Abstract
To design data curation pipelines within DesignSafe-CI, we gathered requirements and sought regular guidance from a group of experts in different aspects of natural hazards engineering research. Upon achieving understanding of experimental, simulation, hybrid simulation and field reconnaissance research workflows, we created four data models to guide data organization and developed specialized vocabularies as metadata. We then translated the models and metadata to interface design (front-end), and selected the infrastructure resources that would support curation and publication functions (back-end). We used iterative design and testing, including the use of interactive mockups of the GUI, to communicate and elicit feedback from the experts, and mapped real datasets to the mockups to evaluate the fitness of the data models, the clarity of the curation tasks. To address the problem of big data interfaces, we provide data representations that highlight the structure of the datasets and the possibility to browse their components in relation to provenance.
Highlights
To study the characteristics and the impact of natural hazards and develop methods to prevent damages to populations, structures, and the environment, engineers employ diverse research methods including: experiments, simulations, hybrid simulations, and field reconnaissance
In designing the pipelines within the end-to-end data management and analysis platform DesignSafe-CI (DS-CI) (DesignSafe-CI)3, the curation and web development team’s goal was to model how researchers conceive their investigative workflows in order to integrate curation to the data analysis tasks conducted in the CI including data transitions between active study, in-curation, and static lifecycle stages
This paper focuses on the process that we followed to understand natural hazards engineering research and gather community requirements
Summary
To study the characteristics and the impact of natural hazards and develop methods to prevent damages to populations, structures, and the environment, engineers employ diverse research methods including: experiments, simulations, hybrid simulations, and field reconnaissance (field recon). We understand curation pipelines as the front-end graphical user interfaces (GUI) to organize, describe, verify, and publish different natural hazards datasets, and the backend infrastructure that supports these functionalities along with the formation of standardized metadata, and the long-term preservation of the data. Workshops, and regular meetings we learned what the community perceived about and wanted from the curation process All this information became the foundation to create the data models that guide the organization of the datasets, and the metadata to describe them. We conducted interviews during which the researchers narrated their workflows so we could better capture the processes and their relations From this information we derived four data models and specialized vocabularies that are used to design and architect the curation pipelines (Figures 2, 3 and 4).
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