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The Data Landscape Exercise helps teams map availability, accessibility, and quality of NIPN-relevant indicators, including which information systems and datasets exist, what they contain, and where legal access is obtained. Subsequent sections cover managing and assessing data quality, principles for analysis, dashboard production via an Excel template, analysis tools, and review processes for quality of analysis outputs.",{"@graph":63,"@context":118},[64,80,101],{"@type":65,"itemListElement":66},"BreadcrumbList",[67,71,74,77],{"item":68,"name":69,"@type":70,"position":9},"https://docshare.wps.com","Home","ListItem",{"item":72,"name":10,"@type":70,"position":73},"https://docshare.wps.com/template/",2,{"item":75,"name":11,"@type":70,"position":76},"https://docshare.wps.com/template/presentations/",3,{"item":78,"name":59,"@type":70,"position":79},"https://docshare.wps.com/template/managing-and-analysing-data-data-landscape-objectives-guidance-notes/239733/",4,{"url":78,"name":59,"@type":81,"image":82,"author":87,"headline":59,"publisher":90,"fileFormat":93,"inLanguage":57,"description":61,"dateModified":94,"datePublished":95,"encodingFormat":93,"isAccessibleForFree":96,"interactionStatistic":97},"DigitalDocument",{"url":83,"@type":84,"width":85,"height":86},"https://docshare.wps.com/thumbnails/managing-and-analysing-data-data-landscape-objectives-guidance-notes/239733.png","ImageObject",442,249,{"name":88,"@type":89},"Graffin","Person",{"url":68,"name":91,"@type":92},"DocShare","Organization","application/pdf","2026-10-29","2026-09-11",true,{"@type":98,"interactionType":99,"userInteractionCount":20},"InteractionCounter",{"@type":100},"ViewAction",{"@type":102,"mainEntity":103},"FAQPage",[104,110,114],{"name":105,"@type":106,"acceptedAnswer":107},"What is the main objective of a data landscape exercise?","Question",{"text":108,"@type":109},"To provide an overview of the availability, accessibility, and quality of indicators of interest to the National Information Platform for Nutrition (NIPN).","Answer",{"name":111,"@type":106,"acceptedAnswer":112},"What key questions does the data landscape exercise typically answer?",{"text":113,"@type":109},"It maps existing information systems, datasets, and indicators, checks how representative the data are at sub-national level and data collection frequency, and identifies where datasets are held and how legal access can be obtained.",{"name":115,"@type":106,"acceptedAnswer":116},"How can the data landscape exercise be used once completed?",{"text":117,"@type":109},"It helps determine which nutrition-policy-relevant data are available and of sufficient quality, supports teams in forming policy questions by assessing whether questions can be answered with existing data, and strengthens connections with data providers for future access.","https://schema.org",{"og:url":78,"og:type":120,"og:title":59,"og:site_name":91,"og:description":61},"article",{"robots":122,"canonical":78},"index,follow",{"doc_id":124,"site_id":56},239733,1791383590,{"code":4,"msg":5,"data":127},{"doc_id":124,"user_id":128,"nickname":88,"user_avatar":129,"doc_module":9,"category_id":8,"category_name":11,"doc_title":59,"doc_description":61,"doc_content":130,"file_id":131,"file_url":132,"file_type":133,"file_size":134,"view_count":20,"is_deleted":4,"is_public":9,"is_downloadable":9,"audit_status":9,"page_count":135,"language":136,"language_code":57,"site_id":56,"html_lang":57,"table_of_contents":137,"faqs":138,"seo_title":139,"seo_description":61,"update_tm":140,"read_time":141},3573418547284,"https://eur-avatar.wpscdn.com/davatar_994ba38a5ba835b3df7d355c54d3ed8d","Managing and analysing data  \nThe guidance notes in this section focus on the identification, management, quality assessment and analyses of available data, which are being shared by multiple sources in order to answer the nutrition policy questions formulated in the previous section.  \nThe first guidance note describes the Data Landscape Exercise, which will provide the country with an overview of the availability, accessibility and quality of indicators that are of interest to the NIPN.  \n(Watch the GSF webinar on the NIPN Data Landscape-16/01/19-40 min. ) .  \nThe second section provides guidance on the Management of the Data, while the third one focuses on the Quality of the Data.  \n(Watch the GSF webinar on the assessment of the quality of routine data-05/11/19-30 min.)  \nThe fourth guidance note provides Principles and Guidance for Data Analysis, aiming to support the NIPN teams to identify or choose the appropriate type of analysis, pertinent to the nutrition policy questions and the data quality. It sets out the strengths and limitations of the NIPN platforms for different types of data analysis, which can also be found a in short synthetic note.  \nThe fifth note is a tool which allows the rapid production of a Sub-national Nutrition Dashboard using a standard Excel spreadsheet template.  \n(Watch the GSF webinar on the NIPN Dashboard-13/12/2018-45 min. )  \nThe sixth section describes certain Analysis Tools and Methods that particularly fit the NIPN objectives.  \n(Watch the GSF webinar on the LiST tools-26/03/2019-30 min. )  \nThe last guidance note introduces a process for the review of the quality of the analysis outputs produced by the NIPN.  \n*****  \n1-Data landscape  \n1.1-Objectives of a data landscape exercise  \nThe main objective when conducting a data landscape exercise is to provide an overview of the availability, accessibility and quality of indicators that are of interest to the National Information Platform for Nutrition (NIPN) .  \nThe exact nature of the exercise will vary between countries, depending upon the range of indicatorsand data sources available, time constraints, and the priorities of the NIPN country team.  \nThe exercise typically answers (fully or partially) the following questions:  \n What are the existing information systems of interest to the NIPN? Which datasets and indicators are included? Are there important indicators that are not available? ( see definitions below)  \n What type of information is contained in the datasets? Is the information representative at the sub-national level? How frequent is the data collected? Which data quality control mechanism is applied? How has the data been collected?  \n Where are the datasets? Which institutions have the mandate to collect and manage the datasets? How can the NIPN obtain legal access to the datasets?  \nThe main output of this exercise is a Data Landscape Report (this section, pages 3 to 6) .  \n*****  \nResources to consider before starting a data landscape exercise  \nThere are two resources that are important for all NIPN teams to be familiar with before starting the data landscape exercise:  \n1. Typically, all countries have a National Statistical Plan that describes the statistical environment and national priorities.  \n2. The Scaling Up Nutrition (SUN) Movement has produced Nutrition Information Mapping country reports and case studies which are a good starting point for the data landscape exercise but may not be sufficient.  \n*****  \nDefinitions  \nInformation system, dataset, indicator  \nAn information system is a system of interrelated components that work together for collecting, processing, storing and disseminating information amongst stakeholders/beneficiaries to support decision-making, coordination, control, analysis and visualisation (e.g. DHIS-2; National Statistics Office repository; DHS platform) .  \nA dataset is a file that contains all the individual records of one specific survey (e.g. DHS survey in country “X” of 2005) . A","cbCait11sTUqn6Re","https://ap.wps.com/l/cbCait11sTUqn6Re","pdf",5899319,83,"English","# Data landscape\n## Objectives of a data landscape exercise\n## The use of a data landscape exercise\n# Definitions\n## Information system, dataset, indicator\n# Resources before starting a data landscape exercise","[{\"question\":\"What is the main objective of a data landscape exercise?\",\"answer\":\"To provide an overview of the availability, accessibility, and quality of indicators of interest to the National Information Platform for Nutrition (NIPN).\"},{\"question\":\"What key questions does the data landscape exercise typically answer?\",\"answer\":\"It maps existing information systems, datasets, and indicators, checks how representative the data are at sub-national level and data collection frequency, and identifies where datasets are held and how legal access can be obtained.\"},{\"question\":\"How can the data landscape exercise be used once completed?\",\"answer\":\"It helps determine which nutrition-policy-relevant data are available and of sufficient quality, supports teams in forming policy questions by assessing whether questions can be answered with existing data, and strengthens connections with data providers for future access.\"}]","Managing and analysing data - data landscape - objectives - guidance notes | PDF",1789152471,29]