Special Issue on Big Data Analytics for Sustainability
• 大类 : 工程技术 - 2区
• 小类 : 计算机：信息系统 - 2区
Uneven economic development, mass consumerism and unreasonable natural or human resource utilization can lead to significant deleterious outcomes, including problems such as pollution, climate change, transportation disorder, social injustice, discrimination, crime, unfair competition, and resource deficiency. Sustainability is a paradigm for deliberating about the future in which environmental, societal and economic considerations are all balanced in the pursuit of our improved existence.
Data-driven analytics has extensively penetrated both academic and practical spheres. By harnessing its power in processing large volumes of information, data analytics techniques help people to discover undiscovered links and make better decisions. Predictive techniques, such as those of machine learning (including artificial intelligence and deep learning), can help to guide us in solving future as well as current problems. Econometric techniques (including difference-in-differences, instrumental variables, matching techniques) allow us to learn causal relationships and their underlying mechanisms in large scale observational data that span across periods of time. However, as yet, insufficient effort has been invested into applying these techniques to the emerging set of problems regarding sustainability.
The focus of this special issue is the application of data analytics to understand better sustainability issues, and to inform stakeholders of possible solutions. Large scale data’s potential impact on alleviating sustainability issues hinges on several aspects. First, interactions between people, resources, ecosystems and climate can be analysed using data gathered from society and the environment. Second, interactions between consumers, companies, suppliers and markets can be optimized for sustainable development. Third, the inter-related impacts that the business world and natural world have on each other also need to be further investigated.
This special issue focuses on high quality, up-to-date technologies and solutions related to data analytics for sustainability. To our knowledge, it is the first special issue of its kind focusing on these converging topics. We aim to serve as a special issue for researchers all over the world to discuss their current work and recent advances in this field. Both theoretical studies and state-of-the-art practical applications are welcomed for submission. All submitted papers will be thoroughly peer-reviewed and selected on the basis of both their quality and their relevance to the theme of this special issue. Papers invited for revision will be invited to present their research at a conference held at King’s College London in June 2019.
The list of possible topics for this special issue includes, but is not limited to:
The impacts of business operations on society and the environment using fine-grained data.
Data analytics for equality, diversity and consumer protection.
Data analytics for improving health outcomes.
Data analytics for environmentally sustainable transportation systems.
Data analytics to achieve conformity to governmental regimes.
The application of data analytics for assessing environmental risks.
Data analytics for information security and resilience.
Data analytics for the circular economy.
The juxtaposition of data analytics in government and sustainability regulation.
Data analytics for smart cities and homes.
Social networks, online sharing and data analytics.
Data analytics for economic growth, employment and income opportunities.
Data analytics for democracy, social justice/inclusion, and crime fighting.
Big data driven approaches to collect and analyze large volumes of information from emerging technologies (e.g., IoT, remote sensors, wireless sensor networks, RFIDs, mobile)