The Data-Driven Innovation initiative has funded the Development of Automated Text Analytics Tool for Extracting & Summarising Evidence from Veterinary Science Publications.
The solution will aid Bill & Melinda Gates Foundation (BMGF), USAID, Department for International Development (DFID) and other international donors in the adoption of data science techniques focused on accessing data in hard to reach places that will improve decision-making for targeting aid. Extracting information from academic publication is vital to understand the livestock disease landscape in Sub-Saharan Africa.
Supporting Evidence-Based Interventions (SEBI) Program at The Royal (Dick) School of Veterinary Studies, Bayes Centre and School of Informatics will work together to develop a new Data-Driven Innovation solution that could save up to 15 years’ worth of research time. According to Dr Karen Smyth, deputy director of the SEBI Programme, this solution has the potential to massively improve the quality and efficiency of researchers’ work. Currently, it takes 3 months for a researcher to extract information and build a report on relevant livestock disease data for just one country. With the proposed tool, they could extract and analyse data from 61 countries within the same timeframe.
Bayes Centre will work with researchers from SEBI, The Royal (Dick) School of Veterinary Sciences Studies to define the exact requirements so that the solution can be easily scaled across multiple projects. SEBI researchers will also work with text analytics experts from The School of Informatics to translate the text analytics requirements into an automated algorithmic solution.