Daniel Ames, Ph.D. - US grants

Idaho State University is developing FossilPlot, a free-access, internet-based software tool and set of reusable teaching modules that aims to enhance active and quantitative learning of the fossil record at the undergraduate level. Founded on the Sepkoski Database, the program gives educators and their students the ability to compile any combination of 36,000 marine animal genera to create graphs illustrating faunal diversity and their geologic ranges over the Phanerozoic. Teaching modules are designed for specific teaching targets in Historical Geology and Introductory Paleontology courses, and are organized to complement teaching activities in the classroom, laboratory and field trip setting. The FossilPlot program and teaching modules are created by a team of faculty, Masters and Doctoral students with specialties in subject matter content, instructional design, and software engineering to ensure alignment between teaching targets and software content, and to produce a user-friendly interface that facilitates learning objectives. The FossilPlot program and teaching modules will be implemented and assessed by a focus group of professors and students at Idaho State University, the University of Utah, the College of Wooster (Ohio), the University of Witwatersrand (South Africa), and the Katholieke Universiteit Leuven (Belgium). Feedback from the assessments will inform modifications to the program and result in an updated version of FossilPlot by the completion of the project.

This project creates a multidisciplinary research virtual organization (SOCNET) of historians, geographers, computer scientists, and mathematicians to share historical social science data and develop geographically integrated frameworks to address complex, dynamic, nonlinear systems and social networks.

Through multidisciplinary collaboration, SOCNET will fuse qualitative and quantitative data to connect humans, events, and environments, and through such connections form historical narratives within and across geographic spaces. The project's ultimate goal is to better infuse computational thinking into the historical social sciences through computational innovation and narrative knowledge creation to revolutionize research outcomes in these disciplines with a shift to Geographically-Integrated History. SOCNET's developments in Dynamics GIS (geographic information systems) and related information technologies will provide the backbone for understanding complex historical social systems with three components that define the geographically-integrated history paradigm: (1) the history of any place is shaped in significant ways by the way the place is connected to other places and by the changes in these connections over time; (2) historical periods are complex, dynamic, nonlinear systems that are spatially large, and in more recent centuries, global in extension, and these systems sometimes become unstable, leading to a phase transition, bifurcation, and the organization of new systems; and (3) within such systems, people and places are connected by social networks in a self-organizing fashion.

Focusing on the first global age (1400-1800), SOCNET will transform historical research with computational thinking on (1) new means for the representation of data for organizing, storing, manipulating, and recovering them for exploration using computational tools; (2) new spatial-temporal GIS for the visualization and analysis of real world dynamics; (3) new tools for data harmonization and text mining; (4) new approaches to the use of information that is vague, uncertain, and incomplete and of qualitative data within a computational context; (5) new forms of modeling to represent the inferences of domain experts; and (6) new metaphors beyond the map and animation-based visualization for temporal GIS. Collaborative protocols, tools, models, data structures, and algorithms developed in the project will be shaped and presented in web-based educational materials to provide interested researchers and their students with easy access.

Beyond the historical social sciences and geographic information science, SOCNET will promote innovations in computer science, mathematical modeling and simulation, environmental sciences, medical research, and transportation studies. Collaborating computer scientists and mathematicians will develop innovative computational concepts and tools to better capture the dynamism of overlapping, multi-dimensional social networks within a complex, nonlinear system. In solving the difficulties associated with using historical information within a computational environment, SOCNET will further promote the idea of 'spatial turn' within history and the historical social sciences.

Because of the higher percentage of women and minorities among majors in the historical social sciences, the project will attract such students into a technologically rich educational and employment environment. The project will support the development of an existing Master's in geographically-integrated history, a forthcoming interdisciplinary Ph.D. in Social and Environmental Dynamics, a future M.S. in Computer Science and Computational Sciences, and a new interdisciplinary degree program in Geoinformatics, providing students educational emphases on geographic information science and technology to seek better understanding of dynamic human and environmental systems.

