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Tagged / Big data

HE policy update for the w/e 25th May 2018

BU Challenges, Funding opportunities, innovation, international, Student Engagement

Brexit

In the PM’s speech this week referred to below, she mentioned the implications of Brexit for research:

…. since 2010 the number of overseas students coming to study at UK universities has increased by almost a quarter. The UK will always be open to the brightest and the best researchers to come and make their valued contribution. And today over half of the UK’s resident researcher population were born overseas.

When we leave the European Union, I will ensure that does not change.

  • Indeed the Britain we build together in the decades ahead must be one in which scientific collaboration and the free exchange of ideas is increased and extended, both between the UK and the European Union and with partners around the world.
  • I know how deeply British scientists value their collaboration with colleagues in other countries through EU-organised programmes.  And the contribution which UK science makes to those programmes is immense.
  • I have already said that I want the UK to have a deep science partnership with the European Union, because this is in the interests of scientists and industry right across Europe.  And today I want to spell out that commitment even more clearly.
  • The United Kingdom would like the option to fully associate ourselves with the excellence-based European science and innovation programmes – including the successor to Horizon 2020 and Euratom R&T.  It is in the mutual interest of the UK and the EU that we should do so.
  • Of course such an association would involve an appropriate UK financial contribution, which we would willingly make.
  • In return, we would look to maintain a suitable level of influence in line with that contribution and the benefits we bring.

The UK is ready to discuss these details with the Commission as soon as possible.

Some more flesh was put on these bones by a policy paper from the Department for Existing the EU: Framework for the UK-EU partnership Science, research and innovation

AI, data and other Industrial Strategy news

The PM made a speech this week announcing 4 “missions” that sit below the Industrial Strategy with a  focus on AI and data, amongst other things– you can read my blog of the highlights here

In related news, Innovate UK published a report on the immersive economy

And the government issued 4 calls for ideas and evidence on the PM’s 4 missions.  They want new ideas here:

  • AI and data:  “we have one question:  Where can the use of AI and data transform our lives?”
  • Ageing society: “we would like to hear your thoughts on the following: How can we best support people to have extra years of being healthy and independent? 
  • Clean Growth: “we would like to hear your thoughts on the following:  How can our construction industry use its existing strengths to halve energy use in buildings?”
  • Future of mobility: “we have one question:  How can we ensure that future transport technologies and services are developed in an inclusive manner?.

If you’d like to contribute to any of these, please contact policy@bournemouth.ac.uk

Subject level TEF

You can read BU’s response to the subject level TEF consultation here.  We agree with the issues raised below and we advocated a new model because of serious problems with both Model A and Model B.  We also suggested a longer time frame (because of the volume of work involved, not complacency), and disagreed with both grade inflation and teaching intensity metrics.  And we challenged the awards at both institutional and subject level, proposing instead two awards (good and excellent/ excellent and outstanding) with stars for subjects.

Interesting developments for TEF (and more generally), the OfS have published their timetable for NSS and Unistats data for 2018:

  • The Office for Students (OfS) is applying the Code of Practice for Statistics to its data publication in anticipation of its designation as a producer of official statistics by July 2018. This has implications for the pre-publication access that we can grant to NSS outcomes and Unistats data, as these will now be treated as official statistics. As a consequence, we will now publish the NSS public dataset at the same time as providers are able to access their own data 2 on Friday 27 July 2018.
  • There will also be no provider preview as part of the annual Unistats data collection and publication process, and data available in system reports will be limited to that essential for quality processes associated with the Unistats return.
  • In June 2018, we will add earnings data from the Longitudinal Education Outcomes dataset for English providers to Unistats.
  • From September 2018, we will begin to use the Common Aggregation Hierarchy developed for the Higher Education Classification of Subjects to present data on Unistats in place of the current subject hierarchy.
  • The Unistats website will be updated in June 2018 to include Year three outcomes from the Teaching Excellence and Student Outcomes Framework.

And :

  •  Following consultation on the outcomes of the Review of Unistats in 2015, the funding bodies are working together on options for a replacement for the Unistats website. This new resource would draw on the findings from the review about decision-making behaviour and the information needs of different groups of prospective students. We will progress this work in stages – ensuring that it is developed in a way that meets the needs of prospective students across all countries of the UK – and will provide the sector with periodic updates, the first of which will be in summer 2018.

Research Professional have a neat summary of the sector response.

