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We welcome the submission of case studies for inclusion in the guide.  All fields are optional.  At the end of the form there is a place to provide detailed information.  

ConfiForms Form Definition
printEnabledtrue
formNameDataIntegrationCaseStudy

entrylinkLink to your responseThis link will be emailed to you on completion of the formautolink

casestudyCASE STUDY section

casestudytitleCase Study Titletext

casestudydescriptionPlease provide a brief description of the worktextarea

organisationOrganisation text

countryCountry (if applicable)text

useofinformationUse of the information providedfalse[1=The information provided can be shared publicly as part of the guide|2=Don't share this information publicly, but only among colleagues in official statistics|3=Only use this information in aggregates or as anonymous information|]Unless otherwise indicated, information may be shared publicly as part of the guide. radio_group

contactnameContact Persontext

emailEmail addresstext

Statistical Domains and data integration

diusesPlease indicate the reason(s) for integrating data in this casefalse[1=As a source for sample frames|2=To supplement surveys (e.g. for a part of population, for a set of variables)|3=To supplement traditional censuses (e.g. register based population census, agricultural census)|4=For replacing sample surveys|5=For replacing traditional censuses (e.g. register based population censuses, agricultural census)|6=For maintaining registers|7=For data validation|8=For data editing and/or imputation|9=For estimation (e.g. small area estimation)|10=To provide geospatial products|11=For customised data services|12=To create statistical products in partnership with other organisations|13=To meet the requirements of measuring the Sustainable Development Goals (SDGs)|14=Other|]checkbox_group

diusesotherinfoIf other, please describe and/or provide linkstextarea

ditypesPlease indicate the types of data being integrated with other data for the production of statistics in your organisationfalse[1=Survey data|2=Census data|3=Automatic identification systems|4=Banking/stock records (2220) |5=Blogs and comments (1200) |6=Car/vehicle location (3122) |7=Commercial transactions (2210) |8=Credit cards (2240) |9=Data from public administration (2100)|10= E-commerce (2230) E-Mail (1900) |11=Home automation (3111) |12=Internet searches (1600) |13=Logs (3110) |14=Medical records (2110) |15=Mobile data content: text messages (1700) |16=Mobile phone location (3121) |17=Mobile phone: call/text times and positions (312.) |18=Personal documents (1300) |19=Pictures: Instagram, Flickr, Picasa etc. (1400) |20=Satellite images (3123)|21=Scientific sensors (3114) |22=Security/surveillance videos/images (3115)|23=Smart Energy Meters (311?)/Smart gas meters |24=Social Networks: Facebook, Twitter, Tumblr etc. (1100) |25=Traffic sensors/webcam (3113) |26=User-generated maps (1800) |27=Videos: Youtube etc. (1500) |28=Weather/pollution sensors (3112) |29=Web logs (3220)|]Source Classification of types of big data (https://statswiki.unece.org/display/bigdata/Classification+of+Types+of+Big+Data) plus additional itemscheckbox_group


ditypeotherIf other, please describe and/or provide linkstextarea

domainsandtypescheckboxPlease indicate the statistical domain(s) covered by this case studyfalse[1=Agriculture, forestry, fisheries (2.4.1)|2=Banking, insurance,financial statistics (2.4.6)|3=Business statistics (2.3)|4=Culture (1.9)|5=Economic accounts (2.2)|6=Education (1.3)|7=Energy (2.4.2)|8=Entrepreneurship (3.3.7)|9=Environment (3.1)|10=Gender and special population groups (3.3.2)|11=Globalisation (3.3.4)|12=Government finance, fiscal and public sector statistics (2.5)|13=Health (1.4)|14=Human settlements and housing (1.7)|15=Income and consumption (1.5)|16=Indicators related to the Millenium or Sustainable Development Goals (3.3.5)|17=Information Society (3.3.3)|18=International trade and balance of payments (2.6)|19=Justice and crime (1.8)|20=Labour (1.2)|21=Labour cost (2.8)|22=Living conditions, poverty and cross cutting social issues (3.3.1)|23=Macroeconomic statistics (2.1)|24=Mining, manufacturing, construction (2.4.3)|25=Political and other community activities (1.10)|26=Population and migration (1.1)|27=Prices (2.7)|28=Regional and small area statistics (3.2)|29=Science, technology and innovation (2.9)|30=Social protection (1.6)|31=Sustainable development (3.6.6)|32=Time use (1.11)|33=Tourism (2.4.5)|34=Transport (2.4.4)|35=Yearbooks and similar compendia (3.4)|36=Other|]checkbox_group

domaintypeotherinfoIf other, please describetext

domaintypestatusWhat is the status of the case study?false[1=Research/experiment/feasibility study/in development|2=One off/customised production of statistics|3=Ongoing production of statistics with data integration included in the business process|4=No information|]radio_group



ICT

ictsectionInformation technologyThe UN guideline: "Using Administrative and Secondary Sources for Official Statistics: A Handbook of Principles and Practices” provides definitions and background information for "administrative sources”, "secondary data sources”, etc. Link: https://unstats.un.org/unsd/EconStatKB/KnowledgebaseArticle10349.aspxsection

toolsWhich tools (applications, software, etc.) are used in relation to the activity?false[1=R|2=SAS|3=SPSS|4=SQL|5=Oracle|6=G-Link|7=FEBRL|8=RELAIS|9=CDA|10=ATINE|11=LinkageWiz|12=LinkSolv|13=Link Plus|14=The Link King|15=ChoiceMaker 2|16=Other commercial tools|17=Other in-house developed tools|18=Other outsourced services|19=Other open source tools|]checkbox_group

toolsotherinfoPlease provide additional details and/or links about the tools you usetextarea

Methods

methodssectionMethodsThe UN guideline: "Using Administrative and Secondary Sources for Official Statistics: A Handbook of Principles and Practices” provides definitions and background information for "administrative sources”, "secondary data sources”, etc. Link: https://unstats.un.org/unsd/EconStatKB/KnowledgebaseArticle10349.aspxsection

methodsWhat methods are used?false[1=Deterministic record linkage (links based on individual identifiers that match among the available data sets)|2=Probabilistic record linkage (linking two pieces of information together using multiple, possibly non-unique, keys)|3=Other|]checkbox_group

methodsotherinfoPlease provide additional details and/or links about the methods you usetextarea

Other Information

infosectionFurther informationsection

otherinformationPlease provide any further information regarding your case study as text and/or links. For example, you could include links to published reports or papers, comments about open issues such as data access, or any other relevant information. textarea

otherinformationfilesUpload filesfile


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Send Emailno_reply@unece.orgonCreatedThank you for providing a case study for the Modernstats Data Integration Project[entry.email]

Dear [entry.contactname],


Thank you for providing a case study for the Modernstats Data Integration Project. You can use the link below if you need to view, edit or print your response.


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Colleagues with a UNECE wiki id can also log in and use the link. Colleagues can request a UNECE wiki id using


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For more information, refer to


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Best regards,

Jenine Borowik

Modernstats Data Integration Project Manager

jenine.borowik@bookmarkit.com.au

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Send Emailno_reply@unece.orgonCreated[entry.contactname] has submitted a case study for the Data Integration Projectdata_integration_admin

[entry.contactname] ([entry.email]) from [entry.organisation] has just submitted the following case study


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Best regards,

Data Integration Project Manager





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