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Information Quality and Data Protection


                 Two sides of the same coin
Introduction

About me, about the presentation
About Me
                                                                Defining & Implementing an
                                                                effective Data Quality
                        Since 2004     Author of
                                                                Strategy, Ark Group 2008
                                                                (ISBN 978-1-906355-14-2)


                        Since 2005
                                           Regular contributor to ComputerScope
                                           Magazine, Running Your Business
                                           (Magazine of Irish Small Firms Association) ,
                                           and the IADQ Newsletter
                        Since 2005         (www.iaid.org/publications)


                        Since 2008



•Graduate of UCD Faculty of Law (Business & Legal Studies),
•Lecturer in Legal Regulation for Information Systems, European Masters in
Business Informatics, Dublin City University
About Me




Winner in 2008 of an Obsessive Blogger award from one of the leading Irish
Blogging Communities for my writing on my personal blog (http://obriend.info)
and elsewhere about Information Quality topics.
About this Presentation
    Crash course in first principles

        Data Protection
    
          European rules… US rules are different and have
           over a dozen different discrete State and Federal
           laws that tackle specific instances of issues….
        Information Quality
    
             Basic principles (very elementary)
        

    Analysis

        Relevance of Information Quality to Data Protection
    
        Relevance of Data Protection to Information Quality
    

    Conclusion

            A detailed handout is available to accompany these slides.
First: Principles

Some fundamentals. Made fun. Not mental.
Conclusion
    Data Protection and Information Quality are inextricably

    linked

    Approaching your Data Protection obligations with an

    “Information Quality Eye” will ensure improved capability
    to comply with regulation while also ensuring information
    in your organisation is of the highest possible quality,
    ensuring customer satisfaction and avoiding other
    regulatory risks.

    Viewing Information Quality and Data Protection as two

    „silo‟ problems deprives you of the potential to add
    greater value to your organisation while managing
    privacy/data protection risks.
Data Protection
DIRECTIVE 95/46/EC OF THE EUROPEAN PARLIAMENT AND OF THE
COUNCIL
SECTION I
PRINCIPLES RELATING TO DATA QUALITY
Article 6
1. Member States shall provide that personal data must be:
(a) processed fairly and lawfully;
(b) collected for specified, explicit and legitimate purposes and not further processed in a
    way incompatible with those purposes. Further processing of data for historical,
    statistical or scientific purposes shall not be considered as incompatible provided that
    Member States provide appropriate safeguards;
(c) adequate, relevant and not excessive in relation to the purposes for which they are
    collected and/or further processed;
(d) accurate and, where necessary, kept up to date; every reasonable step must be taken
    to ensure that data which are inaccurate or incomplete, having regard to the purposes
    for which they were collected or for which they are further processed, are erased or
    rectified;
(e) kept in a form which permits identification of data subjects for no longer than is
    necessary for the purposes for which the data were collected or for which they are
    further processed. Member States shall lay down appropriate safeguards for personal
    data stored for longer periods for historical, statistical or scientific use.
2. It shall be for the controller to ensure that paragraph 1 is complied with.
Data Protection
DIRECTIVE 95/46/EC OF THE EUROPEAN PARLIAMENT AND OF THE
COUNCIL
SECTION I
PRINCIPLES RELATING TO DATA QUALITY
Article 6
1. Member States shall provide that personal data must be:
(a) processed fairly and lawfully;
(b) collected for specified, explicit and legitimate purposes and not further processed in a way
    incompatible with those purposes. Further processing of data for historical, statistical or
    scientific purposes shall not be considered as incompatible provided that Member States provide
    appropriate safeguards;
(c) adequate, relevant and not excessive in relation to the purposes for which they are collected
    and/or further processed;
(d) accurate and, where necessary, kept up to date; every reasonable step must be taken to
    ensure that data which are inaccurate or incomplete, having regard to the purposes for
    which they were collected or for which they are further processed, are erased or rectified;
(e) kept in a form which permits identification of data subjects for no longer than is necessary
    for the purposes for which the data were collected or for which they are further processed.
    Member States shall lay down appropriate safeguards for personal data stored for longer periods
    for historical, statistical or scientific use.
2. It shall be for the controller to ensure that paragraph 1 is complied with.
Data Protection
DIRECTIVE 95/46/EC OF THE EUROPEAN PARLIAMENT AND OF THE
COUNCIL
SECTION I
PRINCIPLES RELATING TO DATA QUALITY
Article 6
1. Member States shall provide that personal data must be:
(a) processed fairly and lawfully;
(b) collected for specified, explicit and legitimate purposes and not further processed in a way
    incompatible with those purposes. Further processing of data for historical, statistical or
    scientific purposes shall not be considered as incompatible provided that Member States provide
    appropriate safeguards;
(c) adequate, relevant and not excessive in relation to the purposes for which they are collected
    and/or further processed;
(d) accurate and, where necessary, kept up to date; every reasonable step must be taken to ensure
    that data which are inaccurate or incomplete, having regard to the purposes for which they were
    collected or for which they are further processed, are erased or rectified;
(e) kept in a form which permits identification of data subjects for no longer than is necessary
    for the purposes for which the data were collected or for which they are further processed.
    Member States shall lay down appropriate safeguards for personal data stored for longer periods
    for historical, statistical or scientific use.
2. It shall be for the controller to ensure that paragraph 1 is complied with.
Fundamental Data Protection Principles
    Obtain the information fairly