On Wonkhe:

  • panel chair Janice Kay of the University of Exeter reflects on progress made and the challenges – and opportunities – arising from the exercise.  “when breaking down the metrics into 35 subjects, cohort sizes can be small”  “ it is clear that the current format of the seven subject groupings poses challenges. For example, while it may reduce the writing load by asking institutions to describe its subjects in a summated way, it has sometimes limited what subjects can say about themselves, making it difficult to identify what happens in individual subjects. And we have heard that the format can increase writing effort, even if volume is reduced… It’s critical during this exercise that the written judgments can continue to do this, and that holistic judgments are not captured by metrics. There is therefore a question whether metric and written submission data can be better balanced in Model B.”  Plus some credibility issues with Model A
  • Melanie Rimmer, chief planner at Goldsmiths, University of London, ponders the likely outcomes of the subject-level TEF consultation.  “Model B best meets the primary intention of Subject-Level TEF – that being to provide greater information to students – since it allows for greater variation between outcomes for subjects. However, highlighting variation in provision will only be attractive to institutions where that differentiation is a better rating than the current provider-level rating. If you want to hide weaker performance, then opt for Model A.  The main argument in favour of Model A is that it will reduce the burden of submission and assessment. That will be attractive to institutions which, having been through the exercise once and established their credentials, perceive the requirements of TEF as an unnecessary additional imposition that will deliver minimal return. Solid Golds and Silvers are likely to prefer Model A for this reason. Those at the borders of the ratings, with an eye on how close they are to moving between them, are more likely to see value in the greater effort required by Model B.”  “Those which are unlikely to see their rating change, or indeed which might see their metrics moving in the wrong direction and worry about a lesser rating, will naturally support longer duration awards. Those hoping to gain a shinier medal as a result of improving performance will see value in more regular submissions.”  “There are, however, bound to be areas of common ground on the consultation proposals. Every institution I have spoken to has identified a problem with the subject classifications, highlighting why combining disciplines X and Y makes no sense in their institution. However, in each case the disciplines cited are different because the issues stem primarily from institutional structures.”
  • Stephanie Harris of Universities UK (UUK) looks ahead to the future of TEF and the forthcoming statutory review of the exercise.
  • Claire Taylor of Wrexham Glyndŵr University looks at TEF from a quality enhancement perspective and considers the options for institutions in devolved nations.  “perhaps the very act of putting together the written submission also provides an opportunity for us to engage with an enhancement agenda. By reflecting upon TEF metric performance within the written submission, providers have an opportunity to outline the qualitative evidence base in relation to enhancement, evaluation and impact, within the context of their own overall institutional strategic approach to improving the student experience”.  But: “the introduction of grade inflation metrics during TEF3 is of questionable value. Such a metric does not consider the contexts within which providers are operating. Providers have robust and detailed mechanisms for ensuring fair and equitable assessment of student work, including the use of external examiners to calibrate sector-wide, a system that contributes positively to the enhancement agenda and to which the grade inflation metric adds little value.”, and “The consultation asks for views around the introduction of a measure of teaching intensity. In my view, the proposed measure has no meaning and no connection to excellence, value or quality, let alone enhancement. There is the potential for the information to be misleading as it will need specialist and careful interpretation”
  • with an updated TEF diagram, “The Incredible Machine”, David Kernohan and Ant Bagshaw look at TEF3 and question its compatibility with the earlier versions of the exercise.  “So what – honestly – is TEF now for? It doesn’t adequately capture the student experience or the quality of teaching. It does not confer any benefit – other than a questionable marketing boost – to providers, and there is no evidence that students are making serious use of it to choose courses, universities, or colleges. Internationally, concerns have already been raised that the three-level ratings are confusing – it’s been widely reported that “Bronze” institutions are often not considered to meet the UK’s laudably stringent teaching quality thresholds. And it is not even a reliable time series – a TEF3 Gold is now achievable by an institution that would not have passed the test under TEF2 rules. Later iterations may well be built “ground up” from subject TEF assessments, once again changing the rules fundamentally. Let’s not even mention TEF1 (it’s OK, no-one ever does) in this context.”

From Dods: The Science and Technology Committee have published its report from the Algorithms in decision-making inquiry which acknowledges the huge opportunities presented by algorithms to the public sector and wider society, but also the potential for their decisions to disproportionately affect certain groups.

The report calls on the Centre for Data Ethics & Innovation – being set up by the Government – to examine algorithm biases and transparency tools, determine the scope for individuals to be able to challenge the results of all significant algorithmic decisions which affect them (such as mortgages and loans) and where appropriate to seek redress for the impacts of such decisions. Where algorithms significantly adversely affect the public or their rights, the Committee highlights that a combination of algorithmic explanation and as much transparency as possible is needed.

