Edinburgh Data-Intensive Research - EFFORT

EFFORT: Earthquake and Failure Forecasting in Real Time Forecasting Model Testing Centre

Rosa.Filgueira — Fri, 31 May 2013 15:35:09 +0000

Speaker(s):

Presentation Type:

poster

PICO presentation:
Across Europe there are a large number of rock deformation laboratories, each which runs many experiments. Similarly
there are a large number of theoretical rock physicists who develop constitutive and computational models
both for rock deformation and changes in geophysical properties. Here we consider how to open up opportunities
for sharing experimental data in a way that is integrated with multiple hypothesis testing. We present a prototype
for a new forecasting model testing centre based on e-infrastructures for capturing and sharing data & models to
accelerate the Rock Physicists research.

This proposal is triggered by our work on data assimilation in the NERC EFFORT(Earthquake and Failure Forecasting
in Real Time) project, using data provided by the NERC CREEP 2 experimental project as a test case.
EFFORT is a multi-disciplinary collaboration between Geoscientists, Rock Physicists and Computer Scientist.
Brittle failure of the crust is likely to play a key role in controlling the timing of a range of geophysical hazards,
such as volcanic eruptions, yet the predictability of brittle failure is unknown. Our aim is to provide a facility for
developing and testing models to forecast brittle failure in experimental and natural data. Model testing is done in
real-time, verifiably prospective mode, in order to avoid selection biases that are possible in retrospective analyses.
The project will ultimately quantify the predictability of brittle failure, and how this predictability scales from
simple, controlled laboratory conditions to the complex, uncontrolled real world. Experimental data are collected
from controlled laboratory experiments which includes data from the UCL Laboratory and from Creep2 project
which will undertake experiments in a deep-sea laboratory. We illustrate the properties of the prototype testing
centre by streaming and analysing realistically noisy synthetic data, as an aid to generating and improving testing
methodologies in imperfect conditions. The forecasting model testing centre allows to:

1. Data transfer:
• Upload experimental data: We have developed FAST (Flexible Automated Streaming Transfer) tool
to upload data reliable and periodically from RP laboratories to the data repository. FAST allows for
setting up data transfer requirements and selects automatically the most suitable transfer protocol.
Metadata are created and stored in the data catalogue.
2. Web data access:
• Create synthetic data: The users can choose the generator and supply parameters. Each synthetic data
is automatically stored in the data repository which corresponding metadata in the data catalogue.
• Select data and models: The metadata of each data (synthetic or from laboratory) and models are welldescribed
through their respective catalogues accessible by the web portal. Searches over the metadata
are supported.
• Upload models: The users can upload their models and them will be automatically stored in the models
repository. The users have the opportunity to share their models among other users. The web portal
creates and stores the metadata of each uploaded model into the models catalogue.
• Run models and visualise results: Once a user has selected data and a model, the model is submitted
to a High Performance Computational resource, hidden the complex interaction with clusters. Their
results are displayed in accelerated time. The results of the computations are stored allowing retrieval,
inspection and aggregation.

3. Metadata and Data Storage:
• Store automatically metadata in catalogues and data, models and results in repositories.
The forecasting model testing centre proposed could be integrated into EPOS context and its expected benefits are:
• Facilities the prediction of brittle failure and its scalability to natural phenomena.
• Provides fast testing and ideas propagation.
• Increases the impact and visibility of RP and GS research.
• Provides important resources for education and training.

Attachment	Size
Rosa-PICO-EGU2013.pdf	2.76 MB

Date and time:

Monday, 8 April, 2013 - 10:00

Location:

Vienna

Web site:

Projects:

EFFORT

Research topics:

Data-intensive computing

Forecasting volcanic eruptions

David.Rodriguez — Tue, 04 Dec 2012 10:20:57 +0000

NeSC Research Seminar Series

Speaker:

Andrew Bell

Unlike earthquakes, most volcanic eruptions are preceded by clear episodes of unrest. These precursory signals are the main basis for forecasting eruptive activity, yet the quality of such forecasts are unknown. I will describe physical and empirical models for eruption forecasting and our efforts to quantify their performance. This work includes a project to test models in real-time, using data from multiple experimental facilities and volcano observatories.

Date and time:

Friday, 7 December, 2012 - 10:00

Length:

45 minutes

Location:

IF502

Projects:

EFFORT

Research topics:

Seismology

EFFORT: Earthquake and Failure Forecasting in Real Time from controlled laboratory test to volcanoes and earthquakes

Rosa.Filgueira — Fri, 29 Jun 2012 13:59:40 +0000

EFFORT is a UK NERC funded research project running from January 2011 to January 2014. It is a multi-disciplinary collaboration between geoscientists (School of GeoSciences, University of Edinburgh), rock physicists (Department of Earth Sciences, UCL), and informaticians (School of Informatics, University of Edinburgh). Brittle failure of the crust is likely to play a key role in controlling the timing of a range of geophysical hazards, such as volcanic eruptions, yet the predictability of brittle failure is unknown.

EFFORT aims to provide a facility for developing and testing models to forecast brittle failure in experimental and natural data. Model testing will be done in real-time, prospective mode (i.e. before failure has occurred) in order to avoid selection biases that are possible in retrospective analyses. The project will ultimately quantify the predictability of brittle failure, and how this predictability scales from simple, controlled laboratory conditions to the complex, uncontrolled real world.

Attachment	Size
Summary about EFFORT by Data Intensive Group	7.18 MB
Flexible Automated Streaming Transfer	1.18 MB
Varpy: A new python library for volcanic and rock physics data analysis	2.12 MB
Poster about EFFORT presented at EGU 2014 conference	2.04 MB

Acronym:

EFFORT

Web site:

Prototype Effort website.

Funding body:

NERC

Dates:

1 January 2011 to 1 January 2014

Project members:

Rosa.Filgueira

Projects:

EFFORT

Research topics:

Data-intensive computing

Project Status:

In progress

Earth Sciences, University College London

Jano.van.Hemert — Thu, 22 Jul 2010 09:12:01 +0000

The Department of Earth Sciences at UCL lies in the heart of London on the Bloomsbury campus. Our research spans a diverse range of activities including: crustal processes, Earth and planetary evolution, mineral physics, palaeobiology and palaeoclimatology, polar observation and modelling, natural hazards, environmental geochemistry and sedimentology.

Our teaching, reflecting the diversity of our research, encompasses a wide range of undergraduate and taught graduate programmes together with an active body of graduate research students.

Web site:

http://www.es.ucl.ac.uk/

Projects:

EFFORT

School of GeoSciences, University of Edinburgh

Jano.van.Hemert — Tue, 02 Mar 2010 11:21:54 +0000

In the School of GeoSciences we explore the factors and forces that shape our world and environments in which we live. As a leading interdisciplinary group, we aim to understand the interaction between the Earth's Geology, atmosphere, oceans, biosphere and human responses and roles in this complex interplay. With over 100 academic and research specialists and some of the best scientific infrastructure in the UK, we deliver new insights into the dynamics of the Earth System and its relationship with society. We have over 1100 undergraduate and 250 postgraduate students. Building on existing strengths, the School is developing fruitful new collaborations in grand challenge research and greater innovation in teaching.

Web site:

http://www.geos.ed.ac.uk/

Projects:

EFFORT