There s data and then there s big data

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1 There s data and then there s big data Paul Hinton Nicola Fulford Jeremy Harris Chris Wray CCF 2 APRIL 2014

2 US National Intelligence Council s December 2012 Report Global Trends 2030: Alternative Worlds IT is one of four technologies that will shape future global developments information technology is entering the big data era process power and data storage are becoming almost free networks and the cloud will provide global access and pervasive services social media and cybersecurity will be large new markets

3 The stone age involved man's clever use of crude tools; the information age, to date, has seen man's crude use of clever tools. A collection of structured/unstructured data so large/complex that it is difficult to process or analyse using traditional data processing applications. A large and growing gap exists between the amount of data that organisations can accumulate and their abilities to leverage those data in a way that is useful (NIC Report, p. 85/6) Big Data Solutions = (i) hardware; (ii) software; and (iii) often cloud based services capable of analysing and processing Big Data But why? Because by analysing (often via computer algorithim) vast amounts of information from multiple sources we can gain deep insights into underlying facts and trends.. _3

4 A vertical model for the data-centric world

5 focusing on the different types of data & their legal attributes

6 The Big Data Analytical Horizontal Model Input Data Big Data Factory Output Data Social Media Live data feed Internal structured data Third party review Third Party Data Transaction data Big Data Storage Platform Cloud? Algorithm Search engine database Question Regular Report Internal unstructured Data

7 The Big Data Analytical Horizontal Model _7

8 in the context of organisations big data operations

9 Unforseen consequences Plans Change _9

10 BIG Data Talk Data Protection Nicola Fulford IP Rights and Big Data - Jeremy Harris BREAK Data Contracts Paul Hinton The Solution - Data Process and Management Chris Wray _10

11 Big Data Data Protection Implications NICOLA FULFORD Privacy & Data Protection Partner 2 APRIL 2014

12 A vertical model for the data-centric world _12

13 Big Data regulation: What is personal data? Data Protection Act 1998: Data which relate to a living individual who can be identified from those data or from other information in the [controller s] possession including opinions about or intentions in respect of that person Personal data is being processed where information is collected and analysed with the intention of distinguishing one individual from another and to take a particular action in respect of an individual even if no obvious identifiers, such as names or addresses, are held Information Commissioner s Office Guidance _13

14 Big Data: And sensitive personal data? Commission / alleged commission of an offence or related court proceedings Sexual life Racial / ethnic origin Physical or mental health Personal data consisting of information as to Political opinions Membership of a trade union Religious beliefs _14 must satisfy one of the conditions for sensitive processing and take additional security steps

15 Big Data Regulation: Examples of personal data There is a lot of personal data out there: location tracking facial recognition wearables social media fitness apps hospital outcomes the Internet of things call recordings communications meta data supermarket loyalty schemes cookies smart meters YouTube etc. videos CCTV / ANPR _15 Beware many of these are likely to also include sensitive personal data

16 Big Data: Compliance with the DP principles Adequate protection outside EEA Fair & lawful Kept secure Purpose limitation Big Data Comply with subjects rights Adequate, relevant and not excessive Retention limits Accurate & up to date _16

17 Big Data regulation: examples of regulatory guidance ICO? ICO Code of Practice on Anonymisation Article 29 Working Party? Opinion on Purpose Limitation European Data Protection Supervisor? Opinion on privacy and competitiveness in the age of Big Data Federal Trade Commission? Investigation into data brokers.comments by European Digital Chief Neelie Kroes in March 2014 _17

18 And the proposed Data Protection Regulation? Current status? Commission and Parliament have each agreed their own positions and texts Council is still discussing its position: nothing will be agreed until everything is agreed Next steps: trilogue negotiations May be agreed end 2014?? / in force from 2017??? _18

19 And the proposed Data Protection Regulation? Key points that are likely to impact heavily on the use of big data fines of up to 100m or 5% of worldwide turnover cookies and IP addresses will constitute personal data profiling restricted extra-territorial effect direct obligations on processors right to erasure for individuals _19

20 Big Data and IP JEREMY HARRIS IP & LITIGATION PARTNER 2 APRIL 2014

21 The Big Data Factory Input Data Big Data Factory Output Data Social Media Live data feed Internal structured data Third party review Third Party Data Transaction data Big Data Storage Platform Cloud? Algorithm Search engine database Question Regular Report Internal unstructured Data

22 IP & Big Data Understanding how IP fits in with Big Data means knowing: what you are getting from where when how under what circumstances, and how you re using it It s worth looking at the IP position in terms of input and output data

23 Input Data Different types of data from many sources Is there a licence in place? Does it matter from an IP perspective? Not really: if there is no licence in place, it doesn t mean that there are no IP rights in the data even if there is a licence in place, still need to understand the IP position breach of licence could constitute infringement of IP, but the measure of damages for IP infringement is different to breach of contract Licence might include indemnity against losses incurred as a result of infringement of third party IP both from licensor to licensee and licensee to licensor

