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ODI Maturity Model: Guide - Assessing your open data publishing and use
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Transcript of ODI Maturity Model: Guide - Assessing your open data publishing and use
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Open Data Maturity Model | Open Data Institute 20151
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Open Data Maturity Model | Open Data Institute 20152
Table of Contents
How to view and download the Open Data Maturity Model 3
Executive summary 3
Foreword 3
Introduction Backgroundandhistory Developingthemodel Acknowledgements
5
Overview of the Open Data Maturity Model Howisthemodelstructured? Howdoesthemodelrelatetoexistingwork? Whatisthescopeofthemodel? Howcanthemodelbeapplied?
8
The five maturity levels 10
The five organisation themes and related activities 11
The two aspects of open data practice - publication and reuse 12
How to perform an assessment Settinganassessmentprocess Prioritisingandaligningyouractivities
12
Theme 1. Data management processes Buildingaprocesstosupportdatarelease Developingstandardsandadoption Developingdatagovernance Managingsensitivedata
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Theme 2. Knowledge and skills Developingopendataexpertise Knowledgemanagement
20
Theme 3. Customer support and engagement Developinganengagementprocesswithdatareusers Documentingyouropendata Buildingareusersupportprocess Creatingopendatacommunitynorms
23
Theme 4. Investment and financial performance Ensuringfinancialoversight Developingdatasetvaluationprocesses Buildingopendataintoprocurementpractices
27
Theme 5. Strategic oversight Shapingopendatastrategy Assetcataloguemanagement
30
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How to view and download the Open Data Maturity Model
TheOpenDataMaturityModelisavailabletoexploreonlineanddownloadasaGoogleDoc,ExcelfileandPDFat:http://theodi.org/guides/open-data-maturity-model
Executive summary
TheOpenDataMaturityModelisbeingdevelopedbytheOpenDataInstituteandtheDepartmentforEnvironment,Food&RuralAffairstohelp organisations assess how effectively they publish and consume open data.
Themodelsupportstheassessmentofoperationalandstrategicactivitiesaroundopendata,providesguidanceonpotentialareasfor improvement,andhelpsorganisationscomparethemselvesagainstoneanothertohighlighttheirrespectivestrengthsandweaknesses,adoptbestpracticesandimprovetheirprocesses.
Themodel isbasedaroundfive themes,eachrepresentingabroadareaofactivity:data management processes, knowledge and skills, customer support and engagement, investment and financial performance and strategic oversight.Anassessmentgridhelpsorganisationsidentifytheirlevelsofmaturityforeachoftheactivities.
Organisationscanusethemodeltosetthemselvesappropriategoalsbasedontheircurrentmaturity,resourcingandanticipatedbenefits.Toachievethefull,long-termbenefitsofopendata,organisationsmusttakestepsbeyondbasicdatapublication,theassessmentofopendatapublishingandconsumptionisastrongstartingpoint.
WhilethemodelhasbeeninitiallydevelopedforaUKpublicsectoraudience,itcanalsobeappliedtoanytypeoforganisationwith littleornomodification,whethertheyarealreadypublishingorconsumingopendata,orareplanningtodoso.
Foreword
Thefirstchallengesthatmanyorganisationsfacewhenbecomingopendatapublishersaretechnical,largelycentredaroundhowtopublishdataineasy-to-useformatswithclearlicensing.
Ifreusersaretohavereliable,sustainableaccesstopublisheddatathenpublisherswillneed
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toconsiderthesechallengesaswellasthestrategic,financialandoperational impactsofmakingtheirdataopen.
Understandingthisorganisationalchangeisanimportantaspectofbecominganeffectiveopendatapublisher.Similarchangestakeplaceasorganisationsbegintoreapthebenefitsofreusingopendatatoreducecosts,increaseefficiencyandtodriveinnovation.
Organisationsareatdifferentstagesinthisopendatajourney.Someareonlyjustbeginningtopublishdata,whileothershavealreadyundergonesignificantchangestowardsamoreopenbydefaultmodel.Manyareseekingguidanceabouthowtotakethenextstepsintheirjourney.
ThegoalofthisOpenDataMaturityModelistohighlightissuescommonlyencounteredbypublishers,andprovideameansfororganisationstoassessandimprovetheireffectivenessaspublishersandconsumersofopendata.Thematuritymodelprovidesaframeworkforunderstandingthedifferentareasoforganisationalchangetowardsopendata,whilealsoidentifyingthebenefitsofthatchange.
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Introduction
TheOpenDataMaturityModelisbeingdevelopedtosupportorganisationsinassessingtheireffectivenessinpublishingandconsumingopendata.
WhilethemodelhasbeeninitiallydevelopedforaUKpublicsectoraudience,itcanalsobeappliedtoanytypeoforganisationwith littleornomodification,whethertheyarealreadypublishingorconsumingopendata,orareplanningtodoso.
Themodel:
supportsassessmentoftheeffectivenessofanorganisationinitsoperationalandstrategicactivitiesaroundopendata
providesguidancetoorganisationsonpotentialareasforimprovement comparesorganisationstohighlighttheir respectivestrengthsandweaknesses,
supportwideradoptionofbestpracticesandhelpimproveprocesses
Withthesepurposesinmind,themodelcanbeusedbybothdatamanagersworkingwithinindividualbusinessunitsandseniormanagementwithoversightondatamanagementandgovernancepractices.
Themodelshouldnotaddunnecessaryburdentoorganisationsthatarepublishingorreusingopendata,rather,theycanuseittosetthemselvesappropriategoalsbasedontheircurrentmaturity,resourcingandanticipatedbenefits.
Toachievethefull, long-termbenefitsofopendata,organisationsmusttakestepsbeyondbasicdatapublication,theassessmentofopendatapublishingandconsumptionisastrongstartingpoint.
WithintheUKpublicsectortheOpenDataMaturityModelshouldbeparticularlyrelevanttoorganisationsresponsibleformanagingaspectsoftheUKNationalInformationInfrastructure1.Theseorganisationsshouldhaveaclearviewoftheiropendatamaturityandhaveappropriatetargetsfordevelopment.
1 NationalInformationInfrastructure,https://www.gov.uk/government/publications/national-information-infrastructureaccessedon2015-03-19
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Background and history
TheOpenDataMaturityModelwasdevelopedasa jointprojectbetweentheOpenDataInstitute2(ODI)andtheDepartmentforEnvironment,Food&RuralAffairs(Defra)3.
TheDefraNetworktransparencypanel identifiedaneedtomeasuretheeffectivenessandtransparencyoftheDefranetworkorganisationsasopendatapublishers.Thepanelfeltthatbetterunderstandingofrelativematuritywouldhelptodrivetheorganisationalchangerequiredtopromoteopendatapublishing.
