1. Janice E. Cuny, Ph.D., Department of Computer and Information Science, University of Oregon cuny@cs.uoregon.edu Judith B. Cushing, Ph.D., Department of Computer Science, The Evergreen State College judyc@evergreen.edu Douglas R. Toomey, Ph.D., Department of Geological Sciences, University of Oregon drt@newberry.uoregon.edu Dawn J. Wright, Ph.D., Department of Geosciences, Oregon State University dawn@dusk.geo.orst.edu The prototype of a computational environment and toolset, called the Virtual Research Vessel (VRV), is being developed to provide scientists and educators with ready access to data, results, and numerical models. While this effort is focused on the EPR 9N region, the resulting software tools and infrastructure should be helpful in establishing similar systems for other sections of the global mid-ocean ridge. Work in progress includes efforts to develop: 1) a virtual database to incorporate diverse data types (along with domain-specific metadata) into a global schema, allowing for web-query across different marine geology data sets, and an analogous, declarative (database-available) description of tools and models; 2) the ability to move data between GIS and the above DBMS, along with the tools to encourage data submission to archives; 3) tools for finding and viewing archives, and translating between formats; 4) support for "computational steering" (tool composition) and model coupling (e.g., the ability to run tool composition locally, but access input data from the web, application programming interfaces (APIs) to support coupling, especially of programs that are running, and help in writing data wrappers to publish programs); 5) support of migration paths for prototyped model coupling; and 6) export of marine geological data and data analysis to the undergraduate classroom (VRV-ET, "Educational Tool"). For more information, please visit oregonstate.edu/dept/vrv and www.cs.uoregon.edu/research/vrv-et. The East Pacific Rise (EPR) from 9-10°N is currently our best-studied section of fast-spreading mid-ocean ridge, and has recently been chosen as a RIDGE 2000 Integrated Study Site. During several decades of investigation, it has been explored by the full spectrum of ridge investigators, including chemists, biologists, geologists and geophysicists. These studies, and those that are ongoing, provide a wealth of observational data, results and data-driven theoretical studies that have not yet been fully utilized, either by research scientists or by professional educators. While the situation is improving, a large amount of data, results, and related theoretical models still exist either in an inert, non-interactive form (e.g., journal publications), or as unlinked and currently incompatible computer data or algorithms. Infrastructure is needed not just for ready access to data, but for linkage of disparate data sets (data to data) as well as data to models, in order to quantitatively evaluate hypotheses, refine numerical simulations, and explore new relations between observables. In an attempt to provide this infrastructure, the Virtual Research Vessel (VRV) is being developed as a prototype of a computational environment and toolset for the East Pacific Rise. Faculty: Jan Cuny, Doug Toomey; System designer: Joshua Rogers (U of O) In conjunction with our VRV-1 research, we are building a prototype set of tools that support web- based collaboration. These tools, which will eventually form the interface for the VRV-1 environment, are being used, tested, and evaluated in building an exhibit entitled, the Volcanic Galápagos. An early prototype of the tools can be seen at http://pyros.cs.uoregon.edu:8080. The tools are designed to allow scientists/educators at remote locations to participate collaboratively in the design and evolution of our exhibit. This will allow us to keep the web-based content current with the diverse scientific efforts of a team of researchers and it will enable other researchers to add material. Faculty: Jan Cuny, Doug Toomey; Graduate Students: Tom Bulatewicz, Maureen Ford, Matt Sottile (U of O) Many computational models of isolated phenomena are now well understood and captured in robust programs. The challenge now — for the ridge community as well as many other communities — is to couple these models into self-consistent representations of more complex processes. Coupling is more complex than program composition. Scientists are faced with the poorly understood task of establishing sophisticated time-varying relationships between models and large, multi-dimensional data that are heterogeneous in quantity, quality, scale, type, and ultimately importance. To accomplish this, they will need more than standard coupling mechanisms; they will need support for dynamically exploring model correlations and relationships at a very high, domain-specific level. We are building infrastructure to support the fast prototyping of model couplings. Robust, abstract descriptions of existing computational models (existing code) will be made available in a common database, a graphical interface will allow scientists to easily specify couplings between