This award is providing funds to upgrade digital mapping facilities for the Idaho State University Digital Mapping Laboratory. The workstations, servers, and associated gigabit network connections supported by this grant are providing modern work stations that will better service existing and future research projects at ISU. The digital mapping facilities supported by the project are contributing to four interdisciplinary near-surface research themes: field characterization and modeling of landscape response to contemporary and ancient changes in climate or tectonics; short-term landscape, soil, and vegetation change as documented by hyperspectral and light detection and ranging (LiDAR) techniques; geospatially distributed, GIS-based hydrologic and water quality modeling at the watershed scale in mountain environments, and simulation of ground-water flow based on statistical analysis and 3-D modeling of inter-bedded volcanic and sedimentary deposits. Each of these research groups pair innovative datasets and techniques against applied and theoretical questions that advance our understanding of water resources, climate change and remote sensing capabilities.

The computer facility upgrade is supporting the research efforts of several early career researchers at Idaho State University, as well as promoting teaching and training of a core group of graduate and undergraduate research assistants in the Department of Geosciences. Increased access to remote sensing and GIS data and applications complements the student-directed research projects in hydrology, structural geology, stratigraphy, geomorphology, and petrology. Results of these projects are being incorporated into the undergraduate and graduate curriculum. Over the lifespan of these computers, about 375 geoscience majors and graduate students are expected to benefit from these facilities. Because approximately 40% of the students who will use the laboratory are members of an underrepresented group, the award is helping to broaden participation in the geosciences. The research projects supported by this award are expected to have a societal impact specifically on decisions regarding Idaho's land use, water resources, and urban expansion and economic development.

Water, its quality, quantity, accessibility, and management, is crucial to society. However, our ability to model and quantitatively understand the complex interwoven environmental processes that control water and its availability is severely hampered by inadequate tools related to hydrologic data discovery, systems integration, modeling/ simulation, and education. This project develops sustainable cyberinfrastructure for better access to water-related data and models in the hydrologic sciences, enabling hydrologists and other associated communities to collaborate and combine data and models from multiple sources. It will provide new ways in which hydrologic knowledge is created and applied to better understand water availability, quality, and dynamics. It will also help to provide a more comprehensive understanding of the interactions between natural and engineered aspects of the water cycle. These goals will be achieved through the development of interoperable cyberinfrastructure tools and the creation of an online collaborative environment, called HydroShare, which enables scientists to easily discover and access hydrologic and related data and models, retrieve them to their desktop, and perform analyses in a high performance computing environment. The software to be developed will take advantage of existing NSF cyberinfrastructure (iRODS, HUBzero, CSDMS, CUAHSI HIS) and be created as open source code. Its development will be end user-driven. In terms of broader impacts, the project builds essential infrastructure for science by developing software tools and computing environments to allow better understanding of the impacts of climate change (i.e., floods, droughts, biofuels, etc.) and to allow improved water resource development and the management of freshwater resources both above and below ground. Resulting software will be made publicly available and provides a strong student and workforce training/education component. In addition, the project supports an institution in an EPSCoR state and engages, as a PI, a person who is from a group under-represented in the sciences and engineering.

Geoscience information is defined on both discrete and continuous spatial domains. Discrete
spatial domains include point locations of observations at measurement sites and GIS coverages
of point, line and area features used for observation and data interpretation. Continuous
spatial domains are used in geophysical fluid sciences such as for the atmosphere, oceans,
and land subsurface to describe arrays of measured or modeled variables defined on a mesh
of uniformly spaced points. Data defined on either discrete or continuous spatial domains
may also vary discretely or continuously in time, ranging from one-time samples, to samples
at random points of time, to samples at regularly spaced intervals of time. This project
builds upon previous work called "Crossing the Digital Divide" focused on integrated discovery
of common information themes including precipitation in discrete data from the CUAHSI hydrologic
information system and continuous data from the Unidata THREDDS data server. This project
will advance that work by investigating in the first year creating new technologies for publishing
and discovery of information through the Global Earth Observation System of Systems (GEOSS)
Common Infrastructure, the definition of a Common Information Model for discrete and continuous
data, development of shard software tools for using this Common Information Model, and extension
of the concepts to similar information in the Polar, Ocean and Solid Earth Sciences.

