Applied Ontologies for Global Health Surveillance and Pandemic Intelligence

Baker, Christopher J. O.; Manir, Mohammad Sadnan Al; Brenas, Jon Haël; Zinszer, Kate; Shaban-Nejad, Arash

doi:10.1101/2020.10.17.20214460

Cited by 4 publications

(5 citation statements)

References 30 publications

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“…SHARE 92 and HYDRA [93][94][95] are specialized query engines to work with SADI registries. They receive user input in the form of SPARQL queries and use the registry as a knowledge base for automated workflow composition, matching the query to thousands of services (Data as a Service (DaaS)/Application as a Service (AaaS)).…”

Section: Share and Hydramentioning

confidence: 99%

Perspectives on automated composition of workflows in the life sciences

et al. 2021

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Scientific data analyses often combine several computational tools in automated pipelines, or workflows. Thousands of such workflows have been used in the life sciences, though their composition has remained a cumbersome manual process due to a lack of standards for annotation, assembly, and implementation. Recent technological advances have returned the long-standing vision of automated workflow composition into focus. This article summarizes a recent Lorentz Center workshop dedicated to automated composition of workflows in the life sciences. We survey previous initiatives to automate the composition process, and discuss the current state of the art and future perspectives. We start by drawing the “big picture” of the scientific workflow development life cycle, before surveying and discussing current methods, technologies and practices for semantic domain modelling, automation in workflow development, and workflow assessment. Finally, we derive a roadmap of individual and community-based actions to work toward the vision of automated workflow development in the forthcoming years. A central outcome of the workshop is a general description of the workflow life cycle in six stages: 1) scientific question or hypothesis, 2) conceptual workflow, 3) abstract workflow, 4) concrete workflow, 5) production workflow, and 6) scientific results. The transitions between stages are facilitated by diverse tools and methods, usually incorporating domain knowledge in some form. Formal semantic domain modelling is hard and often a bottleneck for the application of semantic technologies. However, life science communities have made considerable progress here in recent years and are continuously improving, renewing interest in the application of semantic technologies for workflow exploration, composition and instantiation. Combined with systematic benchmarking with reference data and large-scale deployment of production-stage workflows, such technologies enable a more systematic process of workflow development than we know today. We believe that this can lead to more robust, reusable, and sustainable workflows in the future.

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Section: Share and Hydramentioning

confidence: 99%

Perspectives on automated composition of workflows in the life sciences

et al. 2021

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“…These types of approaches synthesise a workflow by instantiating the missing steps within the provided workflow structure. On the other hand, systems such as AI planning in GIS [39,150] Magallanes [116], SHARE [138] and HYDRA [13,115] and PROPHETS [108] synthesise complete workflows based on abstract specifications. These approaches rely on well-annotated domains that allow them to automatically chain together compatible operations and compose valid workflows.…”

Section: Scientific Workflow Synthesismentioning

confidence: 99%

“…Finally, SHARE [138] and HYDRA [13,115] are specialised query engines used to synthesise and execute workflows over the SADI registries. The engines use SPARQL queries to reason over the registry.…”

Section: Workflow Synthesis In Life Sciencesmentioning

confidence: 99%

“…The presented approaches are often hard to compare as they focus on a different part of the workflow life-cycle [92], as well as different domains. Some systems [34,87] provide assistance while choosing concrete workflow steps, other [46,74] aid in setting up the "abstract" workflows, before they can be implemented, while a few [13,138] automate the whole process omitting the workflow altogether. Similarly, the theoretical approaches (e.g., [15,23,61]), presented in Chapter 3, aim to solve complex and universal synthesis problems, assuming that the required implementations and/or domain annotations are available.…”

Section: Workflow Synthesis In Life Sciencesmentioning

confidence: 99%

“…The experiments are run using bio.tools annotations as of November 25, 2020, EDAM version 1.24, and APE version 2.0.1 13 on an i7-6500U CPU at 2.50GHz and 16GB RAM machine running on Ubuntu 20.04. The runtime behaviour of the workflow exploration algorithm is discussed in detail in Chapter 7.…”

