Decision-Making Using Big Data Relevant to Sustainable Development Goals (SDGs)

Abstract

Policymakers, practitioners, and researchers around the globe have been acting in a coordinated manner, yet remaining independent, to achieve the seventeen Sustainable Development Goals (SDGs) defined by the United Nations. Remarkably, SDG-centric activities have manifested a huge information silo known as big data. In most cases, a relevant subset of big data is visualized using several two-dimensional plots. These plots are then used to decide a course of action for achieving the relevant SDGs, and the whole process remains rather informal. Consequently, the question of how to make a formal decision using big data-generated two-dimensional plots is a critical one. This article fills this gap by presenting a novel decision-making approach (method and tool). The approach formally makes decisions where the decision-relevant information is two-dimensional plots rather than numerical data. The efficacy of the proposed approach is demonstrated by conducting two case studies relevant to SDG 12 (responsible consumption and production). The first case study confirms whether or not the proposed decision-making approach produces reliable results. In this case study, datasets of wooden and polymeric materials regarding two eco-indicators (CO2 footprint and water usage) are represented using two two-dimensional plots. The plots show that wooden and polymeric materials are indifferent in water usage, whereas wooden materials are better than polymeric materials in terms of CO2 footprint. The proposed decision-making approach correctly captures this fact and correctly ranks the materials. For the other case study, three materials (mild steel, aluminum alloys, and magnesium alloys) are ranked using six criteria (strength, modulus of elasticity, cost, density, CO2 footprint, and water usage) and their relative weights. The datasets relevant to the six criteria are made available using three two-dimensional plots. The plots show the relative positions of mild steel, aluminum alloys, and magnesium alloys. The proposed decision-making approach correctly captures the decision-relevant information of these three plots and correctly ranks the materials. Thus, the outcomes of this article can help those who wish to develop pragmatic decision support systems leveraging the capacity of big data in fulfilling SDGs.

Interoperability-Enhanced Knowledge Management in Law Enforcement: An Integrated Data-Driven Forensic Ontological Approach to Crime Scene Analysis

“…One of the most glaring issues is the existence of information silos, which are isolated pockets of data stored in disparate systems that don't communicate with each other. Various departments or units within a law enforcement agency may use different systems for storing and managing data, often with little or no interoperability [41,44,45]. For instance, the cybercrime unit might have its specialized database for digital evidence, while the homicide department may use another platform for DNA and ballistics data [36,42,43,46].…”

“…The impact of these siloed systems is particularly acute in time-sensitive investigations, where every moment lost can affect the outcome of a case [41,42]. A lack of immediate access to relevant information can delay decision-making, compromise the quality of investigative work, and even jeopardize the safety of law enforcement personnel and public safety [45]. Additionally, these fragmented systems often result in duplicated efforts, as different units may unknowingly work on related aspects of a case without sharing crucial information.…”

“…Additionally, these fragmented systems often result in duplicated efforts, as different units may unknowingly work on related aspects of a case without sharing crucial information. This wastes valuable resources and increases the likelihood of conflicting or contradictory evidence, which could weaken a lawsuit in court [41,44,45].…”

“…The admissibility of evidence in court hinges on the chain of custody and the verification of its authenticity [42]. The current state of fragmented and unprotected systems exacerbates these challenges, reinforcing the need for a robust, centralized, and secure knowledge management system to meet modern law enforcement's demands [41,45,48].…”

Towards Developing Big Data Analytics for Machining Decision-Making

“…Fattahi et al [37] developed BDA capable of computing graphs instead of numerical data that helped make the right decisions ensuring Sustainable Development Goal 12 (responsible consumption and production).…”