Defraand theODIwereawarded funding todevelopamaturitymodelandaprototypeassessmenttoolundertheReleaseofDataFund4administeredbytheCabinetOfficeandtheOpenDataUserGroup.
Developing the model
WebegantodeveloptheOpenDataMaturityModelbydrawingontheresultsofaseriesofrequirementsworkshopsattendedbydatamanagersandopendataexpertsfromtheUKgovernmentandwideropendatacommunity.
Theattendeesdiscussedanumberofkeythemesthoughttobecomponentsofdatagovernanceandmanagementpractices.Eachthemewasreviewedtoidentifykeychallenges,outputs(suchaspolicydocuments),andevidenceforprogression.
Therequirementsworkshopsweresupplementedwithadditionalresearchondatagovernanceandmanagementpractices.Somecomparativeresearchonthedesignanddevelopmentofmaturitymodelswasalsodrawnonduringtheanalysis.
Wepublisheddraftversionsofthisdocumentandtheassessmentgridforpubliccomment.Wereviewedfeedbackandincorporateditintothefinaldocuments.
Weintendtoreviseandextendthemodelinfuturebasedonexperiencewithapplyingitinreal-worlduse.Anonlinetoolwillalsobeprovidedtosupportorganisationsinassessingtheirmaturity.
2 OpenDataInstitute,http://theodi.org,accessedon2015-02-04
3 DepartmentforEnvironment,Food&RuralAffairs,https://www.gov.uk/government/organisations/department-for-environment-food-rural-affairs,accessedon2015-02-04
4 BreakthroughFundandReleaseofData,https://www.gov.uk/government/publications/breakthrough-fund-and-release-of-data-fund,accessedon2015-02-4
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Acknowledgements
DefraandtheODIwouldliketojointlythankalloftheattendeesoftherequirementsworkshopsfortheircontributionstothedevelopmentofthematuritymodel.Wewouldalsoliketothankeveryonefromacrosscentralandlocalgovernment,agenciesandotherorganisationswhoprovidedfeedbackonthedraftdocuments.Thecontributionsand ideaswereextremelyvaluable.
ThefundingandsupportfortheprojectfromtheCabinetOfficeandtheOpenDataUserGroup(ODUG)5wereessentialinmakingthemodelareality.
5 OpenDataUserGroup,https://www.gov.uk/government/groups/open-data-user-group,accessedon2015-03-20
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Overview of the Open Data Maturity Model
Amaturitymodelgenerallyprovidesaframeworkthatallowsanorganisationtoassesshowwell itsprocessesconformto industrybestpractices.Themodelactsasan independentbenchmarkthatallowsorganisationstoscoretheirmaturity,usuallyinanumberofrelatedareas.
TheOpenDataMaturityModelhasbeendesignedtospecificallyfocusonhowopendatapracticeimpactsonanorganisation.
Acompletedassessmentagainstthismodelwillgiveanorganisationamaturity scoreforanumberofimportantactivities,namelyhow data is released, how it is governedandhow datasets are valued.Thescorewillreflectthematurityoftheorganisationsprocessesinaspecificareaandcanbeusedtoidentifyareasofimprovementandsetmeasurabletargets.
How is the model structured?
TheOpenDataMaturityModelconsistsof15organisationalactivities,e.g.datareleaseprocessesoradoptionofcommunitynorms,whichareeachexplainedinthispaper.
Theactivitiesaregroupedintofivethemesthatcategorisetheactivities.Thesehavebeenderivedfromthecategoriesused inabalancedscorecard6 toassessandmonitororganisationalperformance.Thisreflectsthegoaltoassessthevarietyofwaysinwhichopendatapracticemayimpactonanorganisation.
Activitiescanalsobegroupedaccordingtowhethertheyrelatetothepublicationofdata,reuseofdataorbothoftheseareas.Thesearereferredtoasaspects.
Theoverallstructureofthemodelisreflectedintheassessmentgridthataccompaniesthispaper(seeAppendix).Werecommendthatyoureviewthegridalongsidethisdocument.
Anorganisationwillassessitsmaturityagainsteachoftheactivitiesinthemodel,producingamaturityscorefrom1-5foreachactivity.Thesefivematurity levelsusenamesdrawnfromsimilarfive-pointschemesinothermaturitymodels:initial,repeatable,defined,managed,andoptimising.
Eachofthematuritylevelshasadefinitionwhichdescribesthekeycharacteristicsofanactivityoccurringatthatlevel.Forlowerscores,activitiesarelikelytobeadhoc,whileathigherlevelsprocesseswillbemorerefined.
6 BalancedScorecard,http://en.wikipedia.org/wiki/Balanced_scorecard,accessedon2015-01-30
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Tohelpmotivateorganisationstoprogressthroughthelevelsofmaturity,eachoftheactivitiesisassociatedwithadescriptionofthebeneficial effectsthatfollowfromincreasedmaturityintheactivity.
Thevariouselementsofthemodelarecoveredinmoredetaillaterinthepaper.
How does the model relate to existing work?
Whilethereareotherefforts78,toassessmaturityofdatamanagementandgovernancepractices,theseexistingmodelsdonotadequatelyaddresstheissueofopendata.
TheOpenDataMaturityModelhasbeendevelopedwithreferencetoexistingmaturitymodelsthatmeasureotherareasoforganisationalmaturity9.OrganisationsthatarealreadyapplyingothermaturitymodelsshouldfindthattheOpenDataMaturityModelalignswellwithotherapproaches.
ThemodelalsocomplementstheOpenDataCertificates,whichprovidepublisherswithfeedbackonhoweffectivelytheyarepublishingindividualdatasets10.TheOpenDataMaturityModelassesseseffectivenessattheorganisationallevel.Matureorganisationswillbeabletoroutinelypublishdatasetsthatarelikelytogainahigherlevelofcertification.
What is the scope of the model?
TheOpenDataMaturityModelisnotintendedtoofferaprescriptivedescriptionofexactlyhoworganisationsshouldpublishorreuseopendata.Rather,themodelfocusesonthegeneralbehavioursthatanorganisationshouldexhibitandtheprocessesitshouldadopt.
Forexample,themodelhighlightsdatagovernanceasan importantorganisationalactivity.Itsuggests thata robust,well-definedandwidelydeployeddatagovernanceprocess isacharacteristicofamatureopendataorganisation.Themodelalsonotesthatawell-designeddatagovernanceprocesswillinvolveclearownershipoverdataandcoverelementssuchasdataqualitymanagement.However,itdoesnotrecommendaspecificdatagovernanceprocessthatorganisationsshouldadopt.