It also calls for the Government to provide better oversight of private sector algorithms which use public sector datasets, and look at how best to monetise these datasets to improve outcomes across Government. The Committee also recommends that the Government should:

  • Continue to make public sector datasets available for both ‘big data’ developers and algorithm developers through new ‘data trusts’, and make better use of its databases to improve public service delivery
  • Produce, maintain and publish a list of where algorithms are being used within Central Government, or are planned to be used, to aid transparency, and identify a ministerial champion with oversight of public sector algorithm use.
  • Commission a review from the Crown Commercial Service which sets out a model for private/public sector involvement in developing algorithms.

Social Mobility Commission

Under the 10 minute rule, the Chair of the Education Committee Robert Halfon introduced legislation to give greater powers and resources to the Social Mobility Commission (SMC), the body set up to promote social justice.  (Link here at 13.52.09pm).  It will have its second reading on 15th June.

The Committee published a draft Bill in March alongside its report.  In its report, the Committee called for the establishment of a new implementation body at the heart of Government to drive forward the social justice agenda.

And in the meantime, the Government have announced a recommendation for a new Chair.  Dame Martina Milburn has spent 14 years as Chief Executive of the Prince’s Trust, supporting more than 450,000 disadvantaged young people across the country in that time, with three in four of these going on to work, education or training. She is also a non-executive director of the National Citizen Service and the Capital City College Group, and was previously Chief Executive of BBC Children in Need and of the Association of Spinal Injury Research, Rehabilitation and Reintegration.

Immigration

From Dods: Last Friday the Science and Technology Committee announced that it intends to develop its own proposals for immigration and visa rules for scientists post-Brexit. This work follows the Government’s rejection of the Committee’s call for the conclusions of the Migration Advisory Committee (MAC) relating to science to be brought forward to form part of an ‘early deal’ for science and innovation.

The Committee published its report on “Brexit, Science and Innovation” in March, and has recently received the Government’s response. The report welcomed the Prime Minister’s call for a “far-reaching pact” with the EU on science and innovation and recommended that an early deal for science—including on the ‘people’ element—could set a positive tone for the rest of the trade negotiations, given the mutual benefits of cooperation on science and innovation for the UK and the EU.

The Committee will draw on the submissions to its previous Brexit inquiry and the sector’s submissions to the MAC to construct its proposals for the immigration system, but further input to this process is welcome on the following points:

  • If an early deal for science and innovation could be negotiated, what specifically should it to contain in relation to immigration rules and movement of people involved with science and innovation?
  • What are the specific career needs of scientists in relation to movement of people, both in terms of attracting and retaining the people the UK needs and supporting the research that they do?
  • What aspects of the ‘people’ element need to be negotiated with the EU-27, as opposed to being simply decided on by the Government?
  • On what timescale is clarity needed in relation to future immigration rules in order to support science and innovation in the UK?

Consultations

Click here to view the updated consultation tracker. Email us on policy@bournemouth.ac.uk if you’d like to contribute to any of the current consultations.

Subscribe!

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JANE FORSTER                                            |                       SARAH CARTER

Policy Advisor                                                                     Policy & Public Affairs Officer

Follow: @PolicyBU on Twitter                   |                       policy@bournemouth.ac.uk

 

 

How can automation and machine intelligence assist defence intelligence analysis?

Awarded & submitted bids, Business Engagement, innovation

Flying planes in a computer game

Digital Catapult is running a Pit Stop with the Defence Science and Technology Laboratory (Dstl) in March 2017. Small and medium sized companies, academics and experts interested in developing innovative automation and machine intelligence solutions to assist defence intelligence analysts are encouraged to apply.

The aim of the Pit Stop is to increase understanding and use of the rapidly developing multidisciplinary field of “autonomous agents” (unsupervised software and devices that undertake analysis on behalf of individuals or groups, without the requirement of human interaction) for operational planning.

Innovators experienced in developing solutions for autonomous data analysis and interpretation, with expertise in the following areas are encouraged to apply:

  • Machine learning
  • Artificial intelligence
  • Machine intelligence
  • Big data
  • Automation
  • Predictive analytics
  • Automated planning
  • Autonomous intelligence systems
  • Cognitive science

The closing date to apply for this Pit Stop is Friday 27 January 2017.

Click here for more information.

Data Science and Analytics Training for Business

HEIF, Knowledge Exchange, Knowledge Transfer

logo-czrneData Science and Analytics Training and Engagement Services for Business – HEIF project

We are experiencing an explosive growth of digital content. According to International Data Corporation, there are currently over 2.7 zetabytes of data. It is estimated that in 2020, the digital universe will be 50 times as big as in 2010 and that from now until 2020 it will double every two years.

