MetApps Discussion

Progress to Date (illustrated with demos)

MetApps prototypes:

• Image Viewer  (IV)
• Interactive Sounding Application (ISA)
• Gridded Data Viewer  (GDV)
• Earlier Surface Obs Viewer components and lessons are embedded in the above Viewers.

Advances in underlying fundamentals:

• The above prototypes deal with important, difficult problems, including:
• image navigation  (IV)
• multiple projections (all)
• thermodynamic coordinate transforms (ISA, GDV)
• interactive selection & manipulation of data points (ISA, GDV)
• direct access to remote data servers (IV, ISA, soon GDV)
• interactive selection of input data (all)
• interactive cross-sectioning (GDV)
• color-table manipulation (IV, GDV)
• direct value readout (ISA, GDV, soon IV)
• 3D rendering (all)
• highly connected component networks  (ISA, GDV)
• zoom & pan (all)
• animation (IV, GDV)
• Prototypes embody key discipline- & data-independent abstractions.

Communication structure:

·           Requirements

·           Approaches

o       email

o       UMADA

§         Centralized discussion area

§         Historical record of transactions

§         Combines documentation and use cases

Collaborations:

·        Australian Bureau of Meteorology (wind components, ADDE data access, data abstractions)

·        SSEC (VisAD, ADDE access, data abstractions)

·        NCAR - ATD/RAP (radar displays), CGD (GDV)

Lessons Learned

Suitability of the chosen infrastructure

• Java is adequate & getting better.
• Java (esp Java3D) is not yet as portable as hoped.
• VisAD is viable & has powerful data & display models.
• VisAD is difficult to learn & needs improved documentation.
• Java Beans are useful largely for internal development at this stage.

Effectiveness of the process

• User-centered design is suitable & workable.
• Task force input is sporadic & requires seeding.
• We understand better the kinds of communication required.
• Extensive user involvement is unrealistic until MetApps are really useful (e.g., satisfies a use case).
• The "Planning Game" method (Extreme Programming) can be effective.

Technical issues

• Development is resource intensive & many of the tasks are hard.
• Collaboration takes effort and resources but can have benefits
• Other Unidata matters (LDM/IDD, e.g.) often distract from MetApps.
• We have not agreed on a data model, & the problem is very hard.

Future Directions

Near-term objectives

• DODS and enhanced ADDE access for MetApps, VisAD
• Radar data viewer (in collaboration with ATD/RAP/TF and ?)
• Initial design of integrated application
• Framework for derived quantities (specification, selection)
• Explore mechanisms for broad community input on prototype and component development

Long-term objectives

• One or two integrated applications with broad functionality similar to, but not replacing, GEMPAK & McIDAS  (Data-type extensibility more important than feature matching)
• Component architecture, as practical
• A few applets for users to embed in education materials
• Broad data-access & data-discovery landscape, linked to DLESE
• Architecture & framework for user authoring & assembly
• Data & metadata models that support the above