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IRI/LDEO Climate Data Library

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Presentation on theme: "IRI/LDEO Climate Data Library"— Presentation transcript:

1 IRI/LDEO Climate Data Library
M.Benno Blumenthal, Michael Bell, John del Corral, Remi Cousin, and Haibo Liu International Research Institute for Climate and Society Columbia University

2 Structure leads to powerful applications
The Data Library's open data model and ability to create networks of virtual web pages and resources leads to some powerful applications

3 Overview multidimensional Specialized Data Tools Maproom
Generalized Data Tools Data Viewer Data Language So here is the IRI/LDEO Data Library shot at this, connecting the space of data and data manipulations. At the bottom we have the compute engine/data organization, which is what maps the data/manipulation space into URLs, i.e. the WWW. Built on top of that are some general data tools, i.e. they can be applied to any dataset and adapt accordingly. There is a data language, making it possible to specify sophisticated analyses. And there is a data viewer, making it possible to quickly graph data in a number of standard ways. And there are also more specialized tools, designed for particular audiences to view specific things. We have a Maproom (soon to be or already map rooms) which contains continuously updated views of aspects of the climate system, as well as specialized tools aimed at particular audiences that let a use extract views/data with a few clicks. There is a tradeoff here: the general tools are great, but require a user to navigate a vast set of datasets and a vast set of possible manipulations, which not everybody is up to. The specialized tools are a way to make sophisticated calculations easy to access. IRI Data Collection Dataset Variable ivar multidimensional URL/URI for data, calculations, figs, etc

4 Possible Projects Maproom into SEVIR Viz Maproom into Google Earth
Integration with Open Health Mapper Standalone Data Library Semantic Translation for Data Discovery Establish Process for USAID maproom development Facilitating climate journalism

5 Integration with SEVIR Viz

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8 WMS and KML: land cover Integration with GoogleEarth
IRI General Data Tools WMS and KML: land cover (link:figure page)‏

9 WMS and KML: precipitation
IRI General Data Tools WMS and KML: precipitation (link: figure page)‏

10 Integration with Open Health Mapper
Based strictly on WMS EMS Mapper involves google projection Cataloging to follow

11 Standalone Data Library
Essentially a miniaturization of Data Library Server Clean packaging of all components Retrieving/Storing/Updating partial dataset copies

12 Semantic Translation of Data Catalogs
SERVIR Viz Data Widget Google Earth Data Discovery (web interface) Google Earth Data Discovery (folders) Climate 1-stop Data Discovery

13 Faceted Search (link)‏

14 Process for USAID Maprooms
IFRC Model Determining needs Determining data Building prototype and iterating Deploying in multiple media

15 Faciliating Climate Journalism
Providing tools/information for writers to inform their audiences

16 Possible Projects Maproom into SEVIR Viz Maproom into Google Earth
Integration with Open Health Mapper Standalone Data Library Semantic Translation for Data Discovery Establish Process for USAID maproom development Facilitating climate journalism


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