Partnerships

The Institute for Data Science (IDAS) primarily serves as a catalyst for academic research excellence. However, the Institute actively cultivates public-private collaborations that generate mutual benefits through complementary expertise exchange. These strategic partnerships are structured around three core motifs: 

Analysis and Prototyping of Advanced Data Science Infrastructure 

Current practice across both commercial and academic sectors typically defaults to procuring standardised data science infrastructure without comprehensive market assessment or requirements analysis. IDAS offers specialized expertise and an environment to: 

1. Conduct systematic horizon scanning of evolving data science technologies; 
2. Perform comparative evaluations of emerging computational architectures; 
3. Identify customised solutions optimised for specific organizational requirements. 

Professional Development for Technical Specialists 

The prevalent reliance on commercial software frameworks and cloud-based computational resources creates dependencies that impact both business and academic institutions. IDAS is establishing a comprehensive skills development program designed to: 

1. Train the next generation of platform architects and software specialists 
2. Develop expertise in mission-critical information technology systems 
3. Reduce organizational dependencies on external service providers 

Due to these activities, we enable institutions to internalise essential computational capabilities and to optimize operational efficiency and cost-effectiveness of data infrastructure. 

Advanced Problem-Solving for Methodological Challenges

IDAS convenes Durham's multidisciplinary expertise to address fundamental challenges in data science that constitute current or anticipated barriers to progress. Together with our members, we are interested in:

• Identifying systemic limitations in existing methodological frameworks 

• Developing innovative approaches through interdisciplinary collaboration  

• Creating solutions applicable across academic and industrial contexts 

IDAS wants to facilitate knowledge transfer between academic research and industrial application, ensuring that advancements in data science methodologies deliver tangible benefits across sectors. As the institute brings together yet does not own domain expertise, it often serves as a catalyst or enabler establishing new direct links into departments and other research consortia. 

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