Toward Sustainable Data Practices: Integrating Open Data With SDG-Based Data Lake Frameworks

IF 2.1 4区 工程技术 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC
Apurva Kulkarni;Chandrashekar Ramanathan;Vinu E. Venugopal
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引用次数: 0

Abstract

Achieving sustainable development goals (SDGs) necessitates the adoption of sustainable policies, which entails a crucial task of policy formulation. Policymakers must consider multiple factors, such as the present development status, which can be assessed using diverse data points, as well as the policy’s impact and an action plan outlining its implementation [1] . These data points typically originate from various sources, primarily governmental bodies encompassing statistics, budgets, legislation, public services, and geospatial data (maps, satellite imagery), along with domain users comprising individuals, organizations, and governments [2] . The SDGs are intricately crafted, taking into account a multitude of factors and pinpointing key indicators that influence these factors. These factors typically span across diverse data points sourced from various sectors. For instance, in assessing the student dropout rate, it is imperative to consider factors such as the availability of transportation facilities, basic hygiene amenities, access to drinking water, and the effectiveness of government-organized schemes in utilization and impact. Employing an open data framework coupled with advanced artificial intelligence (AI) models has the potential to facilitate in-depth exploration and analysis, providing valuable insights into the complex interplay of these factors and contributing to a more comprehensive understanding of SDG-related challenges and opportunities.
实现可持续数据实践:将开放数据与基于可持续发展目标的数据湖框架相结合
要实现可持续发展目标(SDGs),就必须采取可持续政策,这就要求制定政策这一关键任务。政策制定者必须考虑多种因素,如目前的发展状况(可通过不同的数据点进行评估)、政策的影响以及概述政策实施的行动计划[1]。这些数据点通常来自不同来源,主要是政府机构,包括统计数据、预算、立法、公共服务和地理空间数据(地图、卫星图像),以及由个人、组织和政府组成的领域用户[2]。可持续发展目标的制定错综复杂,考虑了多种因素,并精确定位了影响这些因素的关键指标。这些因素通常涉及来自不同部门的各种数据点。例如,在评估学生辍学率时,必须考虑交通设施的可用性、基本卫生设施、饮用水的获取以及政府组织的计划在利用和影响方面的有效性等因素。采用开放数据框架和先进的人工智能(AI)模型有可能促进深入探索和分析,为了解这些因素的复杂相互作用提供有价值的见解,并有助于更全面地了解与可持续发展目标相关的挑战和机遇。
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来源期刊
IEEE Technology and Society Magazine
IEEE Technology and Society Magazine 工程技术-工程:电子与电气
CiteScore
3.00
自引率
13.60%
发文量
72
审稿时长
>12 weeks
期刊介绍: IEEE Technology and Society Magazine invites feature articles (refereed), special articles, and commentaries on topics within the scope of the IEEE Society on Social Implications of Technology, in the broad areas of social implications of electrotechnology, history of electrotechnology, and engineering ethics.
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