The commercial world has been transformed by Big Data with companies competing on analytics. Data has become a commodity referred to as the ‘new oil’. We are entering a new era of predictive analytics and data intensive computing which has been recognised worldwide with various high profile reports. In a recent UK-wide report commissioned by SAS UK (one of our key industrial partners) it has been estimated that there will be about 132,000 big data job opportunities created in the UK economy between 2012 and 2017. McKinsey’s report states that by 2018 the US alone will face a shortage of between 140,000 to 190,000 people with deep analytical skills, while in the UK such shortage will be in the region of 58,000 (e-Skills UK5). Another SAS commissioned report focusing on “data equity” and its impact on the UK, states that increasing adoption of big data analytics will result in cumulative benefits of £216 billion over the years 2012-17.

Following the success of recently launched MSc in Applied Data Analytics, this HEIF project seeks to take advantage of a large demand for and addresses the widening advanced analytics skills gap. Our HEIF project focuses on:

  1. Engagement with industry through a provision of an on-going opportunity for contact, information and advice in the Data Science Surgeries which are open to businesses of all sizes as well as university staff and students. This service is to support the creation of Knowledge Exchange professional network in the Data Science and Analytics area helping to identify potential skillset needed as well as transfer of knowledge and collaborative research opportunities.
  2. Development of a portfolio of CPD/short courses within an area with acute UK-wide shortage of skills and where, within the Data Science community consisting of over 50 academics from four faculties, BU has a wealth of expertise and excellent track record.

Over time, the Data Science Surgeries and CPD courses will facilitate engagement between industry and the broader BU Data Science community, enabling us to build bridges and develop relationships with industry, as well as interdisciplinary research collaborations.  The new perspectives developed through this interdisciplinary collaboration will not only help to give a better understanding of some of the complex problems facing our society, but also help to inform both the teaching and professional practice undertaken by our academics -supporting the vision of Fusion at BU.

The Personal Data & Trust Network is seeking new members

Business Engagement, Knowledge Exchange

Data-science-history

The Network aims to build and nurture a community that brings together industry, the public sector, funders, research organisations, individual researchers and innovators to support the UK in becoming the global leader in trust and responsible innovation with personal data.

To find our more click here

It’s free to join

ESRC seminar: Microenterprise, Technology and Big Data – Southampton

events

Event: Microenterprise, technology and big data: new forms of digital enterprise and work and ways to research them

Dates: Monday 10 and Tuesday 11 October 2016

Location: Grand Harbour Hotel – West Quay Road, Southampton, SO15 1AG – View Map

Please click here to register to attend this FREE event.

About:

This seminar will focus on how technology has transformed microenterprise and work and is likely to shape these in the future. The first key aim is to contribute to understanding of digital microenterprise and work in a global perspective. Combining both Global North and Global South perspectives, this seminar seeks to show how new technology including social media and mobile phones are shaping enterprise and work practices. The potentials and risks involved in advanced technologies for how work is performed and experienced and microenterprises set up and organized will be critically interrogated. The second key aim is to explore new data and methods to reveal and understand digital work and microenterprise which are often ‘hidden’ in workers’ and entrepreneurs’ homes and therefore require novel research approaches. New (big) data sources and emerging research infrastructures will be presented and their application for studying enterprise and work practices discussed.

For more information and to register click here.

Big data – helping cities solving planning challenges

Business Engagement, innovation, Knowledge Exchange

Data-science-history

A data platform developed with support of Innovate UK is helping big cities to plan services such as transport, education and housing.

A data science business is helping London to plan its services thanks to a new decision-making platform. Mastodon C won a £2 million SBRI (Small Business Research Initiative) contract in a ‘future cities’ competition to find ways of meeting the challenges faced by urban areas.

Mastodon C is working with the Greater London Authority to develop and test its Witan platform in a project supported by Innovate UK.

Witan provides modelling tools and data management processes to help solve real challenges faced by cities and their partners, and is already being used by 33 London boroughs. Witan is being used by the London boroughs to see how latest housing projections will affect the spread of population up to 2041. The work used to take specialist staff weeks to do but can now be generated in minutes. The results will help council officials to plan many services including where the demand is likely to be for services such as school places, waste disposal, and housing.

Francine Bennett, chief executive and co-founder of Mastodon C, said: “Our motto is ‘big data done better’. That has two meanings. What we do with big data, we do very well technically. We are also interested in better applications of big data and data science, building applications that improve people’s lives as well as work for the business.”

Click here for the full story.

 

 

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How well do local authorities use data?

innovation, Knowledge Exchange

open data

 

Across England, local authorities are asking questions about how they can redesign services, save money and drive local economic growth.

  • How many people will need adult social care services in 5 years time?
  • Which children are most likely to enter the care system and what support might prevent this happening?
  • How can traffic flows, public transport, cycle lanes and town centres be optimised to help local businesses to grow?
  • Which households are most likely to fall into council tax arrears?
  • How can money be saved on refuse collection by only emptying bins when they are full?
  • How effective are local authority commissioned services at delivering positive social outcomes?

