Harnessing Big Data in the Animal Welfare Industry: Utilizing Data Science to Improve Regulatory Oversight of Commercial Dog Breeding

Clinton Ross Mauck, Jyothi Vinnakota Robertson, Marjorie Robin Vincent
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Abstract

Introduction: In the age of Big Data, the animal welfare industry stands to benefit from data-driven decision making, particularly in commercial dog breeding. Despite its potential, many organizations and regulatory bodies, such as the United States Department of Agriculture (USDA), face significant challenges in organizing and using it effectively. The existing challenges limit the extent to which the vast amount of data collected by the USDA can be used to improve regulatory oversight and promote animal welfare. This study explored the potential of leveraging publicly-available inspection report data to inform animal welfare standards and identify areas of improvement. Methods: We formulated an innovative approach for extracting, cleaning, and structuring data from the Public Search Tool (PST) database. Our approach involved the use of customized web-scraping tools and data manipulation techniques, including automatic data retrieval, transformation of inspection reports into a text-friendly format, and pattern recognition for collating pertinent data elements. We conducted descriptive statistical analyses on the assembled dataset to set the stage for a comprehensive exploration of inspection reports from Class ‘A’ commercial dog breeding facilities. Results: Our study produced an extensive dataset detailing compliance with animal welfare standards at Class ‘A’ commercial dog breeding facilities across the United States from 2014 to 2023. Preliminary analysis revealed prevalent areas of non-compliance, such as inadequate veterinary care and substandard housing conditions. The dataset facilitated a deep analysis of animal welfare practices within the commercial dog breeding industry, providing insights across geographical locations and facility sizes. Conclusion: Our study underscores the potential of harnessing Big Data to inform regulatory decisions and improve animal welfare within commercial dog breeding. It introduces a method to transform publicly available data into an accessible format. This allows us to go beyond anecdotal evidence into comprehensive assessments, facilitating constructive dialogue and effective policy-making. Further research leveraging advancements is recommended to deepen insights and encourage collaborative efforts to elevate animal welfare standards.
在动物福利行业利用大数据:利用数据科学改进对商业养犬业的监管
导读:在大数据时代,动物福利行业将从数据驱动的决策中受益,尤其是在商业犬种方面。尽管它具有潜力,但许多组织和管理机构,如美国农业部(USDA),在有效组织和使用它方面面临重大挑战。现有的挑战限制了美国农业部收集的大量数据用于改善监管和促进动物福利的程度。这项研究探讨了利用公开的检查报告数据来提高动物福利标准和确定改进领域的潜力。方法:我们制定了一种创新的方法来从公共搜索工具(PST)数据库中提取、清理和构建数据。我们的方法包括使用定制的网页搜集工具和数据处理技术,包括自动数据检索、将检查报告转换为文本友好格式,以及模式识别以整理相关数据元素。我们对收集到的数据集进行了描述性统计分析,为全面探索“a”级商业犬种设施的检验报告奠定了基础。结果:我们的研究产生了一个广泛的数据集,详细说明了2014年至2023年美国各地“A”级商业狗饲养场对动物福利标准的遵守情况。初步分析揭示了普遍存在的不合规领域,如兽医护理不足和住房条件不合格。该数据集促进了对商业养犬行业动物福利实践的深入分析,提供了跨地理位置和设施规模的见解。结论:我们的研究强调了利用大数据为监管决策提供信息和改善商业犬种动物福利的潜力。它引入了一种将公开可用的数据转换为可访问格式的方法。这使我们能够超越传闻证据,进行全面评估,促进建设性对话和有效决策。建议进一步研究利用现有的进展,以加深对动物福利标准的认识,并鼓励合作努力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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