This work builds on existing NSF data infrastructures and extends them in a reasonable way between two domains, Hydrology and Atmospheric Sciences, which are closely related intellectually, but have very different data environments. Some
further extension into the Polar, Ocean and Solid Earth Sciences is also attainable. The project include the engagement of an international spectrum of collaborators
through the Global Earth Observing System of Systems.

Hydrology and water resources engineering is an important subject area for undergraduate engineering students who pursue careers related to water management and water infrastructure, such as flood forecasting and flood protection. By developing a web-based platform (HydroLearn) to facilitate collaboration and sharing of online active-learning teaching resources, this project will change the way in which learning resources are developed and adopted. Using modern web technologies, HydroLearn will provide national and global access to materials that will enable faculty to collaboratively develop learning content in the area of water resources. HydroLearn will be a collaboration with the National Water Center and will use their National Water Model to provide students and faculty with innovative learning opportunities that address water problems with immediate community impacts. To disseminate the results at a national scale, investigators will collaborate with the Consortium of Universities for the Advancement of Hydrologic Science, Inc., which represents more than 100 U.S. universities and organizations. Further, during this project, fellowships for faculty and early-career scientists will be provided to support the development and testing of the learning resources via engagement with the water resources engineering community.

More specifically, this project has two main objectives: (1) to support hydrology and water resources engineering faculty to develop, share, and adopt active-learning innovations; and (2) to support effective student learning in key areas of hydrology and water resources engineering, focusing on flood analysis, modeling, forecasting and protection. Using an interactive process of development and propagation, the web-based platform (HydroLearn) that will be developed will showcase the following capabilities: (a) interoperability and integration with community hydrologic data and modeling resources; (b) flexibility in faculty users being able to create their own content modules; (c) creating material ownership via crowdsourcing of learning content using an open source approach to develop a sense of community; and (d) ease in teaching material adoption and customization. The project will contribute to closing the gap between development of innovations and actual adoption by following a design model that engages potential adopters at early stages and throughout the entire project using an active dissemination approach with direct feedback on adopters' needs to facilitate future utility and adoption.

Researchers across the country and around the world expend tremendous resources to gather and analyze vast stores of hydrologic data and populate a myriad of models to better understand hydrologic phenomena and find solutions to vexing water problems. Each of those researchers has limited money, time, computational capacity, data storage, and ability to put that data to productive use. What if they could combine their efforts to make collaboration easier? What if those collected data sets and processed model outputs could be used collaboratively to help advance hydrologic understanding beyond their original purpose? HydroShare is a system to advance hydrologic science by enabling the scientific community to more easily and freely share products resulting from their research, not just the scientific publication summarizing a study, but also the data and models used to create the scientific publication. HydroShare supports the sharing and publication of hydrologic data and models. This capability is necessary for community model development, execution, and evaluation and to improve reproducibility and community trust in scientific findings through transparency. As a platform for collaboration and running models on advanced computational infrastructure, HydroShare enhances the capability for data intensive research in hydrology and other aligned sciences. HydroShare is designed to help researchers easily meet the sharing requirements of data management plans while at the same time providing value added functionality that makes metadata capture more effective and helps researchers improve their work productivity. This project will extend the capabilities of the HydroShare cyberinfrastructure to enhance support for scientific methods, advance the social capabilities of HydroShare to enable improved collaborative research, integrate with 3rd party consumer data storage systems to provide more flexible and sustainable data storage. and establish an application testing environment to empower researchers to develop their own computer programs to act on and work with data in HydroShare. Empowering HydroShare users with the ability to rapidly develop web application programs opens the door to unforeseen, innovative combinations of data and models. WRF-Hydro, the framework for the NOAA National Water Model, will be used as a use case for collaboration on model development. Since WRF-Hydro is used by NOAA as part of the National Water Model (NWM), this collaboration opens possibilities for transfer of research to operations. Collectively, this functionality will provide a computing framework for transforming the practice of broad science communities to leverage advances in data science and computation and accelerate discovery.

