The landscape of socio-environmental research is evolving. Understanding the factors and processes that influence the dynamics of coupled socio-environmental systems (SESs) requires research that harnesses a diversity of data sources and types (quantitative and qualitative) for use with sophisticated analytical and modeling tools. Consequently, data-intensive analytic and modeling approaches have emerged as critical needs for supporting socio-environmental research.
The National Socio-Environmental Synthesis Center (SESYNC) announces a special invitation for proposals for data-intensive or modeling projects that can advance socio-environmental research. Successful proposals will pursue questions critical to understanding the social or ecological dynamics of SESs by:
- integrating large and/or heterogeneous data sets OR
- developing innovative data integration, organization, and/or visualization approaches for use with computationally-intensive data analysis and/or modeling efforts.
SESYNC has significant modeling, data analysis, and database management expertise to guide teams that need assistance with the technical aspects of data mining, processing, integration, visualization and/or modeling.
In addition, we may cover the costs of a research assistant to support project activities. Projects that will utilize a SESYNC research assistant must include a detailed description of the expected responsibilities and desired skills required of the position. A research assistant position could be filled by a graduate research assistant, postdoc, programmer, or database technician depending on the technical skills required. If merited, SESYNC will alternatively support a project team member at his or her home institution. Project team members receiving salary support from SESYNC are required to attend SESYNC's 2014 Computational Summer Institute. Attendance of additional team members is not required, but is encouraged.
Funded projects will gain access to SESYNC’s advanced cyberinfrastructure, including use of and support for scalable cluster computing and substantial storage capacity (10’s of terabytes per project). Funded projects also receive support for meetings at SESYNC in Annapolis, MD, including travel and group facilitation.
This funding opportunity covers two types of projects (not mutually exclusive):
- Data Integration and Analysis: Addressing challenging questions on SESs often requires the integration of heterogeneous, large-scale, or highly detailed data sets from multiple regions and disciplines, yet many natural and social science scholars lack the informatics skills, time, or resources to undertake these tasks. Since this is often a major obstacle for answering critical research questions, SESYNC invites projects that will combine large and/or heterogeneous social and environmental data to address novel and actionable socio-environmental questions. SESYNC will provide support for teams whose socio-environmental research programs will be substantially enhanced through the use of data mining, processing, integration, and/or visualization technologies. We also invite proposals to develop innovative informatics approaches and/or tools that will advance socio-environmental synthesis.
- Data-Intensive Modeling Methodology and Applications: Given the complexity and cross-scale nature of many SESs, field-based experimental research may not be feasible, making modeling and/or analysis of multi-scale and multi-sector data essential for generating and testing new hypotheses in socio-environmental research. SESYNC invites projects that will develop new models and/or modeling methodologies that utilize large and/or multidisciplinary data sources, the integration of which might be computationally-intensive and/or analytically challenging. Quantitative tools and approaches that facilitate the integration of social and biophysical models and data at local, regional, and global scales in a spatially explicit framework are particularly important for investigating multifaceted socio-environmental issues. Such tools and approaches should also provide insights into the structure and dynamics of current SESs, as well as improve capacity to understand and respond to future scenarios. Projects that combine advances in modeling and analytic methods, such as the assimilation of large and/or heterogeneous data to improve model performance, are especially welcome.
Successful candidates will lead strongly data and/or modeling-driven research efforts that synthesize understanding at the interface of the social and environmental sciences. Competitive proposals will:
- bring together social and environmental data in novel ways to address critical socio-environmental research questions that are also actionable or
- attempt to advance modeling and/or analytical techniques beyond current applications, which may be limited to a single scale of analysis, type of data, and/or disciplinary lense.
Below, we provide examples of topics that could be addressed under this theme. These examples are meant only to illustrate the diversity of potential topics related to this call for proposals, rather than the full extent of relevant topics. Data-intensive analysis and/or quantitative modeling projects could involve:
- Integration, organization, and/or visualization of "big data" or highly heterogeneous data to answer socio-environmental research questions;
- Development of spatially-explicit data sets by harmonizing remote sensing products with detailed socio-economic data;
- Novel integration of multi-disciplinary datasets and/or quantitative models for cross-site comparisons;
- Scaling-up of modeling or analytical techniques currently limited to site-based application or small datasets, respectively;
- Adaptation or advancement of high-performance computing methods for socio-environmental applications;
- Capture and analysis of ambient geographic information from geo-tagged social media data to inform analysis and/or modeling of human-environment interactions;
- Assimilation of complex data into simulation models at the design, parameterization, and/or evaluation stages; or
- Development of ‘best practices’ for use of heterogeneous, multi-disciplinary, large-scale, and/or highly detailed data sets.
