ODI Maturity Model: Guide - Assessing your open data publishing and use

Open Data Maturity Model | Open Data Institute 20151

technical


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

15

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


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


toconsiderthesechallengesaswellasthestrategic,financialandoperational impactsofmakingtheirdataopen.

Understandingthisorganisationalchangeisanimportantaspectofbecominganeffectiveopendatapublisher.Similarchangestakeplaceasorganisationsbegintoreapthebenefitsofreusingopendatatoreducecosts,increaseefficiencyandtodriveinnovation.

Organisationsareatdifferentstagesinthisopendatajourney.Someareonlyjustbeginningtopublishdata,whileothershavealreadyundergonesignificantchangestowardsamoreopenbydefaultmodel.Manyareseekingguidanceabouthowtotakethenextstepsintheirjourney.

ThegoalofthisOpenDataMaturityModelistohighlightissuescommonlyencounteredbypublishers,andprovideameansfororganisationstoassessandimprovetheireffectivenessaspublishersandconsumersofopendata.Thematuritymodelprovidesaframeworkforunderstandingthedifferentareasoforganisationalchangetowardsopendata,whilealsoidentifyingthebenefitsofthatchange.


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


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


Acknowledgements

DefraandtheODIwouldliketojointlythankalloftheattendeesoftherequirementsworkshopsfortheircontributionstothedevelopmentofthematuritymodel.Wewouldalsoliketothankeveryonefromacrosscentralandlocalgovernment,agenciesandotherorganisationswhoprovidedfeedbackonthedraftdocuments.Thecontributionsand ideaswereextremelyvaluable.

ThefundingandsupportfortheprojectfromtheCabinetOfficeandtheOpenDataUserGroup(ODUG)5wereessentialinmakingthemodelareality.

5 OpenDataUserGroup,https://www.gov.uk/government/groups/open-data-user-group,accessedon2015-03-20


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


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


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


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.


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


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


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.


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.


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


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.


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


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.


Theme 2. Knowledge and skills


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.


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.


Second,bothinternalandexternalusersneedtohaveaccesstothenecessarydocumentationrequiredtosupporttheuseofpublisheddata.Thisisparticularlyimportantfororganisationsthatundertakeresearchprojectsorsimilaractivitiesthatmayproduceanumberofdatasets.Fordatatoretainitsvalueinthelongterm,peoplewhouseitneedtoknowabouthowitscollected,howitsprocessedandwhoownsit.

Amatureorganisationwillmaximisethevalueofitsdataassetsbyensuringthatappropriateinformationiscapturedandsharedthroughoutthelifecycleofadataset.Thisinformationshouldbeeasilyavailabletobothinternalandexternalusers.


Theme 3. Customer support and engagement


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.


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


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


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


Theme 4. Investment and financial performance


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.


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/


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.


Theme 5. Strategic oversight


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.


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

ODI Maturity Model: Guide - Assessing your open data publishing and use

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