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Strategies for web based data dissemination A strategy is a plan of action designed to achieve a vision - from Greek "στρατηγία" (strategia). Zoltan Nagy.

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Presentation on theme: "Strategies for web based data dissemination A strategy is a plan of action designed to achieve a vision - from Greek "στρατηγία" (strategia). Zoltan Nagy."— Presentation transcript:

1 Strategies for web based data dissemination A strategy is a plan of action designed to achieve a vision - from Greek "στρατηγία" (strategia). Zoltan Nagy – Statistics Division, Department of Economic and Social affairs, United Nations United Nations Regional Workshop on Data Dissemination and Communication Rio de Janeiro, Brazil, 5 - 7 June 2013

2 Existing Strategies Fundamental Principles of Official Statistics “ statistics that meet the test of practical utility are to be compiled and made available on an impartial basis by official statistical agencies to honor citizens' entitlement to public information” Handbook of Statistical Organizations National Strategies for the Development of Statistics (NSDS) The Generic Statistical Business Process Model (GSBPM)

3 Data dissemination = communication Policy making Professionals & public C OMMUNICATION Analysis & research Statistical needs and education Knowledge based society Policy accountability Analysis & assessment Policy options Policy decisions Policy validations INDEPENDENT OFFICIAL STATISTICS ECONOMIC AND SOCIAL PROGRESS

4 The importance of web-based data-dissemination Everyone who has access to internet is becoming a potential user of statistics. From 2008 to 2013 the number of Internet users grows by 67% Forget the last war.

5 Identifying users User groups  Decision makers (government at central and local level, businesses)  Academia (institution that use, research and analyze data)  Educational (primary, secondary, tertiary)  Public at large Tourists Harvesters and (data) Miners

6 Tourists Novice or infrequent users, and typically make up the majority of individual users. Looking for basic data either out of curiosity, or to inform personal decisions. Want to be able to find and view data quickly and easily, they prefer low levels of complexity and need only limited functionality.

7 Harvesters Intermediate and fairly frequent users, who are looking for data to inform basic research or economic decisions. They will accept increased complexity if it results in addition functionality and flexibility in the way they can view and download data.

8 (Data) Miners Expert users, typically small in number, but using large volumes of data on a regular basis, often for detailed research or analysis. They want simplicity, easy downloads functionality and flexibility, take data offline

9 A new type - Builders Experts that want to reuse statistical data without copying or downloading it. Requesting ability to access data servers at 24/7 and feed data to maps, visualizations and other applications. Web services - interoperable machine-to-machine interaction over a network". Mashups – hybrid web applications  Visualizations  Mappings  Data aggregators

10 Defining the content Data  Topic – domain specific or across-domain  Coverage – geographical and time  Aggregation level - micro and macro data  Nature of the data – tables, tabulations, time-series, datapoints Documentation  Metadata (descriptive and structural)  Methodologies and standards  Classifications  Best practices, business processes, etc.

11 Subscription models Registration  No registration required  Registration required (provides better tracking, communication etc) Subscription  Free (preferred by many countries)  For fee (cost recovery, profit, one-time, periodical, service based )  Multi-tier (free basic and for fee premium services)

12 User management User access (registered vs unregistered users) User support, helpdesk User surveys (online polling) User activity tracking  Web server statistics  Analytic services (Google analytics)  Custom built tracking services Social networking (Facebook, Twitter..)

13 Site administration Data Management  Data correction facility  Data upload facility  Data availability Metadata Management  Structural metadata  Descriptive metadata  Data upload calendar Management Reporting

14 Resource allocation +Data dissemination group (Centralized or Decentralized) +Systems/Application development +Hardware and software requirements +Long-term maintenance +Operation +Helpdesk -------------------------------------------------- = TOTAL COST OF OWNERSHIP (TCO)

15 Content delivery Bandwidth conservation Browser considerations

16 Mobile devices

17 Software platform and architecture Off-the-shelf products Custom development (in-house, outsourcing) Open source platforms Proprietary platforms Self hosting Outsourced hosting

18 Design considerations Simplicity and ease of use Easy of navigation Bookmarking Searchability  Drill down  Dimensional search  Full text search

19 Conclusions One size does not fit all Web-based data dissemination should work as a two way communication Focus has to be on users who frequently visit our sites The maintenance of web-based data-dissemination products is a long term commitment We have to be aware of TCO

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