24 What rights might there be? Database Right Database Copyright Literary Copyright Confidence

25 Database Right Is there a qualifying database? a collection of independent works, data or other materials arranged in a systematic or methodical way and individually accessible by electronic or other means (Art 1(2) DD) Does the right subsist? qualitatively and/or quantitatively a substantial investment in either the obtaining, verification or presentation of the contents.. (Art 7(1) DD) who created the data? remember BHB v William Hill the investment in obtaining, verifying or presenting protects resources used to seek out independent material therefore, resources used for the creation of the data are not protected contrast with recent case Football DataCo v Sportradar data collected and recorded at a live events - the compiler of this information had little control over it and it was therefore not created by that person but merely obtained by them

26 Database Right Would use of the data constitute an infringement? Extraction or reutilisation of a substantial part (quantitatively or qualitatively); or Repeated extraction or reutilisation of insubstantial parts Substantial part: quantitative evaluation - proportion of the volume of data lifted in relation to the total volume of the contents of the database qualitative assessment small part of the database which requires significant human, technical or financial investment, may amount to a substantial part evaluated qualitatively look at the scale of investment in obtaining, verifying or presenting the part taken Accordingly, you need to look at how much data is being taken how often how important it is

27 Database Copyright Is there a qualifying database? Same definition as for database right Does the right subsist? Protection if, by reason of the selection or arrangement of the contents of the database the database constitutes the author s own intellectual creation (section 3A CPDA) what exactly is the author s own intellectual creation? Football DataCo v Brittens Pools/Yahoo = an original expression of the creative freedom of the author (which is a matter for the national court to determine) Accordingly: concept of selection and arrangement does not extend to the creation of the data contained in the database must be some creative ability in an original manner by making free and creative choices as to selection/arrangement

28 Copyright Is there a copyright work? Original creation? Literary merit? Skill, labour & judgment - no longer relevant the test is whether it constitutes the author s own intellectual creation (Infopaq) Infringement: would taking the data constitute an an infringing act? has a substantial part been taken, whether on a quantatitive or qualitative basis? quality is more important

29 Confidence Are there obligations of confidence in place? Is the data stated to be confidential? Website terms? Circumstances under which reasonable person would understand it to be confidential?

30 Output data Is IP being created in the output process? What are you doing with the data? manipulation of the data in a new/different way incorporation with other data sets creation of master database producing reports Is there any: investment in obtaining, verifying or presenting? intellectual creativity in selection and arrangement?

31 BREAK Data Contracts Paul Hinton The Solution - Data Process and Management Chris Wray

32 Contracting for Big Data licensed content Navigating the gap PAUL HINTON COMMERCIAL TECHNOLOGY PARTNER 2 APRIL 2014

33 Contracting for Big Data content Licensing requirements Input data standard contracts Output data - key terms Conclusion _33

34 The Big Data Factory Input Data Big Data Factory Output Data Social Media Live data feed Internal structured data Public Data Social Media Data Transaction data Big Data Storage Platform Cloud? Algorithm Search engine database Question Regular Report Internal unstructured Data _34

35 Licensing requirements Input data Ensure that all input data can be used for all Big Data purposes ideally (i) assignment; or (ii) a broad worldwide, irrevocable, perpetual, licence to do anything.. Assuming this is not always possible; What will the data be used for? By whom? Internal v external? Will the data be relied upon for anything? _35

36 Input data - standard contracts Even if no licence applies access can be made subject to a licence at any time once data obtains value this tends to happen Many standard licences prohibit such use: General website terms and conditions You are not permitted (except where you have been given express permission to do so) to adapt or modify the Information on this Website or any part of it and the Information or any part of it may not be copied, reproduced, republished, downloaded, stored, databased, posted, broadcast or transmitted in any other way to any third parties for commercial gain. They can be amended at any time.. _36

37 Input data - standard contracts - social media Contracts your use of data Terms include Only request data that you need for your application Must not include data in any search engine or directory without FB consent Cannot include user data in an advertising creative EVEN if user consents Cannot transfer data to advertising network Cannot sell data FB can force you to delete data if your use is inconsistent with user expectations Terms include Not to store on non-public user profile data or content Cannot use the Twitter API to aggregate geographic location information contained in Twitter Content May not use Twitter Content or other data collected from end users to create or maintain a separate status update or social network database or service Don t sell access to the Twitter API or Twitter Content T s consent Terms include They say very little for now Reflects the limited data flow presently available on this platform Includes general restriction on use of Pinterest Content you cannot use, modify, reproduce, distribute, sell, license, or otherwise exploit it without Pinterest s permission. _37

38 Input data Typical licence issues = CHARGES Key issue for Licensor is that Big Data does not = substitute for original data Ideally = flat fee for all Big Data use Charges per individual licensed users or queries What if data only forms a small part of query? What if the enquiry is a one-off? If individual or search fees charged= complex previsioning system _38

