scholarly journals THE IMPACT OF DATA ON THE ROLE OF DESIGNERS AND THEIR PROCESS

2021 ◽  
Vol 1 ◽  
pp. 3021-3030
Author(s):  
Jiahao Lu ◽  
Alejandra Gomez Ortega ◽  
Milene Gonçalves ◽  
Jacky Bourgeois
Keyword(s):  
Data Science ◽  
Large Data ◽  
The Internet ◽  
Data Sets ◽  
Educational Support ◽  
New Era ◽  
New Material ◽  
The Impact ◽  
The Internet Of Things

AbstractWith the advance of the Internet and the Internet of Things, an abundance of 'big' data becomes available. Data science can be incorporated in design, which brings forward various opportunities for designers to benefit from this new material. However, the designer's perspective and their role remains unclear. How do they think about and approach data? What do they want to achieve with this data? What do they need to take ownership of designing with data? In this paper we take a design perspective to map the opportunities and challenges of leveraging large data-sets as part of the design process. We rely on a survey with 75 participants across a Faculty of Industrial Design Engineering and in-depth reflective interviews with a subset of 9 participants. We discuss the impact of data on the roles designers can adopt as well as an approach to designing with data. This work aims to inform on educational support, data literacy and tools needed for designers to take advantage of this new era of design digitalisation.

scholarly journals Data Science Methods for Psychology

Psychology ◽  
2020 ◽  
Author(s):  
Jeffrey Stanton
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Data Analysis ◽  
Data Collection ◽  
Data Science ◽  
Large Data ◽  
Large Data Sets ◽  
Predictive Analysis ◽  
Data Sets ◽  
The Impact

The term “data science” refers to an emerging field of research and practice that focuses on obtaining, processing, visualizing, analyzing, preserving, and re-using large collections of information. A related term, “big data,” has been used to refer to one of the important challenges faced by data scientists in many applied environments: the need to analyze large data sources, in certain cases using high-speed, real-time data analysis techniques. Data science encompasses much more than big data, however, as a result of many advancements in cognate fields such as computer science and statistics. Data science has also benefited from the widespread availability of inexpensive computing hardware—a development that has enabled “cloud-based” services for the storage and analysis of large data sets. The techniques and tools of data science have broad applicability in the sciences. Within the field of psychology, data science offers new opportunities for data collection and data analysis that have begun to streamline and augment efforts to investigate the brain and behavior. The tools of data science also enable new areas of research, such as computational neuroscience. As an example of the impact of data science, psychologists frequently use predictive analysis as an investigative tool to probe the relationships between a set of independent variables and one or more dependent variables. While predictive analysis has traditionally been accomplished with techniques such as multiple regression, recent developments in the area of machine learning have put new predictive tools in the hands of psychologists. These machine learning tools relax distributional assumptions and facilitate exploration of non-linear relationships among variables. These tools also enable the analysis of large data sets by opening options for parallel processing. In this article, a range of relevant areas from data science is reviewed for applicability to key research problems in psychology including large-scale data collection, exploratory data analysis, confirmatory data analysis, and visualization. This bibliography covers data mining, machine learning, deep learning, natural language processing, Bayesian data analysis, visualization, crowdsourcing, web scraping, open source software, application programming interfaces, and research resources such as journals and textbooks.

Afterword

2021 ◽  
pp. 263-284
Author(s):  
Oscar H. Gandy Jr.
Keyword(s):  
Artificial Intelligence ◽  
Consumer Surplus ◽  
Turn Of The Century ◽  
The Internet ◽  
Technological Systems ◽  
Democratic Systems ◽  
The Impact ◽  
Flow Of Information ◽  
The Internet Of Things

The afterword provides a detailed description of developments in the area of privacy and surveillance after the turn of the century and of the rapid developments in information technology and the monopoly firms like Google, Facebook, Apple, and Amazon, which have come to dominate the flow of information and the appropriation of consumer surplus. Its focus on technological systems includes the expanded internet, with special emphasis on the Internet of Things and the impact of the connections between humans, sensors, and machines. Special attention is paid to transformations in the nature of capitalism, reflected in assessments made by Shoshana Zuboff with regard to its focus on surveillance, and David Lyon and Bernard Harcourt with regard to the role of social media and the exhibitionist culture that it helped to develop. The risks to democratic systems associated with developments in computation and analysis, accelerated through advances in artificial intelligence and machine learning, are described in the context of transformations in governance likely to accompany the emergence of an algorithmic Leviathan. At this point, an assessment of Jacques Ellul’s predictions about the future of our democratic systems is provided once again.

Internet of Things as Engine of Economic Growth in Indonesia

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Bambang Widagdo ◽  
Mochamad Rofik
Keyword(s):  
Economic Growth ◽  
Internet Of Things ◽  
Industrial Revolution ◽  
The Internet ◽  
Economic Diversification ◽  
Great Opportunity ◽  
Economic Basis ◽  
Network Quality ◽  
The Internet Of Things

The economic diversification concept gives hope for a country with rich natural resources to strengthen its economic basis. Thus industrial revolution era of 4.0 provides great opportunity to fasten the process. A study by McKensey in 2011 proved that the internet in the developing country contributes around 3.4% towards its GDP which means that the internet has become a new hope for the economy in the future. Indonesia is one of the countries that is attempting to maximize the role of the Internet of Things (IoT) for its economic growth.� The attempt has made the retail and tourism industries as the two main sectors to experience the significant effect of IoT. In the process of optimizing the IoT to support the economic growth, Indonesia faces several issues especially in the term of the internet network quality and its distribution, the inclusive access of financial access and the infrastructure

Participant recruitment and data collection through Facebook: the role of personality factors

