Cyberinfrastructure for sustainability sciences
Bibliographic Data
| ID | 15548631 |
|---|---|
| Authors | Carol Song (0000-0003-0123-9067, Purdue University West Lafayette, corresponding author), Venkatesh Merwade (0000-0001-5518-2890, Purdue University West Lafayette), Shaowen Wang (0000-0001-5848-590X, University of Illinois Urbana-Champaign), Michael Witt (0000-0003-3417-0561, Purdue University West Lafayette), Vipin Kumar (0009-0003-1021-2170, University of Minnesota), Elena G Irwin (0000-0001-7908-5964, The Ohio State University), Elena Irwin, Lan Zhao (0000-0002-0418-0323), Amy L Walton (U.S. National Science Foundation), Amy Walton |
| Year | 2023 |
| Volume | 18 |
| Issue | 7 |
| Pages | 075002-075002 |
| Publication date | 2023-05-30 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Environmental Research Letters (JOURNAL) |
| Journal identifiers | ISSN: 1748-9326 • E-ISSN: 1748-9326 |
| Publisher | IOP Publishing (PUBLISHER • GB) |
| DOI | 10.1088/1748-9326/acd9dd |
| OpenAlex | W4378741358 |
| Language | EN |
| Citations received | 3 |
| References cited | 44 |
Meeting the United Nation’ Sustainable Development Goals (SDGs) calls for an integrative scientific approach, combining expertise, data, models and tools across many disciplines towards addressing sustainability challenges at various spatial and temporal scales. This holistic approach, while necessary, exacerbates the big data and computational challenges already faced by researchers. Many challenges in sustainability research can be tackled by harnessing the power of advanced cyberinfrastructure (CI). The objective of this paper is to highlight the key components and technologies of CI necessary for meeting the data and computational needs of the SDG research community. An overview of the CI ecosystem in the United States is provided with a specific focus on the investments made by academic institutions, government agencies and industry at national, regional, and local levels. Despite these investments, this paper identifies barriers to the adoption of CI in sustainability research that include, but are not limited to access to support structures; recruitment, retention and nurturing of an agile workforce; and lack of local infrastructure. Relevant CI components such as data, software, computational resources, and human-centered advances are discussed to explore how to resolve the barriers. The paper highlights multiple challenges in pursuing SDGs based on the outcomes of several expert meetings. These include multi-scale integration of data and domain-specific models, availability and usability of data, uncertainty quantification, mismatch between spatiotemporal scales at which decisions are made and the information generated from scientific analysis, and scientific reproducibility. We discuss ongoing and future research for bridging CI and SDGs to address these challenges
Big data · Cyberinfrastructure · Data mining · Data science · Knowledge management · Management science · Operationalization · Sustainability · Sustainability organizations · Sustainability science · Computer Science · Engineering · Environmental Monitoring and Data Management · Geographic Information Systems Studies · Scientific Computing and Data Management
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The Care Principles for Indigenous Data Governance
The Fair Guiding Principles for scientific data management and stewardship
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Assessing 'Neighborhood Effects
| Unique citing works | 3 |
|---|---|
| Citations per year | 1 |
| Citation span | 2023 - 2025 (3) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 3 |