39 Input data market data derived data Derived data: data of any kind containing Data or any part of it and/or resulting directly or indirectly from the manipulation or analysis of Data (whether generated by human or machine) whether alone or in conjunction with other data regardless of whether or not the Data is in any way identifiable from or within such data by any means; Standard positions: Derived data distribution permitted Permitted but not backwards calculable Prohibits distribution of derived data _39

40 Input data market data warranties and liability How much can Big Data be relied upon? Calculated in accordance with specification Damages capped at fees IP Indemnity uncapped No warranties as to accuracy as is as available not to be relied upon No IP warranty/indemnity data itself perhaps not verified if from third parties what if created by licensor? no remedy/reasonableness UCTA unreasonable exclusion _40

41 Input data market data audit The Licensee shall permit [ ] to access to and monitor the use of the Licensee's system used to distribute the Data, in order to verify that the use of the Data by the Licensee is in accordance with this Agreement and that Charges due under this Agreement have been calculated and paid correctly. No audit Full audit and downstream audit right to licensees Confidentiality clauses relevant to other data - insert explicit licence for third party auditors - but some of these will be competitors. _41

42 Input data financial services market data Exit Often delete/purge obligations No deletion Purge all data from all systems involved _42 Carve outs: reports already sent out? record keeping for regulatory requirements? record keeping to enable protection of claims?

43 Output Data - Metered Access key terms Reflect upstream data input obligations accurately Avoid sole reliance upon IP rights Contract is king - Etherton J in At the races v BHB (2005) The ideal is to create metered access to data subject to contract at each stage: Impose clear rights explicitly drafted as obligations into a contract Licence Clauses - set out only what may be done in detail reserve all other rights Contract neutral and able to be flexible adapt where possible by reference to other documents that can change Post Termination Rights do not presume the licence will be implied to terminate Regina Glass Fibre v Schuller [1972] FSR 141 if the Licensee will not be able to enjoy the benefit of what he has paid for. Explicitly set out what must be done post termination purge

44 Key Data licence contract terms conclusions Big Data requires significant legal input and a clear legal methodology and lead to ensure compliance and to maximise value Back to front understanding outputs and system capability critical before negotiating input agreements Input data licences are likely to need careful contract review and negotiation Output data licences will need to be carefully drafted, flexible and updated If complex licensed rights are asserted to data within the Big Data Factory system capabilities will be needed to ensure output compliance: (i) data tracking; (ii) limit access to or use of data; (iii) attach terms/attributions to data; and (iv) delete/remove data how quickly/efficiently Data strategy, policies, process and data management framework technological solution _44

45 There s data - and then there s big data Management and compliance challenges CHRIS WRAY KEMP LITTLE CONSULTING PARTNER 2 APRIL 2014

46 A vertical model for the data-centric world

47 Towards big data management and compliance INPUT PROCESS OUTPUT Multiple sources provide data Multiple operations process data Multiple purposes use data Public domain Market data Personal data Confidential data Licensed data Government data Employee data Self-generated and derived data 3 rd party applications Secret sauce algo Pan enterprise search One view of information Data re-purposing Employee data Internal use Product dev Sales & Marketing CRM Management Finance External use

48 Practical steps towards big data management Step 1: Risk Assessment structured process to review/assess/report/remediate involve all parts of the business establish all the types of data your organisation is using & their sources where does the data come from? what consents were obtained/are needed? what legal wrappers apply to all this data IPR, contract, regulatory, etc what processes do these datasets undergo? what does your organisation use this data for? data protection environment is reasonably mature use this as a start point?

49 Practical steps towards big data management Step 2: Strategy Statement the start point that everything is referable back to high level statement of organisation s goals relating to big data list stakeholders - top management and all parts of the business bought in rationale, scope, governance, etc

50 Practical steps towards big data management Step 3: Policy Statement next level down people context: stakeholder groups, their interests & how they are achieved steering group, working party, compliance officers, etc project plan scope, responsibilities, timelines, etc state tools to be used (mix of IT/system measure & processes & procedures approvals, etc

51 Practical steps towards big data management Step 4: Processes and Procedures applicable to all staff tie in to HR policies, etc proportionate processes & procedures to be followed IT system/measures & how they re to be used awareness training

52 The importance of a logic data model End to End Scenarios Computer Independent Model Business Information Model End to End Processes & Activities Platform Independent Model Logical Data Model Integration Processes Platform Specific Model Integration Specific Data Model Application Specific Data Model Database Specific Data Model Data Warehouse Specific Data Model IT Systems & Components Public Cloud Private Cloud Hybrid Cloud On Premise _52

53

54 Questions?

55 Our People Nicola Fulford Commercial Partner Paul Hinton Commercial Partner Jeremy Harris Commercial Partner Chris Wray Partner, KL Consulting _55

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