7 IBMDataGovernanceCouncilMaturityModel,https://www-935.ibm.com/services/uk/cio/pdf/leverage_wp_data_gov_council_maturity_model.pdf,accessedon2015-03-25
8 StanfordDataGovernanceMaturityModel,http://web.stanford.edu/dept/pres-provost/irds/dg/files/StanfordDataGovernanceMaturityModel.pdf,accessedon2015-03-25
9 See,forexample:CapabilityMaturityModel,http://en.wikipedia.org/wiki/Capability_Maturity_Model,accessedon2015-01-30
10 OpenDataCertificates,https://certificates.theodi.org,accessedon2015-03-19
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Open Data Maturity Model | Open Data Institute 201510
Individualorganisationsshouldimplementtheseprocessesbasedontheirneeds.Itwouldbeoverlyprescriptiveforthismodeltorecommendprocessesthatcouldbeusefullyappliedineveryorganisation.
Whileweexpectthatbestpracticeswilleventuallyemergeformanyoftheseareasofactivity,thatdetailisoutsideofthescopeofthematuritymodel.
How can the model be applied?
Thestructureofthemodelallowsittobeappliedinseveralways:
It canbeused toproduceasinglematurityscoreprovidingasummaryofanorganisationsoverallmaturity
Itcanproducescoresforindividualthemes,allowinganorganisationtofocusonbroadareasthatmayneedspecificimprovement
Itcanproducescoresforindividualactivities,givingamoredetailedassessmentofanorganisation
Itcanbeusedtoassessmaturityasanopendatapublisherorasanopendataconsumer
Importantly,weintendthemodeltobeactionable:itshouldbepossibletousethemodeltobothsetandmonitorgoalsfororganisationaldevelopment,andasasourceofguidanceonimplementingimprovements.
The five maturity levelsTheOpenDataMaturityModelisbasedonfivelevelsthatrepresentthedifferentstatesthroughwhichanorganisationwillpassasitmatures.Advancingtothenextstageinvolvescreating,developingandrefiningspecificbusinessactivitiesandprocesses.
Settingasidethedetailsofindividualactivities,thelevelsthemselvescanbecharacterisedasfollows:
1. Initial thedesirableprocessesarenon-existentoradhoc,withnoorganisationaloversight.
2. Repeatableprocessesarebecomingrefinedandrepeatable,butonlywithinthescopeofindividualteamsorprojects.Therearenoorganisationalstandards.
3. Defined processesarestandardisedwithin theorganisationbasedonbest
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practicesidentifiedinternallyorfromexternalsources.Knowledgeandbestpracticesstarttobesharedinternally.Howevertheprocessesmaystillnotbewidelyadopted.
4. Managedtheorganisationhaswidelyadoptedthestandardprocessesandbeginsmonitorsthemusingdefinedmetrics.
5. Optimisingtheorganisationisattemptingtooptimiseandrefineitsprocesstoincreaseefficiencywithintheorganisationand,morewidely,withinitsbusinesssector.
Broadly,thelevelsrepresentanincreasinglevelofsophisticationintheorganisation:
movingfromadhocuncontrolledprocessestothosethatarerepeatable,standardisedandwell-managed
movingfromareactivetoaproactiveapproachwithinaparticularareaofactivity movingfromisolatedexpertise,e.g.individualschampioningopendata,throughto
widerorganisationalsupport
The five organisation themes and related activities
Themodelisbasedaroundfivethemes.Eachofthethemesrepresentsabroadareaofactivitywithintheorganisation:
Data management processesidentifiesthekeybusinessprocessesthatunderpindatamanagementandpublicationincludingqualitycontrol,publicationworkflows,andadoptionoftechnicalstandards.
Knowledge & skillshighlightsthestepsrequiredtocreateacultureofopendatawithinanorganisationbyidentifyingtheknowledgesharing,trainingandlearningrequiredtoembedanunderstandingofthebenefitsofopendata.
Customer support & engagement addressestheneedforanorganisationtoengagewithboththeirdatasourcesandtheirdatareuserstoprovidesufficientsupportandfeedbacktomakeopendatasuccessful.
Investment & financial performancecoverstheneedfororganisationstohaveinsightintothevalueoftheirdatasetsandtheappropriatebudgetaryandfinancialoversight required to support theirpublication. In termsofdataconsumption,organisationswillneedtounderstandthecostsandvalueassociatedwiththeirreuseofthird-partydatasets.
Strategic oversight highlightstheneedforanorganisationtohaveaclearstrategyarounddatasharingandreuse,andanidentifiedleadershipwithresponsibilityandcapacitytodeliverthatstrategy.
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Eachofthesethemeshavebeenbrokendownintoseveralactivitiesthatdescribethebehavioursandprocessesthattheorganisationshouldcarryout.
Theassessmentgrididentifieshoworganisationsatdifferentlevelsofmaturitywillcarryouteachoftheactivities.Themajorityofthisdocumentprovidesmoredetailonthethemesandactivities.
The two aspects of open data practice - publication and reuseWeexpectthatamatureopendataorganisationwillbebothaconsumerandpublisherofopendata,althoughtheoverallbalanceislikelytovaryacrossorganisations.Someorganisationsmayprimarilypublishratherthanreusedata,whileothersmayprimarilyconsumedataandhavelittleornopublisheddata.
Someactivitieswithinthematuritymodelapplytoboththepublicationandreuseofdata,whileothersareclearlyfocusedononeofthoseaspectsofopendatapractice.
Tohelporganisationsfocusontheelementsofthemodelthataremostapplicabletothem,theassessmentgrididentifieswhethertheindividualactivitiesareassociatedwithoneorbothofthefollowingaspects:
Data publicationaddressestheorganisationalactivitiesandprocessesthatsupportthecreationandmanagementofdatasetsthataremadeaccessibleunderanopenlicence.
Data re-useisconcernedwiththeprocessesthatsupporttheeffectivereuseofthird-partydatasets.
How to perform an assessmentTheOpenDataMaturityModelprovidesaframeworkforassessingorganisationalmaturityacrossarangeofactivities.Aspartofcarryingoutamaturityassessment,anorganisationshouldattempttoscore itselfagainstallof theseactivities.Thiswillproduceacompleteassessmentofopendatamaturityandsupportbenchmarkingwithotherorganisations.Howeverwedonotexpectthatallorganisationswillobtainthemaximumscoreinallactivities.
Someelementsofthemodelwillbemoreapplicabletocertainorganisations.Forexample,anorganisationhandlingsensitivepersonaldatawilllikelyfocusongaininggreatermaturity
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indesensitisingdata.Incontrast,anorganisationthatmanagesonlynon-personalreferencedatawillnotrequireahighmaturityinthisarea.
Someorganisationsmaybecreatingandmanagingdataaspartoftheirprimarytaskorgoal,whileothersmayonlybegeneratingdataasaside-effectofotheractions.Thesedifferenceswillaffecthowimportantitistoattainahighlevelofmaturityand,accordingly,thelevelofinvestmentappropriatetosupportimprovement.
