1. Using Data Issues William Prothero University of California, Santa Barbara

2. Where does data access and display fit into the big picture? Selecting appropriate datasets What is measured, what are the errors, and what does it mean? Constructing a mental model that connects a data representation to a physical process or theory How to fit data observation to a theory Presenting and discussing ideas Writing a report or paper on the results and interpretations

3. Example: the difference between interpretations and observations The separation of ideas into interpretations and observations is specific to each discipline What counts for interpretations and what counts for observations depends on what is accepted as “given” and what is being actively questioned It is reasonable that students have difficulty distinguishing between the two.

4. Additional tools are required Data representation (figures) annotation and markup require integrated or easily used drawing tools Conveniently accessible information about the data Enough theory or background information about the relevant processes

5. Students get overwhelmed to too large a data library Consider the scope of the proposed investigation Provide enough data to answer a rich range of questions (more that a single student or group would address. Leave out irrelevant data

6. The Dataset Jungle Too much data

7. What does this mean for the developer? The data deliverer must be strongly connected to the educators that use the data so that appropriate datasets can be selected and the range of potential investigations defined. Comprehensive examples of how the data can be used to investigate interesting phenomena are essential

8. The Platform Problem To be useful, the data browser must run on both Mac’s and PC’s. Which OS? OSX, OS9 Win95, Win98, WinXP, Win2000 Which browser? Explorer (MS is ending IE development for Mac) Safari (Mac)

9. Design for browsing, make it easy to use Many research based data browsers have obstacles that make students much less likely to use, or browse them. Slow response Inconvenient or unintuitive data access controls and user interface Unexpected quirks in the display (inverted depths, for example) No way to get the display to their desktop for inclusion in reports or presentations Jargon: for example, “zonal” and “meridional”, “analyzed” and “raw”.

10. NVODS on Safari Browser (Macintosh)

11. Lamont IRI Site: could be better

12. Lamont IRI Depth plotted upwards Let’s make it even harder

13. NVODS: Depth goes up, too.

14. Cognitive help is needed with mental models created from cross-sections Students have a seemingly unusual difficulty creating a 3-D mental model from cross-sections

15. The Good News Common Sense Prevails Make an interface that you would like to use yourself, if you were working with unfamiliar subject matter Watch students use it. Note where they get confused Facts: Students are very resourceful. Give them enough information and they will figure out how to use an interface: I.e. it’s NOT about where the buttons are, it’s about making it possible for them to figure it out without too much effort.

16. Difficult Challenges for developers: Bugs: students are surprisingly tolerant of bugs, until too much of their time is wasted. It is very difficult to keep complex software reasonably bug free. User support Obsolescence: the constantly changing software landscape Upgrades and new features OS changes Development platform enhancements A complex resource requires “lifetime” maintenance.

17. Two Examples of Successful Data Delivery Resources Our Dynamic Planet Developed in 1994; maintained and enhanced ever since. It began on Hypercard, migrated to SuperCard, then ended up in Macromedia Director. Global Ocean Data Viewer A joint project between New Media Studio and William Prothero Based on IDL graphics engine and Macromedia Director