Data Intensive Systems

Given the scale of today’s data sets and a seemingly insatiable demand to collect even more, organisations must turn to new approaches and new technologies for data solutions.

METHODS AND TECHNOLOGIES
Tackling the challenges in data intensive systems involves a mixture of methods and technologies. Development of appropriate semantic web and digital repositories, integrating and linking data from different sources, using appropriate data standards and semantics are all essential. Large volumes of data can also be tackled through the use of distributed computing methods such as clouds and grid-based systems.

KEY INDUSTRY COLLABORATIONS
We were a partner in a long-term, large-scale research programme funded by the National Science Foundation in the USA, to develop a Scientific Environment for Ecological Knowledge (SEEK). Our research helped identify a problem caused by the ambiguity of biological names which was exacerbated in a cyberinfrastruture. We addressed the problem using a 'concept' rather than 'name' approach for identifiers, and developed a community-wide data standard for interchanging taxonomic information. This became the TCS standard adopted by the International Biodiversity Standards Community and implemented in global tools and databases.