    Use only for purposes for which it was obtained

    Process it only in ways compatible with the purposes

    for which it was given to you initially
    Keep it safe and secure

    Ensure that the information is accurate, relevant, and

    not excessive
    Retain it for no longer than is necessary for the

    stated purposes
    Give a copy of the information held by you relating to

    them to an individual when requested
Fundamental Data Protection Principles
    Obtain the information fairly

    Use only for purposes for which it was obtained

    Process it only in ways compatible with the purposes

    for which it was given to you initially
    Keep it safe and secure

    Ensure that the information is accurate, relevant, and

    not excessive
    Retain it for no longer than is necessary for the

    stated purposes
    Give a copy of the information held by you

    relating to them to an individual when requested
Data Protection
    SECTION I
    PRINCIPLES RELATING TO DATA QUALITY
    Article 6
    1. Member States shall provide that personal data must be:
    (a) processed fairly and lawfully;
    (b) collected for specified, explicit and legitimate purposes and not further processed in a way
        incompatible with those purposes. Further processing of data for historical, statistical or
        scientific purposes shall not be considered as incompatible provided that Member States provide
        appropriate safeguards;
    (c) adequate, relevant and not excessive in relation to the purposes for which they are collected
        and/or further processed;
    (d) accurate and, where necessary, kept up to date; every reasonable step must be taken to ensure
        that data which are inaccurate or incomplete, having regard to the purposes for which they were
        collected or for which they are further processed, are erased or rectified;
    (e) kept in a form which permits identification of data subjects for no longer than is necessary
        for the purposes for which the data were collected or for which they are further processed.
        Member States shall lay down appropriate safeguards for personal data stored for longer periods
        for historical, statistical or scientific use.
Give a copybe for the controller to ensure by you relating to them to an individual when
   2. It shall of the information held that paragraph 1 is complied with.
requested
Example of a Bad Data Protection Practice
 “Sign up
for a raffle”




  Lots of
 personal
  data…




    Left completely unattended, along with a box full of more sheets like this one…
Data Protection & Information Quality


                   Mapping the Relationship…
Information Quality


Meeting or exceeding information consumer expectations



     Reducing variation around a mean for the performance and
     perceived value of an information product


          Beauty is in the eye of the beholder
Information Quality


                 Data and Information are of high quality
                      if they are fit for their uses (by
                   customers) in operations, decision-
                  making, and planning. They are fit for
                  use when they are free of defects and
                     possess the features needed to
                    complete the operation, make the
                     decision, or complete the plan.
  Joseph Juran
Information Quality



                 What he said… only the view of the customer
                      needs to be broad enough in your
                                organisation…
                Is having your data lost or stolen a “feature” of
                         the service you are buying?
Dr Tom Redman
Setting & Meeting Expectation
1   Obtain and process the information fairly      Setting Expectation

    Keep it only for one or more specified and
2                                                  Setting Expectation
    lawful purposes
    Process it only in ways compatible with the
3   purposes for which it was given to you         Meeting Expectation
    initially
4   Keep it safe and secure                        Meeting Expectation