Nesta’s new research programme – the Local Datavores – aims to help local authorities use data better.

Nesta are always keen to hear from people working on data projects in local authorities and related organisations. If you would like to be involved in the research, or have heard about or been involved in any pioneering data science projects, please get in touch at tom.symons@nesta.org.uk

Big Data in Health and Care – ‘Using data to gain new insights’

Business Engagement, conferences, Knowledge Exchange

Data-science-history

Date: Tuesday 19 April

Location: St. Mary’s Stadium – Britannia Road Southampton, Hampshire SO14 5FP GB – View Map

Time: 9:00am – 5:00pm

About the event:

Big Data in healthcare is being used to cure disease, improve quality of life, avoid preventable deaths and more importantly plan primary prevention strategies. With the UK population increasing and all of us living longer, through initiatives such as the Vanguards, models of care are rapidly changing, and many of the decisions behind those changes are being driven by data.

This Big Data conference, chaired by Richard Samuel, (Fareham and Gosport, South-Eastern Hants CEO) will provide an overview of Big Data from experts within the field, as well as practical examples of how Big Data is being used to improve the way that we deliver services. A Big Data expo will be accessible throughout the day and in the afternoon a variety of plenary sessions will gather feedback from participants to help shape future actions.

To register: Click here

If you have any questions or queries regarding the event or any specific access needs please do not hesitate to contact Katie Cheeseman – Digital Health Programme Manager katie.cheeseman@wessexahsn.net                                                                                     

 

Three for the price of one: Keynote Talk, Outstanding Contribution Award and Media Appearance.

Prof Gabrys delivers a keynote talk at the KES 2014 international conference, receives the Outstanding Contribution to the KES International organisation award and appears in two popular Polish TV’s “Panorama” news programmes.

It was a very nice and productive trip to a beautiful Polish seaside city of Gdynia where the 18th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems took place between the 14th and 17th of September 20014.

I thought that I was only going to deliver a keynote talk which in itself was a nice recognition of the ongoing work that we are doing in the areas of robust adaptive predictive modelling and data science and a great opportunity to talk to over 200 delegates from over 30 countries attending the conference but as it turned out there were some other attractions awaiting.

This very well organised conference attracted the attention of the Polish TV and the topics of data science, artificial intelligence or big data, all in the focus of our Data Science Institute at BU, were judged to be of considerable interest to the general public. Not only I had an opportunity to talk briefly about the conference topics during the TV coverage at the conference venue (which was aired in the evening news programme on the 15th of Sep) but together with one of the local organisers we were invited to the “Panorama” programme studio to take part in the morning news programme the following day (aired on the 16th of Sep). The interaction with the journalists and the production teams brought to my attention how important is our role in informing and educating about this very dynamically changing field and related technological innovations which have already had such a huge impact on our lives and will play even bigger role in the near future.

So whatever next, I thought. Well, there was another surprise around the corner. Though I have been involved in the KES International for a number of years it has come as a very pleasant surprise and an honour to receive the Outstanding Contribution to KES International award during the conference dinner.

An icing on the cake, you could say. 🙂

Data as Utility and Analytics as a Service

We are currently experiencing an incredible, explosive growth in digital content and information. According to IDC, there currently exists over 2.7 zetabytes of data. It is estimated that the digital universe in 2020 will be 50 times as big as in 2010 and that from now until 2020 it will double every two years. Research in traditionally qualitative disciplines is fundamentally changing due to the availability of such vast amounts of data. In fact, data-intensive computing has been named as the fourth paradigm of scientific discovery and is expected to be key in unifying the theoretical, experimental and simulation based approaches to science. The commercial world has also been transformed by a focus on BIG DATA with companies competing on analytics. Data has become a commodity and in recent years has been referred to as the ‘new oil’. We are entering a new era of predictive analytics and data intensive computingwhich has been recognised worldwide with various high profile reports highlighting the challenges and attempting to quantify its huge potential benefits.

In addition to our previously advertised Data Science workshop suitable for a broader audience (Data Scientist: The sexiest job of the 21st century?), this much more focused EPSRC IT as a Utility Network+ (http://www.itutility.ac.uk/) and EU INFER (http://www.infer.eu/) co-sponsored event organised as part of the Bournemouth University’s Festival of Learning will explore the value of very quickly growing data and feasibility of providing data and predictive analytics as services in various industries, public sector and academic disciplines.

The workshop will feature five invited 30 minutes talks to set up the scene for:

i) looking at the growing value of data and treating it as a utility; and

ii) feasibility of providing data and predictive analytics as a service on a large scale and across many industries and disciplines.