SESYNC hopes to catalyze collaborations across a broad range of areas. Proposals are welcome from Principal Investigator(s) (PIs) at any career stage—faculty, postdoctoral, or senior graduate students. Project teams might include experts from domains traditionally engaged in social and environmental sciences with quantitative and/or qualitative skills.
Proposals will be evaluated bi-annually. The inaugural deadline is January 31, 2014, at 5 p.m. (EST), and every six months thereafter.
All funding decisions will be based on external peer review by an international panel.
Questions regarding the content or scope of possible projects should be directed to Dr. Nicholas Magliocca at firstname.lastname@example.org.
Proposals should include and will be ranked based on:
- novelty, creativity, and/or urgency of socio-environmental research question(s) and/or advancement of data-intensive analysis or modeling;
- clear descriptions of:
- data sources: accessibility, structure, and storage requirements,
- analysis: methodology, assumptions, and data and software requirements, and
- models: theoretical foundations, purpose, and structure;
- feasibility of producing meaningful synthetic research, including identifying and showing ability to access appropriate data;
- potential to translate findings into actionable solutions;
- qualifications, appropriate diversity of scientific backgrounds, and experience of the proposed participants;
- inclusion of diversity to broaden the participation of underrepresented groups with respect to gender, ethnicity, disability and geographic location; and
- explanation of why SESYNC is the most appropriate way to support the activity.
What to Include
Applications are composed of two parts to be submitted via SESYNC's online submission system: 1) an online cover sheet submitted via webform and 2) a single PDF file containing the major components of your application. These two parts are described below:
Online cover sheet (Do not include in application document)
- Descriptive title or proposed project type (e.g., "Pursuit...")
- Short title (25 characters max)
- Name and contact information for up to two PIs
- Project summary (250 words) - appropriate for the public; posted on the SESYNC web site
- Keywords (up to 5 keywords different from those used in the title)
- Proposed start and end dates; number and duration of meetings as well as the estimated number of participants
- Potential conflicts of interest with members of the SESYNC External Advisory Board, Scientific Review Committee or Leadership
Application PDF (Use single spacing, 12-pt type fonts, and 1-inch margins.
Main body (5 pages max including references)
- Problem statement: Clear and concise statement of how the project will address a novel socio-environmental research question, what technical barriers need to be overcome to perform the research, and how the proposed data synthesis or innovations in data-intensive analysis and/or modeling can lead to the advancement of SES research.
- Conceptual framework: Graphical and/or textual formats should be used to show how the synthesis approach and various components of the work are linked together to address the problem of interest.
- Proposed activities: Description of the synthesis project to be undertaken. Provide the technical specifications of the data sources (and their permissions needed for use), analytical methods, and/or modeling approaches that will be used, as well as the scope of work for any technical support personnel that are requested.
- Suitability for SESYNC: Brief description of why the proposed synthesis activities are appropriate for funding by SESYNC as opposed to another funding program, such as the National Science Foundation's (NSF's) core programs.
- Expected results: Description of new data sets, analytical/modeling tools, and/or insights into SESs resulting from the proposed activities.
- Metrics of success: Descripton of which metrics are the most appropriate for evaluating the success of the proposed project (e.g., papers, policy-directed efforts, databases, models, development of new resources, etc). If successful, who would most likely use the knowledge or tools developed?
- Cyberinfrastructure needs: Brief description of any anticipated needs for cyberinfrastructure support, which could include descriptions of new data sets or software/databases to be developed; high performance computing needs; data aggregation or fusion required; types of visualization; and description of technical support personnel. Applicants should review SESYNC's IT and data sharing policies and are encouraged to contact SESYNC prior to submission to discuss the project's technical requirements relative to SESYNC's expertise, cyberinfrastructure, and personnel.
Potential Participants (1 page)
Complete a table with the following column headers for all participants:
- Last name
- First name
- Affiliation (include department)
- Website address
- Primary area of expertise
- Secondary area of expertise
- Confirmed (Y/N)
- Prior collaboration with applicants (Y/N)
- Diversity statement: Include a paragraph describing the aspects of diversity in your participant list. Diversity is considered in all its aspects, social and scientific, including gender, ethnicity, scientific field, disability status, career stage, geography, and type of home institution.
Additional Information (1 page)
- Complete description of the expected responsibilities and required skills of technical support staff, and whether the project will rely on SESYNC staff or an individual at one of the project team member's home institutions. Applicants are encouraged to contact SESYNC prior to submitting a proposal if they are unsure how their technical support personnel needs will be met.
- Work plan with budgetary needs: This is not in dollars, but do provide: 1) numbers of trips by year to SESYNC (broken down by number of US domestic and international participants and days of local support) and 2) other anticipated support.
Short CVs of the Pursuit Leads (2 pages for each)
Do not include talks, society memberships, or papers in preparation.
The University of Maryland is an Equal Opportunity Employer
Minorities and Women Are Encouraged to Apply