This dataset provides a systematic survey of decision support system (DSS) capabilities across 33 science gateway implementations documented in the peer-reviewed literature. The survey was conducted to establish the current landscape of computational decision support in science gateways and to identify gaps in participatory modeling approaches that informed the development of the Decision Pathways Framework presented in the accompanying journal article.
Purpose: To characterize existing science gateway DSS capabilities and identify opportunities for integrating stakeholder-driven, participatory approaches into gateway-based decision support systems.
Scope: The dataset covers science gateways spanning multiple domains including water resources, carbon capture and storage, neuroscience, geoscience, structural biology, astrophysics, healthcare, nanotechnology, and environmental science. For each gateway, the survey documents: (1) study focus, (2) gateway platform and underlying technologies, (3) target application domain, and (4) specific DSS capabilities addressed.
Methodology: A systematic literature search of the Semantic Scholar corpus retrieved 498 potentially relevant papers using queries focused on science gateways for decision support in participatory computational science. Papers were screened against seven inclusion criteria: science gateways or web-based computational platforms, decision support applications, empirical evidence, participatory or collaborative approaches, collaborative features, real-world application, and high-performance or distributed computing. Thematic analysis extracted structured data on reproducible environment design, participatory science enablement, infrastructure sustainability, and real-time analytics capabilities, resulting in 33 gateways meeting all criteria.
Associated Publication: Pierce, S.A. (2025). A Science Gateway Approach to Decision Support. SN Computer Science.
