scholarly journals Tracking the New Demand for Justice in the Big Data Ecosystem

2018 ◽  
Vol 4 (1) ◽  
pp. 89-97
Author(s):  
Carmen Vargas Pérez ◽  
Juan Luis Peñaloza Figueroa
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Social Welfare ◽  
Law And Economics ◽  
Point Of View ◽  
Unstructured Data ◽  
New Paradigm ◽  
Huge Amount ◽  
Equity And Efficiency ◽  
Data Ecosystem

Abstract Many studies have focused on the possibilities that organizations have to mine and analyze, through computational analytics, the huge amount of structured and unstructured data that is now available, to determine correlations and thus reveal patterns, trends, and associations to predict human behaviour; and to transform this information into knowledge for companies and governments. That is, just from the point of view of the suppliers of good and services. In this paper we contribute to the Law and Economics literature by showing that the logic of Big Data, the access to the cloud, and the use of Artificial Intelligence are drastically changing the ordinary citizen's way of making decisions in the field of justice; and that this new paradigm in the Demand for Justice will mean improvements in terms of both equity and efficiency, and ultimately an improvement in social welfare.

scholarly journals Tracking the New Demand for Justice in the Big Data Ecosystem

2018 ◽  
Vol 10 (1) ◽  
pp. 90
Author(s):  
Carmen Vargas Pérez ◽  
Juan Luis Peñaloza Figueroa
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Social Welfare ◽  
Law And Economics ◽  
Point Of View ◽  
Unstructured Data ◽  
New Paradigm ◽  
Huge Amount ◽  
Equity And Efficiency ◽  
Data Ecosystem

Many studies have focused on the possibilities that organizations have to mine and analyze, through computational analytics, the huge amount of structured and unstructured data that is now available, to determine correlations and thus reveal patterns, trends, and associations to predict human behaviour; and to transform this information into knowledge for companies and governments. That is, just from the point of view of the suppliers of good and services. In this paper we contribute to the Law and Economics literature by showing that the logic of Big Data, the access to the cloud, and the use of Artificial Intelligence are drastically changing the ordinary citizen's way of making decisions in the field of justice; and that this new paradigm in the Demand for Justice will mean improvements in terms of both equity and efficiency, and ultimately an improvement in social welfare.

scholarly journals Applications of Big Data in the Digital India: Opportunities and Challenges

2016 ◽  
Vol 3 (3) ◽  
Author(s):  
Vinay Kumar ◽  
Arpana Chaturvedi
Keyword(s):  
Big Data ◽  
Social Networking ◽  
Exponential Growth ◽  
Social Networking Sites ◽  
Unstructured Data ◽  
Threat Perception ◽  
Data Repository ◽  
Huge Amount ◽  
Real Challenge ◽  
Area Of Application

<div><p><em>With the advent of Social Networking Sites (SNS), volumes of data are generated daily. Most of these data are multimedia type and unstructured with exponential growth. This exponential growth of variety, volume and complexity of structured and unstructured data leads to the concept of big data. Managing big data and harnessing its benefits is a real challenge. With increase in access to big data repository for various applications, security and access control is another aspect that needs to be considered while managing big data. We have discussed area of application of big data, opportunities it provides and challenges that we face in the managing such huge amount of data for various applications. Issues related to security against different threat perception of big data are also discussed. </em></p></div>

Disrupting Agriculture

2021 ◽  
pp. 771-812
Author(s):  
Omar F. El-Gayar ◽  
Martinson Q. Ofori
Keyword(s):  
Artificial Intelligence ◽  
Systematic Review ◽  
Big Data ◽  
New Paradigm ◽  
Agricultural Industry ◽  
Decision Systems ◽  
Food And Agriculture ◽  
Key Stakeholders ◽  
Smart Agriculture ◽  
Key Aspects

The United Nations (UN) Food and Agriculture (FAO) estimates that farmers will need to produce about 70% more food by 2050. To accommodate the growing demand, the agricultural industry has grown from labor-intensive to smart agriculture, or Agriculture 4.0, which includes farm equipment that are enhanced using autonomous unmanned decision systems (robotics), big data, and artificial intelligence. In this chapter, the authors conduct a systematic review focusing on big data and artificial intelligence in agriculture. To further guide the literature review process and organize the findings, they devise a framework based on extant literature. The framework is aimed to capture key aspects of agricultural processes, supporting supply chain, key stakeholders with a particular emphasis on the potential, drivers, and challenges of big data and artificial intelligence. They discuss how this new paradigm may be shaped differently depending on context, namely developed and developing countries.