5   Keep it accurate and up to date                Meeting Expectation

    Ensure information is accurate, relevant and
6                                                  Meeting Expectation
    not excessive
    Retain information for no longer than is
7                                                  Meeting Expectation
    necessary for the stated purposes
    Give a copy of the information held by you
8                                                  Meeting Expectation
    relating to them to individuals on request
Planning to meet expectations



                 Quality of an asset (product, finance,
                 people) is achieved through
                 •Planning
                 •Control
                 •Improvement

  Joseph Juran
Asset Life Cycle – POSMAD Model
 Asset                                                          Store/Shar
                                 Plan           Obtain                              Maintain            Apply              Dispose
  Life
                                                                     e
 Cycle
                                                                                    What are our     Are we using the
                             What info do I                     Where/how will                                           Do we have a
                                              How will we get                       process to       info for purposes
                             need to                            we store this                                            retention policy
                                                                                    „maintain‟ the
                                              it?                                                    identified @
                             capture?                           info?                                                    for this data?
                                                                                    information?     PLAN
                                                                                    How are we
                                              How will we       Can we find it                       Do we work
   Questions you might ask




                             Why do we                                              keeping our                          Do we retain this
                                              communicate       again when                           with our
                             need it?                                               information up                       data at all?
                                              Hows & whys?      needed?                              suppliers/data
                                                                                    to date?
                                                                                                     service
                                              What are the      Are we storing      How are we
                                                                                                     providers to        How do we
                                              processes we‟ll
                             What will we                       the same data       correcting
                                                                                                     ensure they         dispose of our old
                             use it for?      use to get this   many times in       errors in our
                                                                                                     have adequate       data?
                                              info?             many places?        data?
                                                                                                     procedures in
                                                                What‟s our plan
                                              Will these                            Do our staff     place to protect
                                                                for ensuring                                             Does our data
                             Who will we      processes                             know how/why     the data we
                                                                data integrity                                           become
                             share it with?   capture quality                       we keep info     hold on trust?
                                                                (relating all our                                        “excessive” over
                                              info?                                 up to date?
                                                                records)?                                                time , even if it
                                              Will the
                                                                                    Do our metrics                       was appropriate
                                              processes         Is our data                          Do we protect
                             Why would we                                           and processes                        at the time it
                                              create poor       storage                              copies of data
                             share it?                                              support this                         was captured?
                                              quality           secure?                              on laptops etc?
                                                                                    objective?
                                              information?
                                              What
                                                                Is our data                          Can we find it
                             Am I capturing   processes will                                                             Is our data
                                                                storage                              when we need
                             too much info?   we have to find                                                            disposal secure?
                                                                secure?                              it?
                                              and fix errors?
   DP
                             1,2,3,5,6,7                                                             1.2,3,4,5,6         1.2,3,4,5,6,
                                                1,3,5,6             4,7,8            1,3,5,6,8
Principle
                                 ,8                                                                       ,8                  7
    s
Example of a Bad Data Protection Practice
 “Sign up
for a raffle”




  Lots of
 personal
  data…




    Left completely unattended, along with a box full of more sheets like this one…
Give a copy of the information held by you
  8                                                   Meeting Expectation
         relating to them to individuals on request



A needle in a haystack?

Find ALL the data you have about
ONE specific person based just on
their name, address, other identifying
data… not necessarily an account
number or other unique reference.

For example:
Daragh O Brien, 13 Any Street,
Anytown, Ireland.
Why did I get into Information Quality (an old
slide, but a good slide)
    Daragh

        Darragh
    
        Dara
    
        Darra
    
        Daire
    
        Darach
    
        Darrach
    
        DĂĄire
    
        Daira
    
        Daireach
    

    Gender?

