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ADMIRE

Advanced Data Mining and Integration Research for Europe

Towards Optimising Distributed Data Streaming Graphs using Parallel Streams

C. S. Liew, Atkinson, M. P., van Hemert, J., and Han, L., Towards Optimising Distributed Data Streaming Graphs using Parallel Streams, in Data Intensive Distributed Computing (DIDC'10), in conjunction with the 19th International Symposium on High Performance Distributed Computing, Chicago, Illinois, 2010, pp. 725-736.

Runoff prediction from a Hydrologic Spatio-Temporal Database

Student: 
Charalampos Sfyrakis
Grade: 
first

Present day instrumentation networks in rivers provide huge quantities of multi-dimensional data. Although there are numerous machine learning tools that can extract trends, find patterns and predict future states given some data, it is crucial to properly optimize these techniques according to the semantic content of the data. Hydrology is a data immense science, which requires efficient mining of trajectories of measurements taken at different time points and positions.

Project status: 
Finished
Degree level: 
MSc
Background: 
data mining
Supervisors @ NeSC: 
Subject areas: 
e-Science
Machine Learning/Neural Networks/Connectionist Computing
Projects: 
Student project type: 

Prof Peter Brezany

Affiliation: 
University of Vienna, Austra

to work on the Data Mining and Integration Language for the ADMIRE project.

Dates: 
3 Aug 2008 to 15 Aug 2008
Projects: 

Mr Alexander Wöhrer

Affiliation: 
University of Vienna, Austra

to work on the Data Mining and Integration language for the ADMIRE project

Dates: 
14 Aug 2008 to 19 Aug 2009
Projects: 

Mr Carlos Buil Aranda

Affiliation: 
Universidad Politécnica de Madrid

Carlos Buil Aranda from the Ontology Engineering Group will visit us to work on semantic registries for the ADMIRE project.

Dates: 
21 Jul 2009 to 30 Sep 2009
Projects: 

Dr Javier Fernández Muñoz

Affiliation: 
Universidad Carlos III de Madrid, Spain

Javier will vist on the HPC-Europa2 Transnational Access programme. His expertise is in performance modelling of distributed systems and he will be working with the ADMIRE project in combination with the architecture simulator from the group in Spain.

Dates: 
15 Feb 2009 to 18 Apr 2009
Projects: 

Optimising Data-Streaming Elements in Distributed Data Mining

Principle goal: To evaluate existing data streaming implementation, formulate model to predict streaming performance corresponding to buffering strategy and then optimise data streaming with dynamical buffering implementation.

Project status: 
Finished
Degree level: 
MSc
Background: 
Java programming essential. Distributed/parallel computing desirable.
Subject areas: 
Computer Architecture
Distributed Systems
Parallel Programming
Performance Modelling and Simulation
System Level Integration
Student project type: 
Projects: 
References: 
[1] M. Atkinson, P. Brezany, O. Corcho, L. Han, J. van Hemert, L. Hluchy ́, A. Hume, I. Janciak, A. Krause, and D. Snelling. ADMIRE White Paper: Motivation, Strategy, Overview and Impact. Technical Report version 0.9, ADMIRE, EPCC, University of Edinburgh, January 2009. [2] A. Jacobs. The pathologies of big data. Commun. ACM, 52(8):36–44, 2009.

Improving Data Placement Strategy in Data-intensive Computations

Student: 
Yue Ma
Grade: 
third

Principle goal: to investigate existing data placement strategies and build a decision model to improve data placement strategies in enacting data-intensive workflow.

Project status: 
Finished
Degree level: 
MSc
Background: 
Distributed/parallel computing, databases desirable. Java programming essential.
Supervisors @ NeSC: 
Subject areas: 
Computer Architecture
Distributed Systems
System Level Integration
Projects: 
References: 
[1] M. Atkinson, P. Brezany, O. Corcho, L. Han, J. van Hemert, L. Hluchy ́, A. Hume, I. Janciak, A. Krause, and D. Snelling. ADMIRE White Paper: Motivation, Strategy, Overview and Impact. Technical Report version 0.9, ADMIRE, EPCC, University of Edinburgh, January 2009. [2] T. Hey, S. Tansley, and K. T. (Editors). The Fourth Paradigm: Data-Intensive Scientific
Student project type: 

Facilitating Data Mining and Data Integration Using Parallel Pipeline Streaming

Presentation Type: 
poster

To explore, analyse and extract useful information and knowledge from massive amounts of data collected from geographically distributed sites, one has to overcome both data and computational intensive problems in distributed environments.

Date and time: 
Thursday, 10 December, 2009 - 12:30
Location: 
IEEE e-Science 2009, Oxford, UK
Projects: 

Advanced Data Mining and Integration Research for Europe

Speaker(s): 
Presentation Type: 
talk

There is a rapidly growing wealth of data. The number of sources of data is increasing, while, at the same time, the diversity, complexity and scale of these data resources are also increasing dramatically. This cornucopia of data offers much potential; a combinatorial explosion of opportunities for knowledge discovery, improved decisions and better policies. Today, most of these opportunities are not realised because composing data from multiple sources and extracting information is too difficult.

Date and time: 
Tuesday, 8 December, 2009 - 11:40
Location: 
UK e-Science All Hands Meeting 2009, Oxford, UK
Projects: 

The semantic web basics-RDF, SPARQL and OWL

NeSC Research Seminar Series
Speaker: 
Carlos Buil Aranda

This talk will give an introduction of semantic web basics: RDF, SPARQL and OWL, and then followed by a practical
showcase --- the work that I have done while visiting NeSC and EPCC at the University of Edinburgh for the last two months.

Date and time: 
Friday, 25 September, 2009 - 10:30
Length: 
45 minutes
Location: 
Cramond
Projects: 

ADMIRE mentioned in Scientific Computing

Towards a data analytic society

Felix Grant on the use of statistics in the analysis of society

Scientific Computing April/May 2008

Full story at: http://www.scientific-computing.com/features/feature.php?feature_id=192

Projects: 
Topic of this submission: 

Automating Gene Annotation Expression for Mouse Embryo

Speaker(s): 
Presentation Type: 
talk

It is of high biomedical interest to identify gene interactions and networks that are associated with developmental and physiological functions in the mouse embryo. There are now large datasets with both spatial and ontological annotation of the spatio-temporal patterns of gene-expression that provide a powerful resource to discover potential mechanisms of embryo organisation. Ontological annotation of gene expression consists of labelling images with terms from the anatomy ontology for mouse development. Current annotation is made manually by domain experts.

Date and time: 
Monday, 17 August, 2009 - 14:00
Location: 
The 6th International Conference on Advanced Data Mining and Applications (ADMA2009), Beijing China
Projects: 

Automating Gene Expression Annotation for Mouse Embryo

L. Han, van Hemert, J., Baldock, R., and Atkinson, M. P., Automating Gene Expression Annotation for Mouse Embryo, in Lecture Notes in Computer Science (Advanced Data Mining and Applications, 5th International Conference), 2009, vol. LNAI 5678, pp. 469-478.

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