Organisationsshoulddeterminethetargetmaturitythatisappropriatefortheirspecificgoalsandpurpose.Asanorganisationgainsvaluefromitsopendatapracticethismay justifyadditional investment,andasubsequentraisingoftargetstohelpunlockfurtherbenefits.Assessmentandimprovementshouldbeaniterativeprocess.
Ifanorganisationistransparentaboutitscurrentopendatamaturityandtargetsitmayhelpthewidercommunityunderstandwhatitcanexpectfromthatorganisationintermsofitsopendatapractice.Transparencycanalsohelpsupportbenchmarkingacrossorganisations.
Importantly,themodelisnotmeanttohinderthereleaseoruseofopendata.Forexample,alowmaturityscoreforadatareleaseprocessshouldnotprecludepublishingopendata.Theactivitiesdescribedinthemodelshouldprovidearoadmapforimprovementnotalistoftaskstocompletebeforedataisreleased.Indeed,itisdesirablefororganisationstoexperiencelowlevelsofmaturitysothattheydevelopprocessesthatareappropriatefortheorganisation.Attemptingtoleapfrogtohighmaturitylevelsmayresultinimposingprocessesthatdonottakeintoaccounttheculture,environmentorparticularneedsoftheorganisation.
Setting an assessment process
Thefollowingprocessoutlinesarecommendedapproachforconductingamaturityassessment:
1. Identify an organisational lead athoroughassessmentwilllikelyrequireinputfromacrosstheorganisationbutthereshouldbeaclearleadwhocoordinatestheassessment.
2. Identify the scopethematuritymodelcanbeusedtoassessindividualdepartmentsorawholeorganisation.Werecommendbeginningwithanassessmentofthewholeorganisation.
3. Identify key participants whichpeople in theorganisationmayneedtobeinvolvedtohelpanswerspecificquestionsorsupporttheevaluation?
4. Assess and score each activityusingtheassessmentgrid,revieweachoftheactivitiesandidentifythelevelofmaturityachievedbytheorganisation.Toqualifyata
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specificmaturitylevel,theorganisationshouldexhibitallofthedescribedbehaviours.5. Set appropriate targetshavingconductedabaselineassessment, identify
appropriatetargetsforimprovement.Thiswillinvolveeithermaintainingorimprovingthescoreforspecificactivities.
6. Develop action planbasedontheresultsandthetargets, identifyaplanforimplementingimprovements.
7. Circulate resultssharetheresults,targetsandactionplanwithintheorganisation,includingtothoseinvolvedinsupportingtheassessment.Seniormanagementsupportandreviewwillbeessentialinhelpingtoimplementimprovements.Anorganisationmayalsowishtoshareitsresultsmorewidely.
8. Set date for next assessment theactionplanshouldsetadateforafurtherassessment.Thiswillallowtheorganisationtomonitoritsprogress.Werecommendconductingregularannualassessments.
Prioritising and aligning your activities
Theassessmentgridandthisguidancedocumentdescribeanumberofactivities.Theorderinwhichthesearepresentedreflectsaroughprogressionfromoperationalconcerns(e.g.technology,standards)throughtostrategicissues(e.g.financeandpolicy).Howeverthereisnounderlyingassumptionthatanyoftheactivitieshaveahigherpriorityorvaluethanothers.
Also,inpractice,theactivitieswillrelatetooneanother.Forexample,developinganinternalassetcataloguetohelpcreatestrategicoversightmayalsoprogressgooddatagovernanceanddatareleaseprocesses.Similarly,developingadatasetvaluationprocessmayhelpinformfinancialplanningandprioritisingreleases.
Anorganisationmaychoosetoassignitsownprioritiestotheactivitiesinthemodel:
Whenconducting an assessmentitmaybeusefultoprioritisethereviewofcertainactivities,e.g.toreviewwell-definedandunderstoodareasfirstortoalignwithotherorganisationalpriorities.
Whensetting targets and developing an action plantheorganisationmaywishtoprioritisecertainactivitiesfor improvement.Someorganisationsmayprefertoimplementchanges inatop-downstyle (perhapsfocusingfirstonstrategyandoversight)whileothersmaypreferabottom-upapproach.
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Theme 1. Data management processes
Activity Aspect Level1-Initial
Level2-Repeatable
Level3-Defined
Level4-Managed
Level5-Optimising
Beneficialeffects
Datareleaseprocess
Publication Littleornopublishedopendata.
Datasetsthatarepublished[...]
Specificprojectsorproductsmayhavedefinedarepeatableprocessfor[...]
Thereisarepeatableorganisation-widestandardreleaseprocessfor[...]
Alldatasetsarereleasedaccordingtothestandardorganisationalprocess.
Theorganisationcollectsandmonitorsmetricsonitsreleaseprocess,[...]
Reduceoverheadsassociatedwithdatareleases.
Withinamatureopendataorganisation,anumberofbusinessprocesseswillunderpintheeffectivemanagementofdatasets.Theseprocesseswillsupportboththereleaseandreuseofopendata.
Strongdatagovernancehelpstoensurethatanorganisationeffectivelymaintains itsdataassets.Managingdataqualityisimportantregardlessofhowdataissubsequentlylicensedandshared.
Howeversomedatamanagementpracticesmaybelessapplicableforopendata.Forexample,managingaccessandsecurityisnotaconcerngiventhatopendataisaccessibletoanyone,bydefinition.
Conversely, therearepracticesthatareparticularlyrelevantforopendata.These includeissuessuchas:
anonymisationandaggregationofdatatoremove sensitive information redaction of personally or commercially sensitive data theadoptionofbestpracticesthatensure that published data can be easily re-
used by third-parties
Withthisinmind,thisthemehighlightsdatamanagementandgovernancepracticesthatareparticularlyrelevanttoopendata.Butitisrecommendedthatthisassessmentismadeinthecontextofawiderevaluationofdatagovernancewithintheorganisation.
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Building a process to support data release
Amatureopendataorganisationwillhave a well-defined process to support the publication of open data.Theprocesswilladdressthetechnicalaspectsofpublishingbothnewdatasetsandupdatestoexistingdatasetsinatimelymanner.
Therelease processwillbewelldocumentedandaddresskeyissuessuchas:
thetechnical infrastructureusedtosupportarelease,e.g.aspecificdataplatformorportal
thecreation and maintenance of dataset-specific metadata theinternal processes and workflowsthatsupportreviewandpackagingofdata
forrelease thesyndication of datasetsand/ormetadatatothird-partydatacatalogsand
platforms
Theorganisationsstandardprocesswilldescribethekeystepsinvolvedinarelease,identifyingresponsibilities forensuringreleaseshappen inatimelymannerandtoahighstandard.Individualdatasetsmaybereleasedusingamethodologythatadaptstheorganisation-widestandardbasedontheneedsofthespecificdatasetorproduct.