models, and the required interfaces and runtime monitor will be automatically generated. Current Work A final code description created with minimal user assistance and deposited in the common database. while (c->num_v_in >0) { If (c->num_v_in == 1) { exit_cell(c,0,c->vEnter->v); c->vEnter = remove_particle(c->vEnter); c->num_v_in = 0; annotate.available ( c ); } else { cur_v = c->vEnter->v; opposite = find_particle(c->vEnter,0-cur_v if (opposite == NULL) { /* no opposing p while (c->num_v_in > 0) { exit_cell(c,0,c->vEnter->v); c->vEnter = remove_particle(c->vEnte c->num_v_in = c->num_v_in - 1; } Computational Automatically Generated Database Model Intermediate Form Representation (Source code is (The program's control flow annotated with graph is automatically compressed coupling potentials.) with respect to the annotations.) Geographic Information Systems (GIS) provide an invaluable way to simultaneously view spatial data in the form of a map and access the data that is related to the features displayed. ArcInternetMapServer (ArcIMS) takes GIS a step further by bringing general GIS functions to the Internet. With ArcIMS, users can perform GIS functions such as spatial query, buffering, clipping data and routing over the Internet. ArcIMS has the potential to allow simultaneous access to both web data from the server and local data from the client’s desktop, and the ability to dynamically edit and annotate maps. Users can also potentially contribute their own spatial data layers. EPR data is being compiled from several resources to create the Virtual Research Vessel prototype atlas. Data consist of vector layers such as observations, samples, and fissures, as well as grid layers such as bathymetry. Users can utilize the atlas to view the data and perform spatial analysis. The dynamic nature of ArcIMS will create a simple way for finding and viewing spatial data, translating between formats, and encouraging future data submission to archives. Faculty: Judy Cushing (TESC), Rahul Tikekar (SOU); Students: James Gutholm, Peter Boonekamp (TESC); Aparna Kulkarni, Seth Joslin (SOU); Kristel Lyn Hackett (U of O) Physical access to other scientists’ data sets or artifacts derived from those data such as a recently generated map is a good first step, but not sufficient for effectively using those data for computational analyses. This part of the project focuses on common data models that can provide data, programs and metadata in a uniform manner, and has three focii: 1) a data model for marine geology data that abstracts across cruise formats (Figure A1), 2) an infrastructure so that metadata for data sets published with different formats, or buried within data files, can be viewed as if they were all of the same format, and 3) a distributed infrastructure so that data files and application output could be viewed as database queries (Figure A2). The metadata viewer (2) and the infrastructure for integrating marine geology data and applications (3) use LeSelect, a framework for accessing heterogeneous data and programs over internet environments. LeSelect, developed by Eric Simon and colleagues at the Institut Nationale pour Recherche en Informatique (INRIA), France, provides an underlying mechanism for distributed access to files, databases and programs. We extend LeSelect by providing wrappers that map marine geology data files, metadata and programs onto commonly recognized names and formats, and clients that provide a uniform application interface for marine geology. Figure A2: Metadata Viewer, and Infrastructure for Integrating Marine Geology Data and Applications Adventure Data Predict Physical Properties Geodynamic Modeler Wrapper Data Model Image Physical Properties Seismic Data Modeler Argus Data Metadata Wrapper Metadata Model LeSelect Client Figure B2: Example of pages from the Virtual Research Vessel - Educational Tool. Funded by: NSF/ITR ACI-0081487 Initial Data Contributors: University of Oregon Department of Geological Sciences Oregon State University Department of Geosciences UCSB Department of Geological Sciences University of Washington Mid-Ocean Ridge Processes Group Hawaii Mapping Research Group Research in the earth sciences routinely yields a wealth of observational data and results spanning a range of disciplines, including geophysics, chemistry, theoretical fluid mechanics and biology. As yet though, this complementary information has not been fully utilized. Most of it exists either in inert, noninteractive form (e.g. journal publications) or as unlinked and incompatible data sets and models. Scientists studying mid-ocean ridges have taken the first steps in data archiving, but mere collections of publicly available data will not be sufficient. Scientists will need a wide range of sophisticated programming support to coordinate the use of data, computational tools, and numerical models across distributed networks of computers. Figure B1: ArcIMS offers a method of dynamically viewing spatial data on-line. Faculty: Dawn Wright; Graduate Student: Liz O’Dea Poster designed by Liz O’Dea Figure C1: Model Coupling Process Figure A1: Marine Geology Data Model