DataPro

2021 ◽  
pp. 98-108
Author(s):  
Vala Ali Rohani ◽  
Sedigheh Moghavvemi ◽  
Tiago Pinho ◽  
Paulo Caldas
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Unemployment Rate ◽  
Recommender System ◽  
Social Problems ◽  
National Level ◽  
Point Of View ◽  
Web Based ◽  
Four Dimensions ◽  
Online Portal

Due to the COVID‐19 pandemic, most countries are exposed to unprecedented social problems in the current global situation. According to the official reports, it caused a dramatic increase of 44% in graduates' unemployment rate in Portugal. Moreover, from the human resource point of view, the whole of Europe is expected to face a shortage of 925,000 data professionals by 2025. Given the existing situations, the DataPro aims to propose a national-level reskilling solution in big data to mitigate both social problems of unemployability and the shortage of data professionals in Portugal. DataPro project consists of four dimensions, including an online portal for the hiring companies and unemployed graduates, along with a web-based analytics talent upskilling (ATU) platform empowered by an artificial intelligence recommender system to match the reskilled data professionals and the hiring companies.

scholarly journals Big Data and MapReduce Challenges, Opportunities and Trends

2016 ◽  
Vol 6 (6) ◽  
pp. 2911
Author(s):  
Sachin Arun Thanekar ◽  
K. Subrahmanyam ◽  
A. B. Bagwan
Keyword(s):  
Big Data ◽  
High Velocity ◽  
Structured Data ◽  
Unstructured Data ◽  
Map Reduce ◽  
Huge Amount ◽  
Commodity Hardware ◽  
Survey Paper ◽  
Recent Trends ◽  
Large Clusters

<p>Nowadays we all are surrounded by Big data. The term ‘Big Data’ itself indicates huge volume, high velocity, variety and veracity i.e. uncertainty of data which gave rise to new difficulties and challenges. Big data generated may be structured data, Semi Structured data or unstructured data. For existing database and systems lot of difficulties are there to process, analyze, store and manage such a Big Data.  The Big Data challenges are Protection, Curation, Capture, Analysis, Searching, Visualization, Storage, Transfer and sharing. Map Reduce is a framework using which we can write applications to process huge amount of data, in parallel, on large clusters of commodity hardware in a reliable manner. Lot of efforts have been put by different researchers to make it simple, easy, effective and efficient. In our survey paper we emphasized on the working of Map Reduce, challenges, opportunities and recent trends so that researchers can think on further improvement.</p>

Security Issues and Challenges Related to Big Data

2018 ◽  
pp. 86-101
Author(s):  
Jaimin N. Undavia ◽  
Atul Patel ◽  
Sheenal Patel
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Database Systems ◽  
Heterogeneous Data ◽  
Unstructured Data ◽  
Huge Amount ◽  
Current Time ◽  
Security Issues ◽  
Future Prediction ◽  
Data Term

Availability of huge amount of data has opened up a new area and challenge to analyze these data. Analysis of these data become essential for each organization and these analyses may yield some useful information for their future prospectus. To store, manage and analyze such huge amount of data traditional database systems are not adequate and not capable also, so new data term is introduced – “Big Data”. This term refers to huge amount of data which are used for analytical purpose and future prediction or forecasting. Big Data may consist of combination of structured, semi structured or unstructured data and managing such data is a big challenge in current time. Such heterogeneous data is required to maintained in very secured and specific way. In this chapter, we have tried to identify such challenges and issues and also tried to resolve it with specific tools.