Key metricsthatmaybecollectedaboutthisprocessinclude:
thenumber of datasets released thenumber of datasets released to schedule thenumber of datasets being regularly updated themean time between internal updates being made to a dataset and those
updates being shared with others
Moving from ad-hoc approaches to data releases to a repeatable processwillbringanumberofbenefits,including:
simplifying release of new datathroughreuseofexistingworkflowsandtools making iteasier for reusers to find and use a variety of datasets fromthe
organisation clarity around whether datasets are being releasedinlinewithcorporateobjectives
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Developing standards and adoption
Matureorganisationswillbenefit from both the use of open standards for formatting data and the adoption of industry standard identifiersintheirdatasets.
Thesebenefitsforpublishersinclude:
available open source toolingtosupportmanagingdata easy recruitment of specific technical expertise reduced burden of maintaining and documenting bespoke standards increased adoption and use of published data
Adoptionofstandardsalsohasbenefits for reusersofopendata:
datasets published in industry or de facto standard formats are easier to consume
datasets that use common identifiers,suchascodesforgeographicalareas,aremore easily compared and combined
reuserscan easily find relevant dataanddocumentationbylookingupidentifiers reuserscan more easily process datasetswhentheyarepublishedusingstandard
metadataandpackagingformats
Whenstandardsarewidelyadopteditbenefitseveryoneascostscanbeloweredthroughtheuseofcommon,standardtools.Datasetsthatarelinkedtogethercanbemoreeasilyanalysedandcombinedmoreflexibleways.
Amatureopendataorganisationwilldefine the technical standards that it will use when publishing its data.Thesestandardswilladdress:
thedataformats(e.g.CSV,JSON,KML)usedtostructurethedata theaccessmethods(e.g.anAPI)usedtomakedataavailable themeansbywhichthedataisstructured,e.g.throughuseofstandardschemas
Thestandardsmayrefertoasinglesetoftechnologiesorrecognisethatcertaintypesofdata(e.g.geographicalorstatisticaldata)mightbebestpublishedusingtype-specificstandards.
Thematureopendataorganisationwillalsorecognise that as standards evolve it may need to revise its data publication practices in order to best support both new and existing consumers.Theorganisationwillthereforetrackindustrytrendsandmonitorhowotherorganisationsarepublishingsimilarandinterrelateddatasets.
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Amatureorganisationwillalsoresearch the ways in which reusers would like to process data.Thismightleadtheorganisationtopublishingdatausingseveraldifferentaccessmethods.Fordataanalysistheabilitytodownloaddatainitsentiretyisoftenessential,whereasreal-timeaccesstodatamaybebetterservedbydevelopmentofanAPI.
Developing data governance
Releasinghigh-qualityopendatarequiresorganisationstoapplyappropriatelevelsofdatagovernancetotheirdatasets,addressingissuessuchasdataquality,integrity,monitoringandprotectionacrosstheentiredatalifecycle.
Amatureopendataorganisationwillimplement a data governance process across all of its datasets.Thisincludesdatasetsproducedinternallyandthoseitisconsumingfromthird-partysources.
Organisationsmayfindthatpublicationofopendatawillhighlightexistingdatagovernanceissues.Therearemanyexamplesofinconsistenciesandinaccuraciesindatabeinguncoveredonlyafterthedataisexposedtowiderreview.Thisoftenleadstoimprovementsinnotjustthequalityofthedatabutalsoreviewandimprovementsintheunderlyingdatamanagementpractices.Theresultingimprovementstodataqualitycanbringparticularbenefitswhentheorganisationusesthedatawithinitsownprocessesanddecisionmaking.
Amatureorganisationwilltreat a third-party open dataset as if it were its own asset.Thiswillinvolveprovidingappropriatefeedbacktotheoriginalsourceondataqualityissues.Inthecaseofcrowd-sourcedorcollaborativelymaintaineddatasets,theorganisationwilllikelyinvesttimeinresolvingtheseissuesforthebenefitofitselfandotherreusers.
Managing sensitive data
Datasetsmayincludeavarietyofsensitiveinformationsuchascommerciallysensitivedatathatanorganisationmaynotbehappyaboutsharingwithcompetitors,orpersonalinformationaboutitscustomers,employees,orotherindividuals.
Amatureorganisationwillconduct risk and impact assessments prior to the publication of sensitive datasets.ForexampleitmayconductaPrivacyImpactAssessment11.Itwillalsohaveprocedurestomitigateriskpriortorelease,including:
11 Privacybydesign,https://ico.org.uk/for-organisations/guide-to-data-protection/privacy-by-design/,accessedon2015-03-23
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haveananonymisationpolicyandknow about the process of anonymising data redacting commercially sensitive figuresorcompanynames subsettingofdatatoremove sensitive fields aggregationinordertosummarise data obtaining appropriate consentfromindividualswhosepersonaldatamaybereleased considering the data environmentsuchasotherrelateddatasets,peoplewhohave
accesstothedataorpeoplewhohaveamotivationtoexploitthedatabeyonditsintendeduses.
Amatureorganisationmayalsoseek independent, external validation of its approach to anonymising highly sensitive datasets.Forexample,itmayengageathirdpartytoperformamotivatedintrudertest.
Inadditiontoidentifyingstandardapproachestodesensitising,theorganisationwillproperlyeducateitsstaffabouttheiruseensuringthattechniquesareappliedcorrectlyandeffectively.
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Theme 2. Knowledge and skills
Activity Aspect Level1-Initial
Level2-Repeatable
Level3-Defined
Level4-Managed
Level5-Optimising
Beneficialeffects
Opendataexpertise
Publication&re-use
Theorganisationdoesnotprovideanydirecttrainingorsupportfor[...]
Nosharedunderstandingaroundopendataintheorganisation,althoughsomeareas[...]
Theorganisationisawareofwherefurthersupportandunderstandingisrequired[...]
Theorganisationisactivelybuildingasharedunderstandingaround[...]
Knowledgeandunderstandingofopendataexistsatalllevelsinthe[...]
Reducerelianceandcostofusingexternalexpertise.
Amatureopendataorganisationwillunderstand the benefits of openness and transparency and apply those principles appropriately.
