The Society of Data Miners is delighted to announce a talk by Dr Kuan Hon titled Data and Data Protection Laws, to he held at 6pm on Monday 23rd January 2017 at the Royal Statistical Society, 12 Errol St, London, EC1Y 8LX.
If you're working with data, how do data protection laws affect you? What about the potentially huge fines under the General Data Protection Regulation? Does Brexit mean that you can ignore the GDPR? Come and find out about some of the myths and realities behind data protection law.
Dr W Kuan Hon, MA(Cantab), LLM(UPenn), MSc(Imperial), LLM(QMUL), PhD(QMUL), is a Consultant Lawyer for Pinsent Masons, the law firm behind technology law thought leadership site Out-Law.com, an Editor of the Encyclopedia of Data Protection and Privacy and a Fellow of the Open Data Institute. She was formerly a Senior Researcher at Queen Mary University of London focusing on legal issues in cloud computing including data protection. An English solicitor and (non-practising) New York attorney, Kuan has degrees in law and computing science and a joint law/computer science doctorate. She regularly speaks at events, and has spoken at CERN, CSA and ENISA. Kuan was lead author of 8 chapters in Cloud Computing Law (OUP 2013, Millard ed.) and has published many articles. She is a member of the BCS’s Information Privacy Expert Panel. Her personal site is at www.kuan0.com.
Many thanks to Matthew Tod for his fascinating and entertaining presentation on joining big digital data to small customer data, and thanks to all those who attended for making the discussion so interesting. Also many thanks to Google Campus London for providing the venue.
Slides are available here:
The Society of Data Miners, in association with the Alan Turing Institute, is delighted to announce the second in a series of practitioner seminars. This will be a talk by Rick Adderley, CEO of A E Solutions Ltd, to be held at the Alan Turing Institute, British Library, 96 Euston Road, London NW1 2DB (near Kings Cross / St Pancras) at 2-4pm, Thursday 1st December 2016.
This talk will discuss the challenges of mining Police data to provide operational intelligence. Rick will introduce the data and systems involved in day-to-day reporting, resource tasking and arresting offenders, including the issues of linking data across systems and the challenges of extracting useful information from free text. Digging into more advanced analytics, Rick will discuss criminal network analysis or CNA, an important tool in crime prevention and detection, and the differences between analysing overt networks (SNA) and covert networks (CNA). Rick will describe how supervised and unsupervised learning methods have been used in the identification of prolific and priority offenders, and how the results are used to solve crimes and target offenders, and to use resources effectively. Finally Rick will describe the EU-funded FP7 project Valcri (www.valcri.org), and its task to provide a Police data set that is suitable for release into the research community.
Rick is a retired Police Officer having served for 32 years in an operational capacity. His legacy to the Service is an intelligence product which was developed for the West Midlands region and is now used by all UK Police Forces; he specialises in profiling criminal activity. Rick retired in 2003 and started his data mining company, A E Solutions, focusing within the UK Emergency Services arena. Rick is also a director of the Society of Data Miners.
Towards a professional code of ethics for data mining
First in a series of meetings
Summary: The first in a series of meetings to collect insights and issues from the data mining and analytics community on a practical code of ethics for the profession
Tom Khabaza, Chairman of the Society of Data Miners
Hugh Lawson-Tancred, Ethics Co-ordinator for the Society of Data Miners
Hetan Shah, Executive Director of the Royal Statistical Society
Mariarosaria Taddeo, Researcher at the Oxford Internet Institute, University of Oxford & Faculty Fellow of the Alan Turing Institute
Richard Beaumont, Product Manager at OneTrust
Location: Digital Catapult London, 101 Euston Road, London NW1 2RA (near Kings Cross / St Pancras)
Date & Time: 1:30-3:30 pm, Monday 5 December 2016
The Society of Data Miners is delighted to announce the first in a series of meetings for consultation and discussion on a proposed code of ethics for the data mining profession.
Data mining and data analysis now play an enormous role in social and economic life, but this has not been accompanied by appropriate reflection on the ethical responsibilities of practitioners. The Society of Data Miners will conduct a series of meetings to obtain a broad knowledge-base, to draft a code addressing the ethical issues which face the data analytics profession. The first of these meetings will take the form of a panel discussion, involving senior experts on issues of data ethics:
Hetan Shah is Executive Director of the Royal Statistical Society. He will talk about the wide range of ethical issues which emerge in the data science landscape, and argue that multiple mechanisms are needed to deal with this, including a Council for Data Ethics.
Mariarosaria Taddeo is a researcher at the Oxford Internet Institute, University of Oxford, and Faculty Fellow at the Alan Turing Institute. Mariarosaria will focus on the relevance of Data Ethics to support the development and employment of data science for the good of society, including the ethics of data, the ethics of algorithms and the ethics of practice.
Richard Beaumont is Product Manager at OneTrust, providers of privacy management software to help businesses meet legal obligations for privacy and data protection. Richard will discuss questions such as: Just because you can, does it mean you should?
Hugh Lawson-Tancred has worked on both the practical and theoretical side of data ethics. Hugh will concentrate on the issue of deanonymisation and the ethical cost of collecting, holding and analysing large datasets. Hugh will also summarise the work of the Society so far on drafting a code of ethics, and the proposed series of consultative meetings.
Tom Khabaza is the Chairman of the Society of Data Miners, and a data analytics practitioner of 25 year standing. Tom will chair the panel discussion, hoping to elicit a draft list of issues that the Society should address in its code of ethics.
The Society of Data Miners is an independent non-profit organisation for the public good with the purposes to:
- Increase the benefits of data mining to society;
- Increase knowledge and awareness of the nature and benefits of data mining;
- Advance the profession of data mining;
- Form a community of and for data miners.
In pursuit of these purposes, the Society of Data Miners will:
- Hold events for data miners to exchange experience, formulate best practice and broaden the scope and benefits of data mining;
- Encourage adoption of the highest ethical standards in data mining;
- Provide public and media information about data mining and its benefits;
- Provide certification of data miners who have reached a recognised level of competence and experience in data mining practice;
- Encourage the creation of a literature of data mining practice;
- Encourage data mining standards;
A Sneak Peek into how Sky’s Insight & Decision Science Team Science the Sh*t out of Stuff - THANK YOU
Many thanks to Gavin Meggs for his excellent presentation about Sky’s customer analytics, and to the Alan Turing institute for hosting. A video of the event is available here: https://www.youtube.com/watch?v=hrTNYKGzPOw
Many thanks to Ashish Umre from Tesco for his insights into digital optimisation analytics in a large corporate environment, and to all who attended and contributed to the lively discussion!
Many thanks to Sophie Sparkes from Tableau for her excellent and entertaining presentation on 25/11/15. Thanks also to Christophe Le Lannou for organising the event, and to the Digital Catapult Centre for hosting us.
Slides are available here:
Rich Huebner is undertaking valuable research into the impact of management involvement on the success of data mining projects. Please take his survey here: https://www.surveymonkey.com/r/tms-and-data-mining