Disrupting Agriculture

2020 ◽  
pp. 174-215 ◽  
Author(s):  
Omar F. El-Gayar ◽  
Martinson Q. Ofori
Keyword(s):  
Artificial Intelligence ◽  
Systematic Review ◽  
Big Data ◽  
New Paradigm ◽  
Agricultural Industry ◽  
Decision Systems ◽  
Food And Agriculture ◽  
Key Stakeholders ◽  
Smart Agriculture ◽  
Key Aspects

The United Nations (UN) Food and Agriculture (FAO) estimates that farmers will need to produce about 70% more food by 2050. To accommodate the growing demand, the agricultural industry has grown from labor-intensive to smart agriculture, or Agriculture 4.0, which includes farm equipment that are enhanced using autonomous unmanned decision systems (robotics), big data, and artificial intelligence. In this chapter, the authors conduct a systematic review focusing on big data and artificial intelligence in agriculture. To further guide the literature review process and organize the findings, they devise a framework based on extant literature. The framework is aimed to capture key aspects of agricultural processes, supporting supply chain, key stakeholders with a particular emphasis on the potential, drivers, and challenges of big data and artificial intelligence. They discuss how this new paradigm may be shaped differently depending on context, namely developed and developing countries.

Big Data

2015 ◽  
Vol 6 (2) ◽  
pp. 1-17 ◽  
Author(s):  
Ashok Kumar Wahi ◽  
Yajulu Medury ◽  
Rajnish Kumar Misra
Keyword(s):  
Big Data ◽  
Unstructured Data ◽  
Data Driven ◽  
Enterprise 2.0 ◽  
Huge Amount ◽  
The World ◽  
Data Driven Decisions ◽  
The Impact

Big data has taken the world by storm. Everyone from every industry is not only talking about the impact of big data but is looking for ways to effectively leverage the power of big data. This challenge has heightened with the huge amount of unstructured data flowing from every direction, bringing along with it the increasing pressure to make data driven decisions rather than the gut-driven decisions. This article sheds light on how big data can be an enabler for smart enterprises if the organization is able to address the challenges posed by big data. Enterprises need to equip themselves with relevant technology, desired skills and a supporting managerial attitude to swim through the challenges of big data. It also highlights the need for all enterprises making the journey from 1.0 stage to Enterprise 2.0 to master the art of Big Data if they have to make the transition successful.

scholarly journals Cooperation of Business Intelligence and Big Data in one Ecosystem

2020 ◽  
Vol 83 ◽  
pp. 01008
Author(s):  
Matej Černý
Keyword(s):  
Big Data ◽  
Data Processing ◽  
Business Intelligence ◽  
Structured Data ◽  
The Other ◽  
Unstructured Data ◽  
Data Types ◽  
Data Ecosystem

This paper is focused on the issue, how the business can analyze all data types (structured and unstructured) in one cooperative environment. With structured data handle Business Intelligence and with unstructured data on the other side Big Data. As a solution to this issue, we have suggested our Business Intelligence and Big Data ecosystem. This model - the ecosystem is based on already proven data processing processes running in Business Intelligence and in Big Data areas. Both processes are integrated into one unit. We have also described their common functioning.

scholarly journals Integration of Cloud Computing, Big Data, Artificial Intelligence, and Internet of Things

2021 ◽  
Vol 16 (1) ◽  
pp. 10-17
Author(s):  
Drissi Saadia
Keyword(s):  
Artificial Intelligence ◽  
Cloud Computing ◽  
Big Data ◽  
Internet Of Things ◽  
Detailed Analysis ◽  
New Paradigm ◽  
Research Papers ◽  
Research Issues ◽  
New Challenges ◽  
Open Issues

Cloud computing, internet of things (IoT), artificial intelligence, and big data are four very different technologies that are already discussed separately. The use of the four technologies is required to be more and more necessary in the present day in order to make them important components in today's world technology. In this paper, the authors center their attention on the integration of cloud, IoT, big data, and artificial intelligence. Several kinds of research papers have surveyed artificial intelligence, cloud, IoT, and big data separately and, more precisely, their main properties, characteristics, underlying technologies, and open issues. However, to the greatest of the authors' knowledge, these works require a detailed analysis of the new paradigm that combines the four technologies, which suggests completely new challenges and research issues. To bridge this gap, this paper presents a survey on the integration of cloud, IoT, artificial intelligence, and big data.

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