Building science gateways for humanities content poses new challenges to the science gateway community. Compared with science gateways devoted to scientific content, humanities-related projects usually require 1) processing data in various formats, such as text, image, video, etc., 2) constant public access from a broad audience, and therefore 3) reliable security, ideally with low maintenance. Many traditional science gateways are monolithic in design, which makes them easier to write, but they can be computationally inefficient when integrated with numerous scientific packages for data capture and pipeline processing. Since these packages tend to be single-threaded or nonmodular, they can create traffic bottlenecks when processing large numbers of requests. Moreover, these science gateways are usually challenging to resume development on due to long gaps between funding periods and the aging of the integrated scientific packages. In this paper, we study the problem of building science gateways for humanities projects by developing a service-based architecture, and present two such science gateways: the Moving Image Research Collections (MIRC) – a science gateway focusing on image analysis for digital surrogates of historical motion picture film, and SnowVision - a science gateway for studying pottery fragments in southeastern North America. For each science gateway, we present an overview of the background of the projects, and some unique challenges in their design and implementation. These two science gateways are deployed on XSEDE’s Jetstream academic clouding computing resource and are accessed through web interfaces. Apache Airavata middleware is used to manage the interactions between the web interface and the deep-learning-based (DL) backend service running on the Bridges graphics processing unit (GPU) cluster.
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Sifting Through Clutter and Finding Answers that Utter Among COVID-19 Data for Medical Users via Gateways
Science gateways have been a crucial tool that lowers the barriers of computer language proficiency for researchers and scientists alike to implement digital tools to further their research agendas. However, gateways remain somewhat esoteric and difficult to use for many potential users. A chatbot has been proposed as a solution to aid gateway users and for the improvement of gateway usability. Via in-depth interviews with 10 medical professionals, we investigated the challenges they faced when extracting data, namely, slow speed, limited scope, and mixed quality of data. We suggest future gateway developments to address the issues that medical professionals face when searching for publications and data. Findings suggest that gateways could serve practitioners (i.e., clinicians, healthcare providers in this case), beyond the original vision for research and education. Moreover, gateway projects could consider conducting similar market research interviews to better understand the work context (including challenges) faced by the intended users of specific gateways.
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- Award ID(s):
- 2006816
- NSF-PAR ID:
- 10509329
- Publisher / Repository:
- Zenodo
- Date Published:
- Subject(s) / Keyword(s):
- Science Gateways Chatbot In-Depth Interview
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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