2017 ◽  
Author(s):  
Sean Chandler Rife ◽  
Kelly L. Cate ◽  
Michal Kosinski ◽  
David Stillwell
Keyword(s):  
Data Collection ◽  
Social Research ◽  
Personality Factors ◽  
The Internet ◽  
Data Sets ◽  
Social Networking Service ◽  
Participant Recruitment ◽  
Conducting Research ◽  
Promising Avenue

As participant recruitment and data collection over the Internet have become more common, numerous observers have expressed concern regarding the validity of research conducted in this fashion. One growing method of conducting research over the Internet involves recruiting participants and administering questionnaires over Facebook, the world’s largest social networking service. If Facebook is to be considered a viable platform for social research, it is necessary to demonstrate that Facebook users are sufficiently heterogeneous and that research conducted through Facebook is likely to produce results that can be generalized to a larger population. The present study examines these questions by comparing demographic and personality data collected over Facebook with data collected through a standalone website, and data collected from college undergraduates at two universities. Results indicate that statistically significant differences exist between Facebook data and the comparison data-sets, but since 80% of analyses exhibited partial η2 < .05, such differences are small or practically nonsignificant in magnitude. We conclude that Facebook is a viable research platform, and that recruiting Facebook users for research purposes is a promising avenue that offers numerous advantages over traditional samples.

The Role of the Internet of Things in Health Care: A Systematic and Comprehensive Study

2020 ◽  
Author(s):  
Navod Neranjan Thilakarathne ◽  
Mohan Krishna Kagita ◽  
Thippa Reddy Gadekallu
Keyword(s):  
Health Care ◽  
Internet Of Things ◽  
The Internet ◽  
The Internet Of Things ◽  
Comprehensive Study

The Future of Human Workers

2018 ◽  
Author(s):  
Mahesh K. Joshi ◽  
J.R. Klein
Keyword(s):  
Artificial Intelligence ◽  
New Technologies ◽  
Mental Capacity ◽  
Machine Intelligence ◽  
The Internet ◽  
Traditional Model ◽  
Global Workforce ◽  
Repetitive Tasks ◽  
The Internet Of Things

New technologies like artificial intelligence, robotics, machine intelligence, and the Internet of Things are seeing repetitive tasks move away from humans to machines. Humans cannot become machines, but machines can become more human-like. The traditional model of educating workers for the workforce is fast becoming irrelevant. There is a massive need for the retooling of human workers. Humans need to be trained to remain focused in a society which is constantly getting bombarded with information. The two basic elements of physical and mental capacity are slowly being taken over by machines and artificial intelligence. This changes the fundamental role of the global workforce.

scholarly journals Tangibly understanding intangible complexities: Designing for distributed autonomous organizations

2019 ◽  
Vol 6 (1) ◽  
pp. 47-63 ◽  
Author(s):  
Bettina Nissen ◽  
Ella Tallyn ◽  
Kate Symons
Keyword(s):  
Distributed Systems ◽  
Interaction Design ◽  
Digital Technologies ◽  
Interactive Systems ◽  
Collaborative Practice ◽  
The Internet ◽  
The Face ◽  
Future Technologies ◽  
The Internet Of Things

Abstract New digital technologies such as Blockchain and smart contracting are rapidly changing the face of value exchange, and present new opportunities and challenges for designers. Designers and data specialists are at the forefront of exploring new ways of exchanging value, using Blockchain, cryptocurrencies, smart contracting and the direct exchanges between things made possible by the Internet of Things (Tallyn et al. 2018; Pschetz et al. 2019). For researchers and designers in areas of Human Computer Interaction (HCI) and Interaction Design to better understand and explore the implications of these emerging and future technologies as Distributed Autonomous Organisations (DAOs) we delivered a workshop at the ACM conference Designing Interactive Systems (DIS) in Edinburgh in 2017 (Nissen et al. 2017). The workshop aimed to use the lens of DAOs to introduce the principle that products and services may soon be owned and managed collectively and not by one person or authority, thus challenging traditional concepts of ownership and power. This workshop builds on established HCI research exploring the role of technology in financial interactions and designing for the rapidly changing world of technology and value exchange (Kaye et al. 2014; Malmborg et al. 2015; Millen et al. 2015; Vines et al. 2014). Beyond this, the HCI community has started to explore these technologies beyond issues of finance, money and collaborative practice, focusing on the implications of these emerging but rapidly ascending distributed systems in more applied contexts (Elsden et al. 2018a). By bringing together designers and researchers with different experiences and knowledge of distributed systems, the aim of this workshop was two-fold. First, to further understand, develop and critique these new forms of distributed power and ownership and second, to practically explore how to design interactive products and services that enable, challenge or disrupt existing and emerging models.

Influence and Information Flow in Online Social Networks

2017 ◽  
Vol 9 (4) ◽  
pp. 1-17
Author(s):  
Afrand Agah ◽  
Mehran Asadi
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Large Data ◽  
Marketing Strategies ◽  
Large Data Sets ◽  
Divide And Conquer ◽  
Data Sets ◽  
Divide And Conquer Algorithm ◽  
Flow Of Information

This article introduces a new method to discover the role of influential people in online social networks and presents an algorithm that recognizes influential users to reach a target in the network, in order to provide a strategic advantage for organizations to direct the scope of their digital marketing strategies. Social links among friends play an important role in dictating their behavior in online social networks, these social links determine the flow of information in form of wall posts via shares, likes, re-tweets, mentions, etc., which determines the influence of a node. This article initially identities the correlated nodes in large data sets using customized divide-and-conquer algorithm and then measures the influence of each of these nodes using a linear function. Furthermore, the empirical results show that users who have the highest influence are those whose total number of friends are closer to the total number of friends of each node divided by the total number of nodes in the network.

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