The talks will be followed by breakout interactive/discussion sessions in mixed groups with potential linking of partners for various follow on activities (grant applications, proof of concept projects etc.).

The attendance is free and if you are interested to join us please register following this link: http://microsites.bournemouth.ac.uk/festival-of-learning/events/data-as-a-utility-and-analytics-as-a-service/.

Confirmed invited speakers:

Prof. Nello Cristianini, Prof. of Artificial Intelligence, University of Bristol, UK

Prof. Detlef Nauck, Chief Research Scientist, BT’s Research and Innovation Division, UK

Tom Quay, Director, We Are Base Ltd, UK

Prof. Trevor Martin, Prof. of Artificial Intelligence, University of Bristol, UK

Dr. Dymitr Ruta, Chief Researcher, EBTIC, Khalifa University, UAE

 

Date: 9 June 2014: 12pm – 6pm.

Location: 3rd Floor, Executive Business Centre, 89 Holdenhurst Road, Bournemouth, BH8 8EB

Workshop programme:

12.00 – 12.45 – Registration and buffet lunch.

12.45 – 13.00 – Welcome and introduction (Bogdan Gabrys, Bournemouth University, UK)

13.00 – 13.30 – Prof. Detlef Nauck (BT, UK)

13.30 – 14.00 –Prof. Nello Cristianini (Bristol University, UK)

14.00 – 14.30 – Tom Quay (We Are Base Ltd, UK)

14.30 – 15.00 – Coffee break

15.00 – 15.30 – Prof. Trevor Martin (Bristol University/BT, UK)

15.30 – 16.00 – Dr Dymitr Ruta (EBTIC, Khalifa University, UAE)

16.00 – 16.15 – Break

16.15 – 17.15 – Breakout discussion sessions: i) data as a utility; ii) analytics as a service.

17.15 – 18.00 – Summary, recommendations and follow on actions.

 

Please contact the workshop chair, Prof. Bogdan Gabrys (bgabrys@bournemouth.ac.uk), if you require any further information.

Data scientist: The sexiest job of the 21st century?

Festival of Learning

UK Government has identified Data Science as the ‘transforming and growth driving force across all sectors of economy’ and named Big Data as one of the ‘eight great technologies’. With an unprecedented growth in digital content and data, as the digital universe in 2020 is estimated to be 50 times as big as in 2010, we have entered a new era of predictive analytics and data intensive computing. Data scientists are expected to play a key role in this data revolution and their job has even been referred to as “the sexiest job of the 21st century”. This EU INFER sponsored one-day open workshop will combine talks by eminent speakers, a panel-audience discussion, exhibition of projects, hands-on experience session with a number of digital devices and provide a chance to meet data science experts from academia and industry.

Please register at: (http://microsites.bournemouth.ac.uk/festival-of-learning/events/data-scientist-the-sexiest-job-of-the-21st-century/) and join us during this exciting event.

Date: 10 June 2014: 9am – 6pm.

Location: 3rd Floor, Executive Business Centre, 89 Holdenhurst Road, Bournemouth, BH8 8EB

Workshop chair: Prof. Bogdan Gabrys, Data Science Institute, Bournemouth University

Detailed program of the workshop:

9.00 – 9.15 – Welcome and introduction

9.15 – 10.15 – Prof. Nello Cristianini (Bristol University, UK), ThinkBIG : The Impact of Big Data on Science and Society

10.15 – 10.30 – Break

10.30 – 11.30 – Prof. David van Dyk (Imperial College London, UK), Big Data and Complex Modeling Challenges in Astronomy and Solar Physics

11.30 – 14.30 – Lunch combined with networking, exhibitions, poster session and hands on experimenting.

14.30 – 15.45 – Panel discussion: Is Data Science “the transforming and growth driving force across all sectors of economy”? Is a Data Scientist the “sexiest job of the 21st century”? (Panelists to include the keynote speakers and a number of users and experts from academia as well as public and private sectors)

15.45 – 16.00 – Break

16.00 – 17.00 – Prof. Detlef Nauck (BT, UK), Predictive Analytics and Big Data

17.00 – 17.15 – Break

17.15 – 18.00 – Prof. Bogdan Gabrys (Bournemouth University, UK), Data Science at BU

 

Information about invited keynote talks and speakers:

Talk 1: ThinkBIG: The Impact of Big Data on Science and Society by Prof. Nello Cristianini, Professor of Artificial Intelligence, Bristol University

Abstract: Computers can now do things that their programmers cannot explain or understand: today’s Artificial Intelligence has found a way to bypass the need for understanding a phenomenon before we can replicate it in a computer. The technology that made this possible is called machine learning: a method to program computers by showing them examples of the desired behaviour. And the fuel that powers it all is DATA. Lots of it.

