Case Study

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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.

CASE STUDY
Case Study Title
Please provide a brief description of the work
Organisation
Country (if applicable)
Use of the information provided	The information provided can be shared publicly as part of the guide Don't share this information publicly, but only among colleagues in official statistics Only use this information in aggregates or as anonymous information Unless otherwise indicated, information may be shared publicly as part of the guide.
Contact Person
Email address
Please indicate the reason(s) for integrating data in this case	As a source for sample frames To supplement surveys (e.g. for a part of population, for a set of variables) To supplement traditional censuses (e.g. register based population census, agricultural census) For replacing sample surveys For replacing traditional censuses (e.g. register based population censuses, agricultural census) For maintaining registers For data validation For data editing and/or imputation For estimation (e.g. small area estimation) To provide geospatial products For customised data services To create statistical products in partnership with other organisations To meet the requirements of measuring the Sustainable Development Goals (SDGs) Other
If other, please describe and/or provide links
Please indicate the types of data being integrated with other data for the production of statistics in your organisation	Survey data Census data Automatic identification systems Banking/stock records (2220) Blogs and comments (1200) Car/vehicle location (3122) Commercial transactions (2210) Credit cards (2240) Data from public administration (2100) E-commerce (2230) E-Mail (1900) Home automation (3111) Internet searches (1600) Logs (3110) Medical records (2110) Mobile data content: text messages (1700) Mobile phone location (3121) Mobile phone: call/text times and positions (312.) Personal documents (1300) Pictures: Instagram, Flickr, Picasa etc. (1400) Satellite images (3123) Scientific sensors (3114) Security/surveillance videos/images (3115) Smart Energy Meters (311?)/Smart gas meters Social Networks: Facebook, Twitter, Tumblr etc. (1100) Traffic sensors/webcam (3113) User-generated maps (1800) Videos: Youtube etc. (1500) Weather/pollution sensors (3112) Web logs (3220) Source Classification of types of big data (https://statswiki.unece.org/display/bigdata/Classification+of+Types+of+Big+Data) plus additional items
If other, please describe and/or provide links
Please indicate the statistical domain(s) covered by this case study	Agriculture, forestry, fisheries (2.4.1) Banking, insurance,financial statistics (2.4.6) Business statistics (2.3) Culture (1.9) Economic accounts (2.2) Education (1.3) Energy (2.4.2) Entrepreneurship (3.3.7) Environment (3.1) Gender and special population groups (3.3.2) Globalisation (3.3.4) Government finance, fiscal and public sector statistics (2.5) Health (1.4) Human settlements and housing (1.7) Income and consumption (1.5) Indicators related to the Millenium or Sustainable Development Goals (3.3.5) Information Society (3.3.3) International trade and balance of payments (2.6) Justice and crime (1.8) Labour (1.2) Labour cost (2.8) Living conditions, poverty and cross cutting social issues (3.3.1) Macroeconomic statistics (2.1) Mining, manufacturing, construction (2.4.3) Political and other community activities (1.10) Population and migration (1.1) Prices (2.7) Regional and small area statistics (3.2) Science, technology and innovation (2.9) Social protection (1.6) Sustainable development (3.6.6) Time use (1.11) Tourism (2.4.5) Transport (2.4.4) Yearbooks and similar compendia (3.4) Other
If other, please describe
What is the status of the case study?	Research/experiment/feasibility study/in development One off/customised production of statistics Ongoing production of statistics with data integration included in the business process No information
Information technology The 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.aspx
Which tools (applications, software, etc.) are used in relation to the activity?	R SAS SPSS SQL Oracle G-Link FEBRL RELAIS CDA ATINE LinkageWiz LinkSolv Link Plus The Link King ChoiceMaker 2 Other commercial tools Other in-house developed tools Other outsourced services Other open source tools
Please provide additional details and/or links about the tools you use
Methods The 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.aspx
What methods are used?	Deterministic record linkage (links based on individual identifiers that match among the available data sets) Probabilistic record linkage (linking two pieces of information together using multiple, possibly non-unique, keys) Other
Please provide additional details and/or links about the methods you use
Further information
Please 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.
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CASE STUDY

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