        Male or Female  SPELLING DOES NOT give a clue
    

    Confusion

        Often miskeyed as TARA (definitely female)
    
        Often confused with Darren (male) or Daryl (male or female)
    
        Also confused with Daria (female)
    
        Also confused with Dora (female)
    

    O Brien

        NOT O‟Brien (anglicised version of gaelic name)
    
        Also use O Briain (proper Irish language spelling)
    
        Will accept O‟Brien (mainly out of laziness at this stage)
    

    Grew up on “Foxfield St. John”

        Data cleansing software often changes this to “Foxfield Street John”
    
        Or “St. John‟s, Foxfield”
    
Give a copy of the information held by you
 8                                                Meeting Expectation
     relating to them to individuals on request


Lots of data repositories?
Which haystack?
Give a copy of the information held by you
8                                                Meeting Expectation
    relating to them to individuals on request



Potential duplicate records?
Which needle?
Conclusion
Conclusion
 Information   is an asset
 Its quality can be managed
  and improved just like any
  other asset.
 It should be protected like
 Data Protection and
  Information Quality are
  inextricably linked
Conclusion
    Approaching your Data Protection obligations

    with an “Information Quality Eye” will ensure
    improved capability to comply with regulation
    while also ensuring information in your
    organisation is of the highest possible quality,
    ensuring customer satisfaction and avoiding
    other regulatory risks.
    Viewing Information Quality and Data Protection

    as two „silo‟ problems deprives you of the
    potential to add greater value to your
    organisation while managing privacy/data
    protection risks.

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Information Quality And Data Protection