For this reason, data has been called the new oil: a new natural resource, that businesses and scientists alike can leverage, by feeding it to massive learning computers to do things that we do not understand well enough to implement them with a traditional program. This new way of working is all about predicting, not explaining. It is about knowing what a new drug will do to a patient, not why. But: was not science meant to help us make sense of the world? Or is it just meant to deliver good predictions? And let us remember that the fuel that powers this revolution is very often our own personal data, and that we still do not have a clear cultural framework to think about this.

Short Bio Note: Nello Cristianini is a Professor of Artificial Intelligence at the University of Bristol. His current research covers the large scale analysis of media content (news and social media), using various AI methods, and the implications of Big Data.

Cristianini is the co-author of two widely known books in machine learning, “An Introduction to Support Vector Machines” and “Kernel Methods for Pattern Analysis” and of a book in bioinformatics “Introduction to Computational Genomics”. He is also a former recipient of the Royal Society Wolfson Research Merit Award and a current holder of a European Research Council Advanced Grant.

Talk 2: Big Data and Complex Modeling Challenges in Astronomy and Solar Physics by Prof. David van Dyk, Professor of Statistics, Imperial College London

Abstract: In recent years, technological advances have dramatically increased the quality and quantity of data available to astronomers.  Newly launched or soon-to-be launched space-based telescopes are tailored to data-collection challenges associated with specific scientific goals. These instruments provide massive new surveys resulting in new catalogs containing terabytes of data, high resolution spectrography and imaging across the electromagnetic spectrum, and incredibly detailed movies of dynamic and explosive processes in the solar atmosphere. These new data streams are helping scientists make impressive strides in our understanding of the physical universe, but at the same time generating massive data-analytic and data-mining challenges for scientists who study the resulting data. This talk will give an overview of a number of statistical challenges that arise form big data and complex models in astronomy and solar physics.

Short Bio Note: David van Dyk is a Professor in the Statistics Section of the Department of Mathematics at Imperial College London. After obtaining his PhD from the University of Chicago, he held faculty positions at Harvard University and the University of California, Irvine before relocating to London in 2011. Professor van Dyk was elected Fellow in the American Statistical Association in 2006, elected Fellow of the Institute of Mathematical Statistics in 2010, received a Wolfson Merit Award in 2011, and was elected to the Board of Directors of the American Statistical Association (2015-17). His scholarly work focuses on methodological and computational issues involved with Bayesian analysis of highly structured statistical models and emphasizes serious interdisciplinary research, especially in astronomy. He founded and coordinates the CHASC International Astrostatistics Center and is particularly interested in improving the efficiency of computationally intensive methods involving data augmentation, such as EM-type algorithms and various Markov chain Monte Carlo methods.

Talk 3: Predictive Analytics and Big Data by Prof Dr Detlef Nauck, Chief Research Scientist, BT

Abstract: Detlef’s research focuses on exploiting large operational data sources to improve BT’s systems, networks and processes. The ultimate goal is the introduction of autonomic systems into operations that can learn from historic data to self- improve, self-configure and self-heal. In his presentation, Detlef will discuss how the application of predictive analytics to operational data has led to a number of solutions in BT’s operations that predict performance of networks, systems and processes, and forecast expected demand. Detlef will also discuss some current research topics at BT, which range from automatic discovery of patterns, to autonomic behaviour in processes and systems, to the challenges of exploiting Big Data.

Short Bio Note: Detlef Nauck is a Chief Research Scientist with BT’s Research and Innovation Division located at Adastral Park, Ipswich, UK. He is leading a group of international scientists working on Intelligent Data Analysis and Autonomic Systems. He is a Visiting Professor at Bournemouth University and a Private Docent at the Otto-von-Guericke University of Magdeburg, Germany. Detlef holds an MSc (1990) and a PhD (1994) in Computer Science both from the University of Braunschweig, Germany. He also holds a Habilitation (post-doctoral degree) in Computer Science from the Otto-von-Guericke University of Magdeburg, Germany (2000). Detlef has published over 120 papers, holds 4 patents and 20 active patent applications.

Workshop on Streaming Analytics Thursday 13th March 10:30.

Fusion, PG research

As part of a collaboration between BU and several other EU based universities and intitutions we will be hosting SAAT 2014 a workshop on the emerging area of streaming analytics. The workshop is open to all for the first day (the second day is taken up with management meetings). The focus of this workshop is on the technical aspects of how to provide streaming analytics.

