There s data and then there s big data

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1 There s data and then there s big data Richard Kemp Paul Hinton Jeremy Harris CCF 15 TH JANUARY 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 impact of big data is all about knowing your customer and the competitive advantage that confers Information Technologies Technology focus Current status Potential for 2030 Issues Impact Data solutions Large data sorting and analysis is applied in various large industries, but the quality of data accumulating is outstripping the ability of systems to leverage it efficiently. As software and hardware developments continue, new solutions will emerge to allow considerably more data to be collected, analysed and acted on. The greatest areas of uncertainty are the speed with which big data can be usefully and securely utilised by organisations. Opportunities for commercial organisations and governments to know their customers better will increase. These customers may object to the collection of so much data. Since modern data solutions have emerged, big data sets have grown exponentially in size. At the same time, the building blocks of knowledge discovery, and the software tools and best practices available to organisations that handle big data sets, have not kept pace with such growth. So a large - and rapidly 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)

4 An analytical model for the data-centric world

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

6 in the context of organisations big data operations

7 in the context of organisations big data operations 1. Input data from multiple sources public domain market data social media personal data confidential data licensed data government data employee data self-generated and derived data

8 in the context of organisations big data operations 1. Input data from 2. Processing operations multiple sources public domain market data social media personal data confidential data third party applications secret sauce algo pan enterprise search one view of information data re-purposing licensed data government data employee data self-generated and derived data

9 in the context of organisations big data operations 1. Input data from multiple sources 2. Processing operations 3. Output data for multiple purposes public domain market data social media personal data confidential data licensed data government data employee data third paty applications secret sauce algo pan enterprise search one view of information data re-purposing - for internal use product development sales & mktg CRM management finance - for external use - self-generated and derived data

10 Big Data and IP JEREMY HARRIS 15 TH JANUARY 2014

11 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

12 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

13 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

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

15 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

16 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

17 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

18 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

19 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?

20 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?

21 Contracting for Big Data content Navigating the gap PAUL HINTON 15 TH JANUARY 2014

22 Contracting for Big Data content Licensing requirements Input data standard contracts FS market data contract terms Output data - key terms Conclusion _22

23 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 _23

24 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? _24

25 Licensing requirements Input data Plans Change _25

26 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.. _26

27 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. _27

28 Input data financial services market data Financial Services Market Data = a mature data licensing market licensor maximises control of data and income from downstream use Historic data v Live data Internal licence v External Distribution licence and charge Licensor controls any directly competing redistribution and requires direct licence or identikit sub-licence Use for trading on a platform/analysing v creating separate tradeable product Do not generally enable broad Big Data use per se but new licences and charging mechanisms developing _28

29 Input data financial services market data licence and charges Ideally = flat fee or easily calculable fee for Big Data use Key issue for Licensor is that Big Data does not = substitute for original data Typical charges based upon individual traceable licensed users charges per user What if upstream data only forms a small part of Big Data query? What if the enquiry is a one-off? Can use be tracked? _29

30 Input data financial services 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: prohibited distribution of derived data permitted only if no part of original data shown or backwards calculable owned by original licensor and report/track licence and charge data use _30

31 Input data financial services market data warranties How much can Big Data be relied upon? Warranties as to accuracy as is as available not to be relied upon data itself perhaps not verified if from third parties what if created by licensor what if derived by calculation by licensor can warrant calculation accurate no remedy/reasonableness _31

32 Input data financial services market data attribution display the [Trade Marks] at all times in accordance with the Permitted Distribution Policy solely in connection with the grant of licence in clause [ ]. practical or possible? will data be individually discernible? _32

33 Input data financial services market data audit The Licensee shall permit [ ] to audit and inspect: the Licensee's accounts, records and other information and permit it to take copies or extracts and on demand supply copies to [ ] of such information; any information in the Licensee's control that relate to any Subscriber; 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. Is this possible/practical/desirable? Confidentiality clauses relevant to other data - insert explicit licence for third party auditors - but some of these will be competitors. Alternative and lesser obligations _33

34 Input data financial services market data Exit Often delete/purge obligations the Licensee must stop using the Data and the Trade Marks and purge its systems of all Data Is this possible? Also: what about reports already sent out? record keeping for regulatory requirements? record keeping to enable protection of claims? _34

35 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

36 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 _36

37 Big data regulatory aspects information management Richard Kemp CCF 15 TH JANUARY 2014

38 Regulatory aspects of big data

39 Different legal areas where regulatory duties around data arise 1 - generic Data Protection UK s ICO has powers to fine up to 500,000 current progress of draft Data Protection Regulation LIBE European Parliament Committee compromise amendments approved on 21 October 2013 At the moment, fines of upto the greater of 100m or 5% ww turnover if greater Likely in force date 2015 Most Enterprise and many SME orgs have in place formal data protection compliance policies & processes can be used as the basis for big data compliance?

40 Different legal areas where regulatory duties around data arise 2 sector specific Financial services MiFID equity trading rules pre- & post- trade data transaction reporting Market data source/exchange rules Air Transport Industry (ATI) Passenger Name Record (PNR) data Fares data GDS (Amadeus, Worldspan, etc) Airline websites Mobile check in, etc MiFID II will extend to other asset classes Market Abuse, Capital Adequacy directive requirements alleged LIBOR, forex market manipulation

41 Different legal areas where regulatory duties around data arise 2 sector specific Professional services e.g. legal services regulatory client confidentiality rules rules on conflicts of interest privilege rules Healthcare clinical outcomes data aggregated and anonymised? sensitive personal data litigation privilege legal professional privilege

42 Different legal areas where regulatory duties around data arise 3 competition law Articles 101 and 102 EU Treaty (Chapters I & II Competition Act 1998) Competition authorities becoming more vigilant around commercial practices for supplying and licensing data Article 101/Chapter I concerned with anti-competitive agreements Article 102/Chapter II concerned with abusive conduct by market powerful orgs Two cases around securities identifiers the financial services area S&P & CUSIPs, Thomson Reuters and RICs Markit & CDSs (Credit Default Swaps)

43 Towards big data management and compliance

44 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 data undergo? what does your organisation use these data for? data protection environment is reasonably mature use this as a start point?

45 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

46 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

47 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

48 Our People Richard Kemp Senior Partner Paul Hinton Commercial Partner Jeremy Harris Commercial Partner _48

49 Questions?

50 Upcoming events in 2014 If you would like to attend either of the following events, please contact 5 th February HR Forum Tweaking your business for success in nd April - There s data and then there s big data (re-run) We will also be running events on the following topics over the next couple of months we will contact you with further information: Cloud Data Protection

51 Contact info KEMP LITTLE Cheapside House 138 Cheapside London EC2V 6BJ TEL +44 (0) FAX +44 (0) kemplittle.com Kemp Little LLP is a limited liability partnership registered in England and Wales (registered number: OC300242) and is authorised and regulated by the Solicitors Regulation Authority. Its registered office is Cheapside House, 138 Cheapside, London EC2V 6BJ. A list of members is open to inspection at the registered office. _51

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