Methods for Assessing, Predicting, and Improving Data Veracity: A survey

2020 ◽  
Vol 9 (4) ◽  
pp. 5-30
Author(s):  
Fatmah Assiri
Keyword(s):  
Big Data ◽  
Web Applications ◽  
Smart Cities ◽  
Future Research ◽  
Research Directions ◽  
Future Research Directions ◽  
Software Construction ◽  
Technical Solutions ◽  
The Internet Of Things

Data is an essential part of smart cities, and data can play an important role indecision making processes. Data generated through web applications and devicesutilize the Internet of Things (IoT) and related technologies. Thus, it is also importantto be able to create big data, which has historically been defined as having threekey dimensions: volume, variety, and velocity. However, recently, veracity has beenadded as the fourth dimension. Data veracity relates to the quality of the data. Anypotential issues with the quality of the data must be corrected because low-quality dataleads to poor software construction, and ultimately bad decision making. In this work,we reviewed the existing literature on related technical solutions that address dataveracity based on the domain of its application, including social media, web, and IoTapplications. The challenges or limitations and related gaps in existing work will bediscussed, and future research directions will be proposed to address the critical issuesof data veracity in the era of big data

scholarly journals Moving to the Edge-Cloud-of-Things: Recent Advances and Future Research Directions

Electronics ◽  
2018 ◽  
Vol 7 (11) ◽  
pp. 309 ◽  
Author(s):  
Hind Bangui ◽  
Said Rakrak ◽  
Said Raghay ◽  
Barbora Buhnova
Keyword(s):  
Cloud Computing ◽  
Leading Edge ◽  
Cloud Services ◽  
Future Research ◽  
Research Directions ◽  
Iot Applications ◽  
Future Research Directions ◽  
Iot Devices ◽  
The Internet Of Things

Cloud computing has significantly enhanced the growth of the Internet of Things (IoT) by ensuring and supporting the Quality of Service (QoS) of IoT applications. However, cloud services are still far from IoT devices. Notably, the transmission of IoT data experiences network issues, such as high latency. In this case, the cloud platforms cannot satisfy the IoT applications that require real-time response. Yet, the location of cloud services is one of the challenges encountered in the evolution of the IoT paradigm. Recently, edge cloud computing has been proposed to bring cloud services closer to the IoT end-users, becoming a promising paradigm whose pitfalls and challenges are not yet well understood. This paper aims at presenting the leading-edge computing concerning the movement of services from centralized cloud platforms to decentralized platforms, and examines the issues and challenges introduced by these highly distributed environments, to support engineers and researchers who might benefit from this transition.

scholarly journals Computational Techniques for Eye Movements Analysis towards Supporting Early Diagnosis of Alzheimer’s Disease: A Review

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Jessica Beltrán ◽  
Mireya S. García-Vázquez ◽  
Jenny Benois-Pineau ◽  
Luis Miguel Gutierrez-Robledo ◽  
Jean-François Dartigues
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Eye Movements ◽  
Early Diagnosis ◽  
Future Research ◽  
Computational Techniques ◽  
Research Directions ◽  
Future Research Directions ◽  
Tools And Techniques

An opportune early diagnosis of Alzheimer’s disease (AD) would help to overcome symptoms and improve the quality of life for AD patients. Research studies have identified early manifestations of AD that occur years before the diagnosis. For instance, eye movements of people with AD in different tasks differ from eye movements of control subjects. In this review, we present a summary and evolution of research approaches that use eye tracking technology and computational analysis to measure and compare eye movements under different tasks and experiments. Furthermore, this review is targeted to the feasibility of pioneer work on developing computational tools and techniques to analyze eye movements under naturalistic scenarios. We describe the progress in technology that can enhance the analysis of eye movements everywhere while subjects perform their daily activities and give future research directions to develop tools to support early AD diagnosis through analysis of eye movements.

Centralized, Distributed, and Everything in between

2022 ◽  
Vol 54 (7) ◽  
pp. 1-34
Author(s):  
Sophie Dramé-Maigné ◽  
Maryline Laurent ◽  
Laurent Castillo ◽  
Hervé Ganem
Keyword(s):  
Access Control ◽  
Future Research ◽  
The Internet ◽  
Research Directions ◽  
Security Issues ◽  
Security Properties ◽  
Future Research Directions ◽  
Iot Devices ◽  
The Internet Of Things ◽  
Security Of Iot

The Internet of Things is taking hold in our everyday life. Regrettably, the security of IoT devices is often being overlooked. Among the vast array of security issues plaguing the emerging IoT, we decide to focus on access control, as privacy, trust, and other security properties cannot be achieved without controlled access. This article classifies IoT access control solutions from the literature according to their architecture (e.g., centralized, hierarchical, federated, distributed) and examines the suitability of each one for access control purposes. Our analysis concludes that important properties such as auditability and revocation are missing from many proposals while hierarchical and federated architectures are neglected by the community. Finally, we provide an architecture-based taxonomy and future research directions: a focus on hybrid architectures, usability, flexibility, privacy, and revocation schemes in serverless authorization.