Scalability and responsiveness of algorithms and architectures for large scale data streams are fundamental to harvesting the power of data generated in real-time networks. The workshop seeks to bring together industry and academic partners to explore specifically the requirements of data processing, the real-world target applications and develop from there the techniques required. The scope thus includes applications, scaling algorithms, streaming platforms, integration of streaming and batch algorithms, graph partitioning together with machine learning for streaming, concept drift and dynamic data analysis. Additional topics such as security issues and tool and platform development are of interest.

Aims:
The key aims in this workshop are several fold. Primarily we seek to identify the key issues associated real world streams of data, including key target applications. Integrated  solutions, combining appropriate topics from the scope which target likely directions in this field is the end goal. Specifically, the aim of the workshop is to facilitate interaction as a crucible for consortium building in advance of Horizon 2020 (call 1.A.1.1 from the 2014-15 draft work programme.).

Organisers: Dr. Hamid Bouchachia(DEC) , Dr. Damien Fay (DEC)

Service Computing Seminar: Servicing Big Data

Fusion

As part of the Service Computing Seminar (SCS) project, funded by Bournemouth University Fusion Investment Fund, we would like to invite you to the Service Computing Seminar

Title: Servicing Big Data

Time: 14:00-16:00 Wednesday, 18 Dec. 2013

Venue: PG143 (Thomas Hardy Suite, Talbot Campus)

Speaker: Prof. Athman Bouguettaya, Head of School of Computer Science and Information Technology at RMIT University, Melbourne, Australia

 

Abstract

Big data is here and in a big way.  Big data is coming from all sorts of sources and means, including sensors, deep space, social media, smartphones, genomic, etc.  The cloud has been instrumental supporting the storage and processing of the ever increasing amount of data.  “Domesticating” the data, i.e., making it useful, however, has been a major challenge.  Service computing is the next major evolution of computing that aims at transforming massive data into artefacts that are acted upon, i.e., services. Service computing is increasingly being recognized as part of a broader agenda in Service Science. In that respect, service computing may be viewed as the “engineering” side of service science. Service computing broadly focuses at providing a foundational framework to support a service-centric view of designing, developing, and exposing data (and applications), whether it is in the enterprise or on the Web. In that respect, the Web is and will undoubtedly be the preferred delivery platform of service-based solutions. More specifically, Web services are currently without contest the key enabler for deploying service-centric solutions. Fully delivering on the potential of next-generation Web services requires building a foundation that would provide a sound design for efficiently developing, deploying, publishing, discovering, composing, trusting, and optimizing access to Web services in an open, competitive, untrustworthy, and highly dynamic environment. The Web service foundation is the key catalyst for the development of a uniform framework called Web Service Management System (WSMS). In this novel framework, Web services are treated as first-class objects. In this talk, I will first motivate the need for a uniform service management to service big data. I will then overview the core components of a typical WSMS. I will conclude by describing our latest research servicing sensor data.

 

Short Bio

Athman Bouguettaya is Professor and Head of School of Computer Science and Information Technology at RMIT University, Melbourne, Australia. He received his PhD in Computer Science from the University of Colorado at Boulder (USA) in 1992.  He was previously Science Leader in Service Computing at CSIRO ICT Centre, Canberra. Australia. Before that, he was a tenured faculty member and Program director in the Computer Science department at Virginia Polytechnic Institute and State University (commonly known as Virginia Tech) (USA).  He is a founding member and past President of the Service Science Society, a non-profit organization that aims at forming a community of service scientists for the advancement of service science. He is on the editorial boards of several journals including, the IEEE Transactions on Services Computing, ACM Transactions on Internet Technology, the International Journal on Next Generation Computing, VLDB Journal, Distributed and Parallel Databases Journal, and the International Journal of Cooperative Information Systems. He is also on the editorial board of the Springer-Verlag book series on Services Science.  He served as a guest editor of a number of special issues including the special issue of the ACM Transactions on Internet Technology on Semantic Web services, a special issue the IEEE Transactions on Services Computing on Service Query Models, and a special issue of IEEE Internet Computing on Database Technology on the Web. He served as a Program Chair of the 2012 International Conference on Web and Information System Engineering, the 2009 and 2010 Australasian Database Conference, 2008 International Conference on Service Oriented Computing (ICSOC) and the IEEE RIDE Workshop on Web Services for E-Commerce and E-Government (RIDE-WS-ECEG’04). He has published more than 170 books, book chapters, and articles in journals and conferences in the area of databases and service computing (e.g., the IEEE Transactions on Knowledge and Data Engineering, the ACM Transactions on the Web, WWW Journal, VLDB Journal, SIGMOD, ICDE, VLDB, and EDBT). He was the recipient of several federally competitive grants in Australia (e.g., ARC) and the US (e.g., NSF, NIH). He is a Fellow of the IEEE and a Distinguished Scientist of the ACM.