HydroShare is a system for sharing hydrologic data and models aimed at giving hydrologists the cyberinfrastructure needed to manage data, innovate and collaborate in research to solve water problems. It addresses the challenges of sharing data and hydrologic models to support collaboration and reproducible hydrologic science through the publication of hydrologic data and models. With HydroShare users can: (1) share data and models with colleagues; (2) manage who has access to shared content; (3) share, access, visualize and manipulate a broad set of hydrologic data types and models; (4) use the web services interface to program automated and client access; (5) publish data and models to meet the requirements of research project data management plans; (6) discover and access data and models published by others; and (7) use web apps to visualize, analyze, and run models on data. This project will extend the capabilities of HydroShare to: (1) enhance support for scientific methods enabling systematic data and model analysis and hypothesis testing; (2) advance the social capabilities of HydroShare to enable improved collaborative research; (3) integrate with 3rd party consumer data storage systems to provide more flexible and sustainable data storage; and (4) establish an application testing environment to empower researchers to develop their own computer programs to act on and work with data in HydroShare. Under development since 2012 and first released in 2014, HydroShare supports the sharing and publication of hydrologic data and models. This capability is necessary for community model development, execution, and evaluation. As a platform for collaboration and cloud based computation on network servers remote from the user, HydroShare enhances the capability for data intensive research in hydrology and other aligned sciences. HydroShare is innovative from a computer science and CI perspective in the way computation and data sharing are framed as a network computing platform that integrates data storage, organization, discovery, and programmable actions through web applications (web apps). Support for these three key elements of computation allows researchers to easily employ services beyond the desktop to make data storage and manipulation more reliable and scalable, while improving ability to collaborate and reproduce results. The generation of new understanding, through integration of information from multiple sources and reuse and collaborative enrichment of research data and models, will be enhanced. Structured and systematic model process intercomparisons and alternative hypothesis testing will be enabled, bringing, through user friendly CI, the latest thinking in advancing hydrologic modeling to a broad community of earth science researchers, thereby transforming research practices and the knowledge generated from this research. Interoperability with consumer cloud storage will greatly ease entry of content into HydroShare and support its sustainability. This meshing of the rigorous metadata model of HydroShare with consumer file sharing will enhance reproducibility as well as provide an innovative mechanism for sharing and collaboration. Empowering HydroShare users with the ability to rapidly develop web apps opens the door to unforeseen, innovative combinations of data and models. WRF- Hydro will be used as a use case for collaboration on model development. WRF-Hydro provides a reach-based high resolution representation of hydrologic processes, and offers the potential to bring together scientists working at scales from research catchments on the order of 1 to 100s of square kilometers as well as those working at regional to continental scales and cut across disciplines from environmental engineering to aquatic ecologists. Since WRF-Hydro is used by NOAA as part of the National Water Model (NWM), this collaboration opens possibilities for transfer of research to operations. This project will adapt current best practices in CI for interoperability and extensibility to serve this multidisciplinary community of scientists. HydroShare has already had a broader impact, with documented rapid growth in use and uptake by other projects including in EarthCube. It will become sustainable community CI through operation as part of the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) Water Data Center (WDC) facility. The use of WRF- Hydro/NWM, as a driving use case, will advance CI for community based model improvement. Through the Summer Young Innovators Program at the National Water Center (NWC), supported by the National Weather Service (NWS) and operated by CUAHSI, a pathway already exists to translate research findings to the operational needs of federal agencies participating in the NWC. HydroShare already touches a broad and diverse community, with user base including Native American tribes, hydrologic science students, and faculty researchers across the U.S. This proposal builds on the success of HydroShare to extend its capabilities and broaden model hypothesis testing, collaborative data sharing, and open app development across earth science research and education.