Every transaction conducted in the Bitcoin network is recorded permanently and irrevocably in a public database known as the Blockchain.  By visualizing this network of highly associated data in a large scale environment we are able to accelerate algorithmic discovery of anomalous transactional patterns, with obvious applications into areas such as fraud detection.

Real time obseravtory on the different patterns of transactions that occur on the bitcoin network.

It also features some past blocks which contains relevant, unusual activity

If you want to read further about Bitcoin through a Master's student's visit, please click here. 

Please read the publication Visualizing Dynamic Bitcoin Transaction Patterns written by our researchers, here.

 

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Working with collaborators at Zhejiang University, the DSI has had access to data from a sample population of one million people. By employing various data mining and modelling techniques, researchers have been able to visualise the Chinese floating population and urbanisation over the past five years on the Data Observatory.

Results have shown that migrants to Henan have been relatively young and well educated, often from wealthy provinces like Zhejiang. After mining deeper into the data, our results indicated that more than half of these people were involved in new business start-ups, and the income of these businesses grows much faster than other cities like Beijing.

From analysing news concerning Henan over the past five years, we found that prominent terms relating to the migration to Henan Province were ‘high speed railways’, ‘business start-up policy’, ‘urbanisation’ and ‘rising strategy of central China’. It appears that the principle reasons for the young and highly-educated migrating to Henan are accessibility, business start-up oriented policies and rapid urbanisation. In turn, this has led to the province benefiting from a young and educated workforce.

The visualisation allows the presentation of this research in a format which can be easily interrogated by researchers, and communicated to non-experts. 

Interactive satellite maps, with the possibility of adding geolcated information on top of it. 

We usually show London, frequent bike paths and Imperial campuses.

This brings maps to life in the DO, getting to see which routes are faster and getting to see the areas we know from a different perspective. 

Visualisation that shows how employees in a bank moved between different departments within the company through several years. Data comprises biweekly HR record. 

This demonstration presents the open-source data management and analysis system we have been developing for future personalised medicine. The system has been used widely by numerous institutions in the biomedical research and pharmaceutical industries.

The volume, complexity and heterogeneity of data generated from biomedical research require a knowledge management infrastructure which can provide effective data sharing, integration, standardisation and analysis of biomedical data.In the DSI we have been developing an open-source data management platform to support large-scale data management and complex analytical tasks for personalised medicine in clinical applications.

The data shown in this demonstration is from the Innovative Medicines Initiative (IMI) ‘Unbiased Biomarkers in the Prediction of Disease’ (U-BIOPRED) project, which contains samples and medical information from hundreds of adults and children with severe asthma. We have been working with U-BIOPRED to create a system in which the diverse data sets can be compared in an unbiased way – deploying cutting edge analytical techniques to identify different sub-types of severe asthma. The system can select a specific patient cohort based on the chosen clinical parameters, and analyse the genetic and genomic data of the patient cohort to identify the set of genes which are most likely to cause asthma. The sequences of these genes can be further analysed and the molecular interactions among these genes in the cell can be explored in the system. The findings are expected to provide novel insights into the underlying mechanisms of asthma for each patient.

Study that shows the pulse of the Shanghai Metro in China during a day, depicting the majority of its stations. Taking data from how many people were coming in and out from the stations, they were able to visualize the pulse or flow at stations throughout the day. It also comprises a proof of concept of what is possible if a simulation model is created

Longitudinal study of how Sharing Economy (Uber, Airbnb, etc..) has risen in the last few years in the UK.nIt includes a detailed study on the demographics of the participants, together with a timeline of events leading to it.

GPS data in our mobile phones are a great source of information for insurance companies. The aim of the 'Telematics from Smartphone Data' project is to enable car manufacturers, insurers and service providers to deliver an enriched driving experience that creates loyalty and unlocks the value in vehicle. With the help of the DSI, the visualisation presented in the DO shows three user cases of how those data can be used for fraud detection, crash forensic, risk assesment and more. 

Were contents of the speeches of Trump and Clinton during their campaigns any different?

We analysed the content of Mr. Trump's and Mrs. Clinton's speeches in the lead up to the US election to see which topics the presidential candidates touched on the most.

This analysis allowed us to create a semantic fingerprint of both candidates and their topics, and to understand what are the topics each candidate talk more about.