser is a GWT Web application for browsing and querying KUPKB.

The steps to create KUPKB using Populous involved:
1. Making a KUP ontology (KUPO) by gluing together various extant ontologies that cover the domain – Gross anatomy; cells; gene products; attributes of gene products; disease; descriptions of investigations and so on.
2. Joining the ontologies together in order to sufficiently describe our domain entities to ask the questions we want to ask.
3. Adding some bits that are missing.
4. Populate the schema formed by the KUPO with lots of “instance” data to form a KUP knowledgebase, the KUPKB.

The creation of KUPKB was described in a Journal of Biomedical Semantics paper: Jupp, S.; Klein, J.; Schanstra, J. & Stevens, R. Developing a kidney and urinary pathway knowledge base
Journal of biomedical semantics, BioMed Central, 2011, 2, S7