Section: Workflow Exploration Runsmentioning

confidence: 99%

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Synthesis of Scientific Workflows: Theory and Practice of an Instance-Aware Approach

Kasalica¹

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The dissertation introduces a novel scientific workflow synthesis, i.e., automated composition, approach, which relies on an existing temporal (SLTL)-based approach and builds upon it. This chapter provides an overview of the existing program synthesis approaches, and focuses on workflow synthesis as their subset. Unlike the program synthesis approaches, which often have to limit the structure of synthesised programs to provide efficient automated composition approaches, scientific workflow synthesis has, by definition, well-defined and structured composition goals. The scientific workflows can be represented as acyclic directed graphs, and are used as such in practice. This loop-free structure allows for an efficient synthesis, without compromising the workflow structure. The temporal logic (SLTL)-based synthesis approach presented in the chapter, allows for an automated composition of scientific workflows based on an abstract description of the problem. The approach is used as a basis for the contributions presented in the following chapters.

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Changes to Public Health Surveillance Methods Due to the COVID-19 Pandemic: Scoping Review

Clark,

Neumann,

Hopkins

et al. 2024

JMIR Public Health Surveill

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Background Public health surveillance plays a vital role in informing public health decision-making. The onset of the COVID-19 pandemic in early 2020 caused a widespread shift in public health priorities. Global efforts focused on COVID-19 monitoring and contact tracing. Existing public health programs were interrupted due to physical distancing measures and reallocation of resources. The onset of the COVID-19 pandemic intersected with advancements in technologies that have the potential to support public health surveillance efforts. Objective This scoping review aims to explore emergent public health surveillance methods during the early COVID-19 pandemic to characterize the impact of the pandemic on surveillance methods. Methods A scoping search was conducted in multiple databases and by scanning key government and public health organization websites from March 2020 to January 2022. Published papers and gray literature that described the application of new or revised approaches to public health surveillance were included. Papers that discussed the implications of novel public health surveillance approaches from ethical, legal, security, and equity perspectives were also included. The surveillance subject, method, location, and setting were extracted from each paper to identify trends in surveillance practices. Two public health epidemiologists were invited to provide their perspectives as peer reviewers. Results Of the 14,238 unique papers, a total of 241 papers describing novel surveillance methods and changes to surveillance methods are included. Eighty papers were review papers and 161 were single studies. Overall, the literature heavily featured papers detailing surveillance of COVID-19 transmission (n=187). Surveillance of other infectious diseases was also described, including other pathogens (n=12). Other public health topics included vaccines (n=9), mental health (n=11), substance use (n=4), healthy nutrition (n=1), maternal and child health (n=3), antimicrobial resistance (n=2), and misinformation (n=6). The literature was dominated by applications of digital surveillance, for example, by using big data through mobility tracking and infodemiology (n=163). Wastewater surveillance was also heavily represented (n=48). Other papers described adaptations to programs or methods that existed prior to the COVID-19 pandemic (n=9). The scoping search also found 109 papers that discuss the ethical, legal, security, and equity implications of emerging surveillance methods. The peer reviewer public health epidemiologists noted that additional changes likely exist, beyond what has been reported and available for evidence syntheses. Conclusions The COVID-19 pandemic accelerated advancements in surveillance and the adoption of new technologies, especially for digital and wastewater surveillance methods. Given the investments in these systems, further applications for public health surveillance are likely. The literature for surveillance methods was dominated by surveillance of infectious diseases, particularly COVID-19. A substantial amount of literature on the ethical, legal, security, and equity implications of these emerging surveillance methods also points to a need for cautious consideration of potential harm.

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Applied Ontologies for Global Health Surveillance and Pandemic Intelligence

Cited by 4 publications

References 30 publications

Perspectives on automated composition of workflows in the life sciences

Perspectives on automated composition of workflows in the life sciences

Synthesis of Scientific Workflows: Theory and Practice of an Instance-Aware Approach

Changes to Public Health Surveillance Methods Due to the COVID-19 Pandemic: Scoping Review

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