食品安全知识交流(FSKX)形式:基于 SWOT 分析的现状和战略发展计划

IF 3 4区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES
Matthias Filter, Thomas Schüler, Racem Ben Romdhane
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引用次数: 0

摘要

食品安全知识交换(FSKX)格式是一项由社区推动的工作,最初的目的是促进食品安全领域数据和模型的高效交换。在过去几年中,风险评估知识集成平台(RAKIP)计划推动了这项工作,该计划还通过其网站 https://foodrisklabs.bfr.bund.de/rakip-initiative/.This 提供了大量软件工具和符合 FSKX 的模型文件。本文介绍了 SWOT 分析的结果,该分析旨在确定提高 FSKX 可用性和采用率的战略途径。SWOT 分析为 FSKX 的未来发展提出了一系列建议。首先,建议降低注释模式的复杂性,以方便格式的采用。其次,建议明确区分 FSKX 的描述部分和可执行部分。为了促进符合 FSKX 标准的模型的广泛使用,我们还建议开发并提供符合 FSKX 标准的 API 和资源,以方便基于云的执行。作为研究的一部分,在确定未来 FSKX 开发方案的优先级时,我们还考虑了新兴生成式人工智能技术的影响,特别是大型语言模型(LLM)在支持研究界采用 FSKX 方面可能产生的影响。认识到该格式在食品安全领域之外的应用潜力,我们建议将 FSKX 的缩写重新命名为 "FAIR 科学知识交换格式",以更好地反映其在各个科学领域的广泛适用性。我们的研究结果表明,随着 SWOT 分析所确定的改进措施的实施,以及生成式人工智能技术的广泛应用,FSKX 作为一种以 FAIR 方式共享数据和模型的方法将得到广泛采用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Food Safety Knowledge Exchange (FSKX) format: Current status and strategic development plans based on a SWOT analysis

The Food Safety Knowledge Exchange (FSKX) format is a community-driven effort initially created to promote the efficient exchange of data and models in the food safety domain. Over the past years this effort was driven by the Risk Assessment Knowledge Integration Platform (RAKIP) Initiative that also provided a number of software tools and FSKX-compliant model files via their website https://foodrisklabs.bfr.bund.de/rakip-initiative/.

This paper describes the results of a SWOT analysis that was conducted to identify strategic avenues for enhancing FSKX's usability and adoption. The SWOT analysis identified a number of recommendations for the future evolution of FSKX. First, it is recommended to reduce the complexity of the annotation schema to ease the adoption of the format. Second, a clear distinction between the descriptive part of FSKX and the executable part is proposed. To promote the broad usage of FSKX-compliant models, it is also recommended to develop and provide FSKX-compliant APIs and resources that facilitate cloud-based execution.

As part of the research to prioritize future FSKX development options, we also considered the implications of the emerging generative AI technologies, particularly which impact large language models (LLMs) might have in supporting the adoption of FSKX by the research community. Recognizing the format's application potential beyond the food safety domain, we then proposed to re-brand the FSKX acronym as "FAIR Scientific Knowledge Exchange Format" which better reflects its broad applicability in various scientific domains. Our research findings suggest that with the implementation of the improvements identified by the SWOT analysis and the broader availability of generative AI technologies the broad adoption of FSKX as a method to share data and models in a FAIR way comes into reach.

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来源期刊
Microbial Risk Analysis
Microbial Risk Analysis Medicine-Microbiology (medical)
CiteScore
5.70
自引率
7.10%
发文量
28
审稿时长
52 days
期刊介绍: The journal Microbial Risk Analysis accepts articles dealing with the study of risk analysis applied to microbial hazards. Manuscripts should at least cover any of the components of risk assessment (risk characterization, exposure assessment, etc.), risk management and/or risk communication in any microbiology field (clinical, environmental, food, veterinary, etc.). This journal also accepts article dealing with predictive microbiology, quantitative microbial ecology, mathematical modeling, risk studies applied to microbial ecology, quantitative microbiology for epidemiological studies, statistical methods applied to microbiology, and laws and regulatory policies aimed at lessening the risk of microbial hazards. Work focusing on risk studies of viruses, parasites, microbial toxins, antimicrobial resistant organisms, genetically modified organisms (GMOs), and recombinant DNA products are also acceptable.
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