  • 1. Information Quality and Data Protection Two sides of the same coin
  • 2. Introduction About me, about the presentation
  • 3. About Me Defining & Implementing an effective Data Quality Since 2004 Author of Strategy, Ark Group 2008 (ISBN 978-1-906355-14-2) Since 2005 Regular contributor to ComputerScope Magazine, Running Your Business (Magazine of Irish Small Firms Association) , and the IADQ Newsletter Since 2005 (www.iaid.org/publications) Since 2008 •Graduate of UCD Faculty of Law (Business & Legal Studies), •Lecturer in Legal Regulation for Information Systems, European Masters in Business Informatics, Dublin City University
  • 4. About Me Winner in 2008 of an Obsessive Blogger award from one of the leading Irish Blogging Communities for my writing on my personal blog (http://obriend.info) and elsewhere about Information Quality topics.
  • 5. About this Presentation Crash course in first principles  Data Protection   European rules… US rules are different and have over a dozen different discrete State and Federal laws that tackle specific instances of issues…. Information Quality  Basic principles (very elementary)  Analysis  Relevance of Information Quality to Data Protection  Relevance of Data Protection to Information Quality  Conclusion  A detailed handout is available to accompany these slides.
  • 6. First: Principles Some fundamentals. Made fun. Not mental.
  • 7. Conclusion Data Protection and Information Quality are inextricably  linked Approaching your Data Protection obligations with an  “Information Quality Eye” will ensure improved capability to comply with regulation while also ensuring information in your organisation is of the highest possible quality, ensuring customer satisfaction and avoiding other regulatory risks. Viewing Information Quality and Data Protection as two  „silo‟ problems deprives you of the potential to add greater value to your organisation while managing privacy/data protection risks.
  • 8. Data Protection DIRECTIVE 95/46/EC OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL SECTION I PRINCIPLES RELATING TO DATA QUALITY Article 6 1. Member States shall provide that personal data must be: (a) processed fairly and lawfully; (b) collected for specified, explicit and legitimate purposes and not further processed in a way incompatible with those purposes. Further processing of data for historical, statistical or scientific purposes shall not be considered as incompatible provided that Member States provide appropriate safeguards; (c) adequate, relevant and not excessive in relation to the purposes for which they are collected and/or further processed; (d) accurate and, where necessary, kept up to date; every reasonable step must be taken to ensure that data which are inaccurate or incomplete, having regard to the purposes for which they were collected or for which they are further processed, are erased or rectified; (e) kept in a form which permits identification of data subjects for no longer than is necessary for the purposes for which the data were collected or for which they are further processed. Member States shall lay down appropriate safeguards for personal data stored for longer periods for historical, statistical or scientific use. 2. It shall be for the controller to ensure that paragraph 1 is complied with.
  • 9. Data Protection DIRECTIVE 95/46/EC OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL SECTION I PRINCIPLES RELATING TO DATA QUALITY Article 6 1. Member States shall provide that personal data must be: (a) processed fairly and lawfully; (b) collected for specified, explicit and legitimate purposes and not further processed in a way incompatible with those purposes. Further processing of data for historical, statistical or scientific purposes shall not be considered as incompatible provided that Member States provide appropriate safeguards; (c) adequate, relevant and not excessive in relation to the purposes for which they are collected and/or further processed; (d) accurate and, where necessary, kept up to date; every reasonable step must be taken to ensure that data which are inaccurate or incomplete, having regard to the purposes for which they were collected or for which they are further processed, are erased or rectified; (e) kept in a form which permits identification of data subjects for no longer than is necessary for the purposes for which the data were collected or for which they are further processed. Member States shall lay down appropriate safeguards for personal data stored for longer periods for historical, statistical or scientific use. 2. It shall be for the controller to ensure that paragraph 1 is complied with.
  • 10. Data Protection DIRECTIVE 95/46/EC OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL SECTION I PRINCIPLES RELATING TO DATA QUALITY Article 6 1. Member States shall provide that personal data must be: (a) processed fairly and lawfully; (b) collected for specified, explicit and legitimate purposes and not further processed in a way incompatible with those purposes. Further processing of data for historical, statistical or scientific purposes shall not be considered as incompatible provided that Member States provide appropriate safeguards; (c) adequate, relevant and not excessive in relation to the purposes for which they are collected and/or further processed; (d) accurate and, where necessary, kept up to date; every reasonable step must be taken to ensure that data which are inaccurate or incomplete, having regard to the purposes for which they were collected or for which they are further processed, are erased or rectified; (e) kept in a form which permits identification of data subjects for no longer than is necessary for the purposes for which the data were collected or for which they are further processed. Member States shall lay down appropriate safeguards for personal data stored for longer periods for historical, statistical or scientific use. 2. It shall be for the controller to ensure that paragraph 1 is complied with.
  • 11. Fundamental Data Protection Principles Obtain the information fairly  Use only for purposes for which it was obtained  Process it only in ways compatible with the purposes  for which it was given to you initially Keep it safe and secure  Ensure that the information is accurate, relevant, and  not excessive Retain it for no longer than is necessary for the  stated purposes Give a copy of the information held by you relating to  them to an individual when requested
  • 12. Fundamental Data Protection Principles Obtain the information fairly  Use only for purposes for which it was obtained  Process it only in ways compatible with the purposes  for which it was given to you initially Keep it safe and secure  Ensure that the information is accurate, relevant, and  not excessive Retain it for no longer than is necessary for the  stated purposes Give a copy of the information held by you  relating to them to an individual when requested
