Statistical Scalability for Streaming Data

Statistical Scalability for Streaming Data's image
Created: 2018-06-22 09:43
Institution: Isaac Newton Institute for Mathematical Sciences
Description: The profusion of sensor-based technologies in research and industrial systems is having a major influence on our ability to derive real-time insight and understanding about the world around us. However, this deluge of data streams also brings with it significant statistical challenge.

In the past, there has been a tendency to focus purely on algorithmic scalability. However, increasingly we find new statistical challenges arising, requiring novel solutions. For example, the statistical analysis of data streams can involve computational and memory constraints due to a need to process data at source on limited hardware. An alternative challenge can arise with the problem of synthesizing information across multiple related streams, such as those observed in digital networks. Research is therefore needed to find more robust and effective methods for scaling data and, in particular, streaming data.

This workshop is part of the six month programme at the Isaac Newton Institute (INI) on Statistical Scalability. It follows on from a highly successful knowledge exchange workshop in February which focused on Big Data and the role of statistical scalability..


Aims and Objectives
Challenges in streaming data arise in numerous fields – consumer products, financial transactions, computer network traffic, transport and communications networks and energy systems are just some of them. As with statistical scaling generally, this requires an integrated approach.

This knowledge exchange event by the Turing Gateway to Mathematics will harness expertise from the research being undertaken as part of the INI Statistical Scalability Research Programme. It will also highlight experience, expertise and challenges from a number of key stakeholders from the following areas:

Exploration and Geology
Energy and Environment
Communications
The problems faced can often be generic and so have relevance to numerous other sectors and end user applications. Additionally, real applications of streaming data involve specialist streaming infrastructure, hardware and software. It is therefore envisaged that this event will be of interest to a wide audience including those working in multiple business and industrial sectors, Government and the public sector.
 

Media items

This collection contains 5 media items.

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Media items

5G Grand Research Challenges

   18 views

Wang, N
Thursday 21st June 2018 - 16:00 to 16:30

Collection: Statistical Scalability for Streaming Data

Institution: Isaac Newton Institute for Mathematical Sciences

Created: Fri 22 Jun 2018


Causality and Streaming Data

   7 views

Peters, J
Thursday 21st June 2018 - 10:50 to 11:30

Collection: Statistical Scalability for Streaming Data

Institution: Isaac Newton Institute for Mathematical Sciences

Created: Fri 22 Jun 2018


Future Challenges for Data Analytics for Energy Management

   9 views

Goude, Y
Thursday 21st June 2018 - 14:00 to 14:30

Collection: Statistical Scalability for Streaming Data

Institution: Isaac Newton Institute for Mathematical Sciences

Created: Fri 22 Jun 2018


Real-time Monitoring of the Underground for Researchers, Industry and the Public

   8 views

Stephenson, M
Carl Watson, C
Thursday 21st June 2018 - 12:20 to 12:50

Collection: Statistical Scalability for Streaming Data

Institution: Isaac Newton Institute for Mathematical Sciences

Created: Fri 22 Jun 2018