Supportingthedevelopmentofthisculture,amatureorganisationwillensurethatstaffhavethenecessaryskillsandexpertiseinanumberofdifferentareas.Thisknowledgewillrangefrom:
acommonunderstanding of the value of open data and its applicationtotheorganisation
operationalskillsrequiredtosupport data governance and publishing strategicunderstanding,ataseniorlevel,ofhowtouse open data to further the
goalsoftheorganisation
Anorganisationwillsupportemployeesindevelopingtheskillsnecessarytodeliveronitsopendatastrategy.Thismayincludeofferingtrainingonkeytopicssuchaslicensing,technologyordatagovernance.Accesstoinformationisalsoanimportantcomponentofdevelopinginternalexpertisewithopendata.Theorganisationwillensurethatallorganisationalstandards,datasetsandrelevantdatadocumentationareaccessibletothestaffwhoneedit.
Theskillsdevelopmentsupportprovidedbyorganisationsforhealth&safetyisagoodanalogyforhowanorganisationmaydevelopbothabroadunderstandingofgooddatamanagementpracticesaswellasidentified,accessibleexpertise.
Allorganisationsofferhealth&safetytrainingasastandardelementofstaffinductionandkeystaffmembersareidentifiedashealth&safetyexperts.Datahealth&safetyunderstandingtherisks,responsibilities,andactionsrequiredtoensurethatdataiswellmanagedandsharedeffectivelyshouldbecomeanelementofstaffdevelopmentinmatureopendataorganisations.
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Expertiseintopicssuchaslicensinganddatastandardswillbeidentifiedandmadeavailableacrosstheorganisation.
Developing open data expertise
Amatureorganisationwillensure that staff have the necessary training and support required to deliver on their individual responsibilities relating to open data.Thisislikelytobeoneaspectofwiderawarenessofthebenefitsofgooddatagovernanceanditsapplicationtocompanystrategy.
Itwillbeimportantthatemployeeshavetrainingtoensurethattheyhave
anunderstanding of both the risks and benefitsofusingandpublishingopendataandhowthataffectstheirownroleandresponsibilities
anunderstanding of the organisations open data policies and strategy theabilitytoapply the appropriate level of data governanceintheirownprojects specific training on individual topics,e.g.technicalstandards,bestpractices,
licensingissues
Ideallythiseducationprogrammewillbeginatstaffinduction(datahealth&safety)andbeofferedaspartofcontinualstaffdevelopment,e.g.viainternaltrainingandrefreshercourses.
Amatureorganisationwillalsoworktodevelopskillsatalllevelsoftheorganisation,supportingbothoperationalneedsandstrategicoversight.
Wherestaffidentifyadditionalsupport isrequiredthenaccesstothenecessaryexpertise,whetherfromotherpartsoftheorganisationorexternally,willalsobemadeavailable.Inlargerorganisationsthismaytranslate intodedicatedstaffresponsibleformanagingopendataprogrammesandtechnicalplatforms.
Knowledge management
Knowledgemanagement isan importantprocess inanyorganisation.Fromanopendataperspective,knowledgemanagementisimportantfortworeasons.
First,staffneedtobeabletofindandusedocumentationonorganisationalstandardsandpolicies.Manyofthesepolicieswillalsobeofinteresttothird-partiessuchaspotentialreusersofpublisheddata.Apublicopendatapolicyandstrategywillhelpidentifytheleveloforganisationalcommitmenttoopendataandidentifyhowthird-partiescanengagewiththeorganisation.
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Second,bothinternalandexternalusersneedtohaveaccesstothenecessarydocumentationrequiredtosupporttheuseofpublisheddata.Thisisparticularlyimportantfororganisationsthatundertakeresearchprojectsorsimilaractivitiesthatmayproduceanumberofdatasets.Fordatatoretainitsvalueinthelongterm,peoplewhouseitneedtoknowabouthowitscollected,howitsprocessedandwhoownsit.
Amatureorganisationwillmaximisethevalueofitsdataassetsbyensuringthatappropriateinformationiscapturedandsharedthroughoutthelifecycleofadataset.Thisinformationshouldbeeasilyavailabletobothinternalandexternalusers.
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Theme 3. Customer support and engagement
Activity Aspect Level1-Initial
Level2-Repeatable
Level3-Defined
Level4-Managed
Level5-Optimising
Beneficialeffects
Engagementprocess
Publication Littleornoattemptmadetoidentifypotentialre-usersforreleased[...]
Someteamsattempttoidentifyandengagewithpotentialre-users[...]
Theorganisationidentifiesarepeatableapproachfor[...]
Theorganisationbeginstrackingtheeffectivenessofits[...]
Theorganisationisroutinelytrackingmetricsrelating[...]
Greaterinsightintore-userneeds&activities.
Publishinghighqualityopendatainvolvesmorethanmakingdataavailableonline:reuserswillneedsupportincorrectlyinterpretingandusingthatdata.Ataminimumthiswillrequirethatdataispublishedwithenoughdocumentationandsupportingmetadatathatreuserscanunderstandthestructure,scopeandprovenanceofadataset.
Amatureorganisationwillalsoconsider additional ways that it can support its reusers such as via a help desk function or similar services.Growingacommunityaroundadatasetmightinvolvehelpinginterestedreusersconnectwitheachothertoshareexperiencesandbenefits.
Opendataispublishedforavarietyofreasons.Butregardlessofwhetherdataispublishedtomeetlegalobligationsoraspartofaopendatabusinessmodel,anorganisationwillneedtoplanhowitwillengagewithitscustomers,monitorhowitsdataisbeingusedandidentifywherevalueisbeingcreated.
Developing an engagement process with data reusers
Amatureopendataorganisationwilldefine a process for engaging with reusers of its data.Fororganisationsthatarealreadyfamiliarwithpublishingdataorsupportingexternalcustomersthis typeofengagementwillbeanevolutionofexistingpractices. Inotherorganisationsthismightbeanewprocessandmayrequiretheorganisationto identifynewrolesandcommunicationchannels.
Organisationswithexistingcustomerengagementandmarketingprogrammeswillneedtoconsiderhowpublishingopendatamayresultinnewaudiencesfortheirdata.Cost-reductionandnetworkeffectsmaysurfaceadditionaldemandforandopportunitiesforusingdata.
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Anengagementprocesswilltypicallyincludearangeofactivities12:
identifyingbothpotential and actual reusers of a dataset identifyingthekey stakeholders in the re-user communityinordertoprioritise
andfocusengagementactivities engagingwiththatcommunitytohelp them understand how a dataset might be
used andtohighlightrelevantnewdatareleases acommunicationsplantohelp promote the activities of both the publisher(news,
events,etc)and the community itself(e.g.sharesuccessstories,insightsintothedata,andcasestudies)
reflectingexperiencesbackintotheorganisationtohelpdemonstratevalue,buildbusinesscases,etc.
runningeventssuchashackdaysorchallengestoencourage and incentivise use of dataandtogeneratecasestudiesforwidersharing
Ideallytheprocesswillbemetrics-driven,allowinganorganisationtomonitorandimproveitsoutreachactivities.Metricsgatheredbytheorganisationmightincludebasicindicatorssuchas:
thenumberofusers accessing or using data thenumberofusers contributing to discussions or data updates thenumberofapplications developed on published data
Notalldatasetswillnecessarilyneedorrequireadetailedengagementactivity.Onestepindefiningtheengagementplanforadatasetwillbeidentifyingtheappropriatelevelofengagementnecessaryandappropriatetotheongoinginvestmentinthedata.