Future Research Directions in E-Tourism Studies

Big Data ◽  
2016 ◽  
pp. 2368-2387
Author(s):  
Hajime Eto
Keyword(s):  
Big Data ◽  
Future Research ◽  
Research Directions ◽  
Scientific Methods ◽  
Tourism Studies ◽  
The Future ◽  
Future Research Directions ◽  
And Behaviors ◽  
Public Voice

As this book has the limited numbers of chapters and pages, many important issues remain unanalyzed. This chapter picks up and roughly discusses some of them for the future analyses in more analytical ways. The focuses are placed on how to apply the data scientific methods to the analyses of public voice, claims and behaviors of tourists, customers and the general publics by using the big data already acquired and stored somewhere.

Big Data Analytics Driven Supply Chain Transformation

2019 ◽  
pp. 106-124 ◽  
Author(s):  
Mondher Feki
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Future Research ◽  
Research Directions ◽  
Digital Platforms ◽  
New Frontier ◽  
Future Research Directions ◽  
Chain Transformation

Big data has emerged as the new frontier in supply chain management; however, few firms know how to embrace big data and capitalize on its value. The non-stop production of massive amounts of data on various digital platforms has prompted academics and practitioners to focus on the data economy. Companies must rethink how to harness big data and take full advantage of its possibilities. Big data analytics can help them in giving valuable insights. This chapter provides an overview of big data analytics use in the supply chain field and underlines its potential role in the supply chain transformation. The results show that big data analytics techniques can be categorized into three types: descriptive, predictive, and prescriptive. These techniques influence supply chain processes and create business value. This study sets out future research directions.

Science for All through Reflective Interactions

2012 ◽  
pp. 102-118 ◽  
Author(s):  
Jennifer J. Neakrase ◽  
H. Prentice Baptiste ◽  
Ashley N. Ryan ◽  
Elsa Q. Villa
Keyword(s):  
Science Classroom ◽  
Future Research ◽  
Online Environment ◽  
Science Content ◽  
Science Concept ◽  
Research Directions ◽  
Online Interactions ◽  
Future Research Directions ◽  
The Individual

One of the goals of science education is to ensure that the discipline of science is accessible to all individuals. By many organizations this has been termed “Science for All,” and those who promote this idea also advocate the connection to science literacy. Teaching science in the online environment has been one way to offer science content to many different individuals, who do not necessarily need to be in the same location. Discourse in the science classroom is framed under situated cognition theory, whereby interactions between individuals are part of the normal culture of the classroom. For science knowledge to be adequately constructed by a student these interactions must be meaningful ones. This is especially important in an online science course where typically learning occurs through interactions between the students and the instructor, the students with one another, and within the individual themselves. As part of these online interactions, good reflective practice includes the different forms of feedback and the quality of this feedback. However, even with quality reflective interactions, there are barriers to science concept construction in an online environment. These barriers are discussed, and future research directions are suggested based on this review.

Computational and Data Mining Perspectives on HIV/AIDS in Big Data Era

2022 ◽  
pp. 1477-1503
Author(s):  
Ali Al Mazari
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Healthcare Sector ◽  
Future Research ◽  
Research Directions ◽  
Scientific Disciplines ◽  
Future Research Directions ◽  
Hiv Aids

HIV/AIDS big data analytics evolved as a potential initiative enabling the connection between three major scientific disciplines: (1) the HIV biology emergence and evolution; (2) the clinical and medical complex problems and practices associated with the infections and diseases; and (3) the computational methods for the mining of HIV/AIDS biological, medical, and clinical big data. This chapter provides a review on the computational and data mining perspectives on HIV/AIDS in big data era. The chapter focuses on the research opportunities in this domain, identifies the challenges facing the development of big data analytics in HIV/AIDS domain, and then highlights the future research directions of big data in the healthcare sector.

On the Road to Ephesus

2015 ◽  
pp. 102-125
Author(s):  
Suzanne Roff-Wexler
Keyword(s):  
Big Data ◽  
Future Research ◽  
Review Of Literature ◽  
Healthcare Organizations ◽  
Research Directions ◽  
The Road ◽  
Future Research Directions ◽  
On The Road ◽  
Definition Of

Following a brief review of literature on big data as well as wisdom, this chapter provides a definition of data-based wisdom in the context of healthcare organizations and their visions. The author addresses barriers and ways to overcome barriers to data-based wisdom. Insights from interviews with leading healthcare professionals add practical meaning to the discussion. Finally, future research directions and questions are suggested, including the role of synchronicity and serendipity in data-based wisdom. In this chapter, developing data-based wisdom systems that flourish Wisdom, Virtue, Intellect, and Knowledge are encouraged.

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