The vision for the Center for Geospatial Sciences is to establish a core of excellence at UCR that becomes an internationally renowned source of innovation in geographical information science, open source tools development, application, and dissemination. This vision will be realized by leveraging existing, and emerging, areas of strength from across UCR and by exploiting external opportunities latent in the critical need for spatial analytical perspectives in addressing the major challenges facing our cities, regions, nations, and planet, and is supported by four pillars:

Pillar 1: Fundamental research in spatial analysis

Fundamental research in spatial analysis is the first of the four pillars in this vision. The Center will build long standing research interests in and contributions to the development of novel spatial and spatio-temporal methods by team members. These methods offer the potential to increase our understanding of spatial dynamics and feedbacks inherent in many socioeconomic, environmental, biological, and physical processes. A particular emphasis in this work has been to address questions of scalability and high performance computing so that these new analytics can be applied in the era of big data represented by new types of streaming, network, sensor, mobile, and other non-traditional sources. This research requires scholars with expertise in advanced statistical theory, econometrics, computer science, geocomputation, engineering, and visualization, and bringing together new faculty in these areas will be a top priority to ensure the establishment of an excellent scientific core for the Center, and to advance spatial analysis at UCR.

Pillar 2: Open source software & Open science

The second pillar of this vision is the implementation of the advanced methods of spatial analysis in open source software. Team members have been pioneers in founding, directing, and contributing to leading spatial analytical frameworks. Chief among these is the Python Spatial Analysis Library (PySAL) which has implemented the new analytics developed in our theoretical research. As a result, PySAL now covers a wide array of spatial analytical methods running from deterministic spatial analysis, exploratory spatial analysis, spatial optimization, spatial dynamics, spatial econometrics and spatial networks. Because of these developments PySAL is now seen as a key package in the Python scientific software stack. PySAL has also afforded a number of important collaborations with leading industry partners, such as Esri, as well with as open source projects such as QGIS. Moreover, we are passionate about the role of open source and open science in transforming the practice of scientific research and we are excited about the possibility of the Center playing a leading role in this transformation.

Pillar 3: Collaborative interdisciplinary research

Advanced spatial analysis methods development and their implementation in open source software lead to applications in support of interdisciplinary and transdisciplinary research across a wide array of substantive problem domains. Our record is one of collaboration on large teams where time and again we have seen how spatial analysis and tools can serve as vital scientific glue that binds scholars from different disciplines together in innovative ways. Increasingly, national funding agencies as well as foundations are seeking this type of collaborative interdisciplinary team capacity when targeting research problems involving coupled human-natural systems that blur disciplinary boundaries. The Center offers a powerful mechanism to enhance the competitiveness of UCR proposals seeking large scale research funding where a spatial analytical perspective is central.

Pillar 4: Dissemination & Training

The fourth pillar of the vision for the Center is to establish a major initiative on dissemination and training in advanced geospatial analysis and data science. This will build on our extensive experience in offering workshops and short courses on exploratory spatial data analysis and geocomputation throughout the world. These courses have provided researchers from a vast array of disciplines with skill sets that allow the application of state of art spatial analysis in their own research problems. Alongside the methods training courses, we envisage specialized modules in spatial analytical software development. These modules will be designed to serve a large and growing demand for spatial data scientists in both private industry as well as in non-profits, NGOs and governmental spheres. These training activities also have a strong potential to generate revenue for the Center and UCR.

Together, these four pillars form the foundation of the Center’s mission, yet they are also intertwined and synergistic. Collaboration of large interdisciplinary teams addressing scientific questions in novel ways (Pillar 3) can often generate a demand for further advances in spatial analysis methods. Development of those new methods (Pillar 1) offers new enhancements to PySAL and related tools (Pillar 2). Implementation of the new spatial analytics can serve as the foundation for a studio in the instructional and training mission of the Center (Pillar 4), as well as to broaden and deepen the analytical capability of the Center which, in turn, further elevates the competitiveness of UCR’s research agenda. In these ways, the Center can evolve and expand to create methods, tools, collaborations, and impacts of lasting value.

Code of Conduct

The Center for Geospatial Sciences values the participation of every member of our community. We are dedicated to providing a harassment-free research experience for all members, regardless of gender, sexual orientation, disability, physical appearance, body size, race, religion, or choice of operating system. All Center members are expected to show respect and courtesy to other colleagues at all times. As a research community we do not tolerate harassment of participants in any form.

All communication should be appropriate for a professional audience including people of many different backgrounds. Sexual language and imagery is not appropriate in this Center.

Be kind to others. Do not insult or put down other members. Behave professionally. Remember that harassment and sexist, racist, or exclusionary jokes are not appropriate for this environment.

Individuals violating these rules may be asked to leave the Center.

This code of conduct is an adaptation of the SciPy 2016 Code of Conduct.


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