Documenting your open data
Data cannot be used effectively if it is not properly documented. Amature opendataorganisationwillensure that all datasets are published with a standard set of supporting documentation that follows a consistent template structure.Thisdocumentationwillbecreatedandmaintainedthroughoutthelifecycleofthedataset,ratherthanjustpriortopublication.
The levelofdocumentationrequiredwillusuallyvarydependingonthecomplexityoftheindividualdatasetanditsmethodofcollectionandanalysis.Typicallydocumentationwillinclude:
12 seealso,theODIguideonengagingwithreusers:http://theodi.org/guides/engaging-reusers
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descriptive dataprovidingahigh-levelsummaryandsupportingmetadatatodescribethedatasetincludingtitle,description,keywords,licence,rightsstatementsandattributionrequirements
access informationdescribeshowtoaccessthedata,locationofarchivesandmirrors,etc
indicatorssummarystatisticsthatprovideinsightintothesize,rateofgrowth,qualityandupdatefrequencyofthedataset,anddataquality
relationshipspointerstootherdatasourcesthatwereusedtoconstructthedataset,e.g.referencestostandardcode-listsandothercomplementarydatasets
scope & coverageadescriptionofthecontentsofthedataset,thetypesofentityitdescribes,itsgeographicfocus,andthetimeperiodtowhichitapplies
provenance howdatahasbeencollectedandprocessedpriortopublication technical documentation adescriptionofthedataformatswithreferenceto
formalschemasthatdefinethefieldsinthedatasets;samplerecordsmaybeusedforillustrativepurposes
DatadeliveredviaanAPIratherthanadatasetdownloadwillalsobeaccompaniedbyaspecificationoftheAPIimplementation.Creatingandmaintainingthisdocumentationwill forman importantelement inboththeprocessofreleasingadatasetandsupportingitssubsequentuse.Ideallydocumentationwillbemanagedusingacontentmanagementsystemthatenablesitsrapidproduction,reviewandpublication.
Inamatureopendataorganisation,referencedocumentation will often be supplemented with additional material,suchastutorialsonusingoraccessingadataset,sampleapplications,orpointerstousefultoolsandresourcesthatsupporteffectivereuse.
Theeffortputintoprovidingboththecoreandanyadditionaldocumentationwillbeappropriatetothevalueandinvestmentinthedataset.
Building a reuser support process
Amatureopendataorganisationwillhavewell-defined contact points that will allow third-parties to engage with the organisation about its open data practice.Forexample,theywillallowreuserstorequestthattheorganisationopenupdata,orprovideinputintotheprioritisationofplannedreleases.
Fordatathatisalreadyreleased,amatureorganisationwillalsoprovidesupportforreusers
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inotherways:
anopen forum for raising questions about a dataset,e.g.withasupportteamorothersinthereusercommunity
ameans to report errors, data quality, or privacy issues with a dataset communication on issues that may impact reusers,e.g.significantchangesto
adataset;reporteddataquality issues;retiringofadataset;oradecisiontonotreleaseanidentifieddataset
Theorganisationwillensurethatthesupportavailableforadatasetisclearlydefinedsothatreuserscanhaveappropriateexpectationsaboutthelevelofsupportavailable.
Creating open data community norms
Amatureopendataorganisationwillsupport not only its reusers but will also act as a good citizen in the wider open data community.Forexampleanorganisationwillbetransparentabouttheopendataituses,ensuringthatappropriateattributionisgiventothosesources.
Theorganisationwillalso:
seektoshare its experiences with individual datasets,providingfeedbacktotheirpublishersoneaseofuse,dataissues,etc
be transparent about the open datasetsitusestohelphighlightthevalueofthosedatasetsinthecommunity;thiswillincludeensuringthatsourcesareattributed
create and share case studiesthathighlighttheimpactandbenefitsofworkingwithopendata
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Theme 4. Investment and financial performance
Activity Aspect Level1-Initial
Level2-Repeatable
Level3-Defined
Level4-Managed
Level5-Optimising
Beneficialeffects
Financialoversight
Publication&re-use
Datareleasesareunfundedanddoneasexceptionalexpenditure.
Individualprojectsmayincludeopendatapublicationcostsas[...]
Projectfundingandoperationalcostsroutinelyincludelongterms[...]
Theorganisationactivelymonitorsthefinancialcostsand[...]
Theorganisationlooksforefficiencysavingsaround[...]
Costsofpublishingandusingdataclearly[...]
Publishingopendata,especiallyoverthelong-termandtoahighstandard,requiresongoing investment in both people and infrastructure.Thesecostsmaybeoffsetbyfinancialbenefitsfromopeningdata,suchasthroughexploitingnewbusinessmodels,orefficiencysavingsfromdeduplicationofdatacurationeffortsoreasierintegrationwiththird-parties.
Similarbenefitsaccruefromtheuseofthird-partyopendatasets.Anopendatasetmightreplaceacostlylicensedalternative.Coststomaintainaninternaldatasetmightbereducedbyswitchingtoanopencollaborativemodelformanagingthedata.
Amatureopendataorganisationwillquantify both the costs and benefits that relate to its open data practice.Byvaluingbothpublishedandunpublisheddatasets,theorganisationwillbeabletoprioritiseandjustifyitsongoinginvestment.
Ensuring financial oversight
Amatureorganisationwillactively monitor the financial costs and benefits of both publishing and using open and closed (restrictively licensed) data.Thiswill includeensuringthatprojectfundingandoperationalcostsfornewandexistingprojectsincludetheappropriatelevelsofinvestmenttosupportdatapublicationwhereapplicable.
Theorganisationwill recognisethedifferencebetweentheongoingcostsassociatedwithgeneraldatagovernanceandthoseassociatedspecificallywithopendatapublication.Thiswillavoidincorrectlyattributingtoopendatapublishingeffortstheentirecostofimprovementstodatagovernanceandsimilarbestpractices.
Theorganisationwillalsousethisfinancialinsighttolookforefficiencysavingsinitspublicationanduseofdatasuchasthroughreductionindatamanagementoverheadsorcostsavingsfromadoptionofopendata.
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Developing dataset valusation processes
Amatureorganisationwillrecognise that investment in open data publication should be driven by a cost/benefit analysis.Highvaluedatasets,namelythosedirectlyalignedwithdeliveryofcorporateobjectives,mayrequirehigherlevelsofinvestmentthanothersecondarydatasets.