  • 13. Data Protection SECTION I PRINCIPLES RELATING TO DATA QUALITY Article 6 1. Member States shall provide that personal data must be: (a) processed fairly and lawfully; (b) collected for specified, explicit and legitimate purposes and not further processed in a way incompatible with those purposes. Further processing of data for historical, statistical or scientific purposes shall not be considered as incompatible provided that Member States provide appropriate safeguards; (c) adequate, relevant and not excessive in relation to the purposes for which they are collected and/or further processed; (d) accurate and, where necessary, kept up to date; every reasonable step must be taken to ensure that data which are inaccurate or incomplete, having regard to the purposes for which they were collected or for which they are further processed, are erased or rectified; (e) kept in a form which permits identification of data subjects for no longer than is necessary for the purposes for which the data were collected or for which they are further processed. Member States shall lay down appropriate safeguards for personal data stored for longer periods for historical, statistical or scientific use. Give a copybe for the controller to ensure by you relating to them to an individual when 2. It shall of the information held that paragraph 1 is complied with. requested
  • 14. Example of a Bad Data Protection Practice “Sign up for a raffle” Lots of personal data… Left completely unattended, along with a box full of more sheets like this one…
  • 15. Data Protection & Information Quality Mapping the Relationship…
  • 16. Information Quality Meeting or exceeding information consumer expectations Reducing variation around a mean for the performance and perceived value of an information product Beauty is in the eye of the beholder
  • 17. Information Quality Data and Information are of high quality if they are fit for their uses (by customers) in operations, decision- making, and planning. They are fit for use when they are free of defects and possess the features needed to complete the operation, make the decision, or complete the plan. Joseph Juran
  • 18. Information Quality What he said… only the view of the customer needs to be broad enough in your organisation… Is having your data lost or stolen a “feature” of the service you are buying? Dr Tom Redman
  • 19. Setting & Meeting Expectation 1 Obtain and process the information fairly Setting Expectation Keep it only for one or more specified and 2 Setting Expectation lawful purposes Process it only in ways compatible with the 3 purposes for which it was given to you Meeting Expectation initially 4 Keep it safe and secure Meeting Expectation 5 Keep it accurate and up to date Meeting Expectation Ensure information is accurate, relevant and 6 Meeting Expectation not excessive Retain information for no longer than is 7 Meeting Expectation necessary for the stated purposes Give a copy of the information held by you 8 Meeting Expectation relating to them to individuals on request
  • 20. Planning to meet expectations Quality of an asset (product, finance, people) is achieved through •Planning •Control •Improvement Joseph Juran
  • 21. Asset Life Cycle – POSMAD Model Asset Store/Shar Plan Obtain Maintain Apply Dispose Life e Cycle What are our Are we using the What info do I Where/how will Do we have a How will we get process to info for purposes need to we store this retention policy „maintain‟ the it? identified @ capture? info? for this data? information? PLAN How are we How will we Can we find it Do we work Questions you might ask Why do we keeping our Do we retain this communicate again when with our need it? information up data at all? Hows & whys? needed? suppliers/data to date? service What are the Are we storing How are we providers to How do we processes we‟ll What will we the same data correcting ensure they dispose of our old use it for? use to get this many times in errors in our have adequate data? info? many places? data? procedures in What‟s our plan Will these Do our staff place to protect for ensuring Does our data Who will we processes know how/why the data we data integrity become share it with? capture quality we keep info hold on trust? (relating all our “excessive” over info? up to date? records)? time , even if it Will the Do our metrics was appropriate processes Is our data Do we protect Why would we and processes at the time it create poor storage copies of data share it? support this was captured? quality secure? on laptops etc? objective? information? What Is our data Can we find it Am I capturing processes will Is our data storage when we need too much info? we have to find disposal secure? secure? it? and fix errors? DP 1,2,3,5,6,7 1.2,3,4,5,6 1.2,3,4,5,6, 1,3,5,6 4,7,8 1,3,5,6,8 Principle ,8 ,8 7 s
  • 22. Example of a Bad Data Protection Practice “Sign up for a raffle” Lots of personal data… Left completely unattended, along with a box full of more sheets like this one…
  • 23. Give a copy of the information held by you 8 Meeting Expectation relating to them to individuals on request A needle in a haystack? Find ALL the data you have about ONE specific person based just on their name, address, other identifying data… not necessarily an account number or other unique reference. For example: Daragh O Brien, 13 Any Street, Anytown, Ireland.
  • 24. Why did I get into Information Quality (an old slide, but a good slide) Daragh  Darragh  Dara  Darra  Daire  Darach  Darrach  DĂĄire  Daira  Daireach  Gender?  Male or Female  SPELLING DOES NOT give a clue  Confusion  Often miskeyed as TARA (definitely female)  Often confused with Darren (male) or Daryl (male or female)  Also confused with Daria (female)  Also confused with Dora (female)  O Brien  NOT O‟Brien (anglicised version of gaelic name)  Also use O Briain (proper Irish language spelling)  Will accept O‟Brien (mainly out of laziness at this stage)  Grew up on “Foxfield St. John”  Data cleansing software often changes this to “Foxfield Street John”  Or “St. John‟s, Foxfield” 
  • 25. Give a copy of the information held by you 8 Meeting Expectation relating to them to individuals on request Lots of data repositories? Which haystack?
  • 26. Give a copy of the information held by you 8 Meeting Expectation relating to them to individuals on request Potential duplicate records? Which needle?
  • 28. Conclusion  Information is an asset  Its quality can be managed and improved just like any other asset.  It should be protected like  Data Protection and Information Quality are inextricably linked
  • 29. Conclusion Approaching your Data Protection obligations  with an “Information Quality Eye” will ensure improved capability to comply with regulation while also ensuring information in your organisation is of the highest possible quality, ensuring customer satisfaction and avoiding other regulatory risks. Viewing Information Quality and Data Protection  as two „silo‟ problems deprives you of the potential to add greater value to your organisation while managing privacy/data protection risks.

Hinweis der Redaktion

  1. Data Quality is explicitly referenced in the EU directive which underpins our data protection regulations. They even go so far as to spell out what the attributes of quality they are concerned with are.
  2. Data Quality is explicitly referenced in the EU directive which underpins our data protection regulations. They even go so far as to spell out what the attributes of quality they are concerned with are.