A highlight of data products from IRIS Data Services

Abstract:

Since 2009 the IRIS Data Management Center has served the seismology community in a variety of ways by offering higher order data products generated internally or by the research community in addition to raw times series data traditionally managed at the DMC. These products are intended to facilitate research as baseline standards, tools for data visualization or characterization, and teaching & outreach material. We currently serve 25 data products of which 7 are event-based that provide quick looks at many aspects of interest to researchers, often within a few hours of real-time.

Among our new offerings is an expansion of the visualization capabilities of the Earth Model Collaboration, a repository of author contributed tomography and other Earth models. Currently EMC tools allow users to make 2D plots slicing through models. New 3D visualization tools being developed will bridge the gap between 2D slices and advanced and sometimes complicated 3D visualization packages with common 3D capabilities that can be set up and learned within minutes. The newly released Global Stacks is a project that stacks up to a million seismograms to illuminate the global seismic wavefield. Seismograms are processed and stacked for three component data across many frequency bands. The resulting stacks lead to high-fidelity wavefield images that clearly highlight characteristics such as dispersion in surface waves and many phases not commonly observed such as P’P’P’P’. Another recent addition is the Automated Surface Wave Phase Velocity Measuring System, which is an automated do-it-yourself surface wave tomography package requiring minimal user input and produces research quality tomography results.

To further enhance our effort to support the research community, we invite proposals for collaborative data product development. This is an excellent opportunity for researchers to put forward unique and useful data product ideas and collaborate with the DMC in the development of the product. While we do not offer funding, this is an opportunity to utilize our resources to make a new data product that will be shared with the community. In the near future, DOIs will be provided for products we host, thereby improving contributor recognition. Details on our data products are available at: http://www.iris.edu/ds/products