Theorganisationwillhaveamethodologyforassessingthevalueofadatasettoboththebusinessandend-users.Themethodologymayinvolveengagingwithend-usersinordertoidentifythelevelofinterestordemandindatasets,andhowthatdatamightbeused.
Thelackofadatavaluationprocessshouldnothinderthereleaseofopendata.Butbydefiningaprocessanorganisationwillbebetterabletoprioritisedatasetsforreleaseandtoensureappropriatelevelsofinvestmentaremadeintheirgovernanceandongoingpublication.
Amatureorganisationwillalsobe transparent about its approach to valuing datasets, sharing the metrics it uses with those who have interest in its data.
Similarly,whereanorganisationisre-usingdatasetsitshouldbeabletoquantifythefinancialbenefitsassociatedwiththeirreuse,forexamplebycomparisonwiththecostsassociatedwithlicensedalternatives.Theorganisationwillworktomaximisethevalueitderivesfromdataassetsandlookforopportunitieswhereswitchingfromalicenseddatasettoanopendatasetmightprovideadditionalbenefits,suchasaffordinggreatertransparencyortheabilitytoswitchtolesscostlyserviceproviders.
Building open data into procurement practices
Foranorganisationtounderstanditsrightstopublishandreusedataitisessentialthatthereisclarityabouthowdata iscreatedandmanagedthroughouttheorganisation13. Insomecasesdataassetsmaybecreatedormanagedbythird-partiessuchasbycontractors,partnerorganisations,orinSoftware-as-a-Serviceinfrastructure.
Amatureopendataorganisationwillensurethat:
contracts used for sub-contractors clearly describe the intellectual property rightsassociatedwithanydatadeliveredorcreatedduringaprojectorservice,wherepossiblegrantingthoserightstotheorganisation
13 SeetheODIguideonembeddingpublicdataintoprocurementofpublicserviceshttp://training.theodi.org/Procurement/Guide/
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procurementprocesseshavebeenupdatedtoensure that, where appropriate, potential contractors provide information about how they will deliver open dataaspartofaproject
contractorsprovide clarity around the provenance of any data they useorsupplysothattheorganisationisclearonanyrightsrelatingtoderiveddatasets
procurementpracticestake into account the whole-life costsofaservicetofavoursuppliersthatprovideeasyaccesstodatarequiredtomovesuppliers
Thiswillensurethattheorganisationisproactivelyclarifyingintellectualpropertyrights,wherenecessary,ratherthanreactivelyundertakingcostlyrightsclearanceaftercontractsareawarded.
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Theme 5. Strategic oversight
Activity Aspect Level1-Initial
Level2-Repeatable
Level3-Defined
Level4-Managed
Level5-Optimising
Beneficialeffects
Opendatastrategy
Publication&re-use
Theorganisationhasnostrategyorpolicywithregards[...]
Individualbusinessunitsidentifybenefitstoopendatafortheir[...]
Theorganisationdefinesanopendatastrategy.Thiswill[...]
Theorganisationhasaligneddeliveryonopendatapolicy[...]
Theorganisationisusingopendataasakeyelementofits[...]
Claritywithintheorganisationandexternallyaboutopendatastrategy.
Giventhe impactsofopendatapracticeon internalprocessesandthepotentialfinancialbenefitsandinvestmentrequired,amatureopendataorganisationwillensurethatitsadoptionofopendataiscloselyalignedwithitswiderorganisationalobjectives.
Bothinternalandthird-partyopendatasetswillberecognisedasassetsthatshouldbecarefullymanaged.Closealignmentwithcompanystrategywillensurethatobjectivesfordeliveringonthevalueassociatedwithopendatawillbereflectedataseniormanagementlevel.
Shaping open data strategy
Amatureopendataorganisationwillhave an open data strategy that clearly describes its ongoing commitments and policies relating to its open data practice.
Asaninternalresource,anopendatastrategywillsetouttheorganisationsstrategyforbuildingopendataintoitsproductsandreporting.Itwillalsoidentifytherolesandresponsibilitiesofthoseinvolvedinpublishingopendataonbehalfoftheorganisation.Thestrategywillreferencethekeyprocesseshighlightedelsewhereinthismodel,thatisforprocurement,datagovernance,releaseprocesses,etc.
Amatureorganisationmightpublicly publish its open data strategy, making a stronger commitment to open data.Apublicstrategywillgivereusersinsightintohowtheorganisationprioritisesitsdatasetsforreleaseanddescribehowtoengagewiththatprocess.Agoodopendatastrategywillalsoidentifyhowtheorganisationspolicymayevolveovertime.
Thematureorganisationwillalsoattempt to measure its progress against its strategy.ForexampleitmayincludecommitmentsthatsetouttargetsforgainingandimprovingthelevelsofdatasetcertificationaccordingtotheOpenDataInstitutescertificationprogress.
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Theopendatastrategywillhaveaclearownerwhowillhaveboththebudgetandresponsibilityforitsdelivery.Theindividualprocessesreferencedinthestrategy,suchasdatagovernance,willalsobeownedbyspecificrolesintheorganisationandtheirresponsibilitieswillbeclearlydefined.
Asset catalogue management
Amatureopendataorganisationwilltreat data as an asset.Theorganisationwillmaintainacataloguethatlistsbothitsowninternaldatasetsandthoseitusesfromthird-parties.Thecataloguewillincludeallsignificantinternaldata,notjustthatpublishedasopendata.
Thecataloguewillsupportthereportingnecessarytodelivertheappropriateoversightoverdatagovernanceandreleaseprocessesand,atahigher-level,progressagainsttheorganisationalstrategy.Thecataloguemayalsosupportdiscoveryofcostsavingsbyidentifyingduplicateoroverlappingdatasetsandopportunitiestoreuseexistingdatasetsinnewproductsandservices.
Fordatasetsthattheorganisationowns,thecataloguemayincludeinformationsuchas:
therisksassociatedwithreleasingadataset,e.g.whetheritcontainspersonalorsensitiveinformation
thevalueofthedataset,asdeterminedthroughtheorganisationsdatavaluationprocess
thedetailsofongoingfinancialinvestmentassociatedwithitsrelease(orre-use)asopendata
whetherthedatasetisplanned for release asummary of the key metricscollectedbytheengagementprocess,etc.
Fordatasetsthattheorganisationreuses,thecatalogmayincludeinformationsuchas:
therightsthattheorganisationhastousethedata forcommercialdata,thecostsassociatedwithreuse forcommercialdata,therisksassociatedwithapriceincrease therisksassociatedwithadatasetbecomingunavailableorunmaintained thewaysthatthedataisre-usedbytheorganisation
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