Expertise

Home/Outputs/Expertise
Expertise 2017-05-18T20:09:15+00:00

Three core research themes have been identified as the basis for the CeADAR technology centre.

The themes are necessarily broad and intended to underpin the research direction of the centre long term. Within each theme there are a few selected priority projects representing industry’s most pressing needs.

To view details on the priority projects for the first phase of the centre, please click on each theme below.

Intelligent Analytic Interfaces

The goal of this theme is to create innovative approaches and tools to aid non-analytics specialist users in exploring datasets and performing customer segmentations.  The four sub-themes are:

Ease of interaction

Goal: develop smart analytics tools to aid non- expert users in exploring datasets and performing customer segmentations that significantly improve how non-analytics experts can articulate and discover the insights they want.

Beyond the Desktop

Goal: apply / develop ground-breaking ways of interacting with large complex data sets using more natural interfaces to discover new insights.

Changing User behaviour based on Analytics

Goals: investigate how to make analytics outputs more compelling and effective by modelling and incentivising specific user behaviours; investigate the effect of different communication options.

Passive analytics

Goal: develop innovative tools and techniques to deliver results from background analytics processes in the most effective, timely, and targeted way using the most appropriate medium based on what is being communicated.

Data Management for Analytics

The main goal of this theme is to develop approaches, methods and tools to improve, simplify and reduce the effort involved in the management of data for analytics purposes. The four sub-themes are:

Reduce data management effort for analytics

Goal: develop approaches, methods and tools to improve, simplify and reduce the effort involved in the management of data for analytics.

Data validation

Goal: develop advanced analytics techniques and demonstrators to manage the validity and quality of the data being used for data analytics.

Harnessing the Power of Open Data

Goals: develop analytical approaches, methods, models, and tools to understand and improve the way open data sources are identified, validated, and, where possible, incorporated into proprietary data sources.

Data Curation (determining useful data)

Goal: use advanced analytics techniques to determine which data may be considered ‘useful’ to improve data archiving and data storage approaches.

Advanced Analytics

The goal of this theme is to create innovative approaches and tools to aid non-analytics specialist users in exploring datasets and performing customer segmentations. The five sub-themes are:

Knowledge Discovery and Insight

Goal: explore new approaches, tools and techniques to improve the ability to uncover insights from data.

Social media trending and contextualisation challenge

Goal: create techniques, tools, and methods to identify trending scenarios in social networks within a defined/relevant context linked to internal data.

Continuous analytics

Goal: develop methodologies, processes, technologies, tools, and algorithms to analyse continuous streams of data using complex analytic algorithms to report the most accurate and timely results.

Predictive Analytics

Goal: create techniques, tools, and methods to help predict the values of unknown variables in order to improve decision making.

Cognitive Computing

Goal: create new tools that can serve as solutions for humans to learn from large volumes of predominantly unstructured data.