scholarly journals Data Science for Service Design: An exploration of methods

2020 ◽  
Author(s):  
Youetta Kunneman ◽  
◽  
Mauricy Alves da Motta Filho
Keyword(s):  
Data Science ◽  
Service Design

scholarly journals Design for data ethics: using service design approaches to operationalize ethical principles on four projects

2018 ◽  
Vol 376 (2128) ◽  
pp. 20170353 ◽  
Author(s):  
Cat Drew
Keyword(s):  
Data Science ◽  
Service Design ◽  
Initial Development ◽  
Social Good ◽  
Ethics Framework ◽  
Ethical Frameworks ◽  
Data Ethics ◽  
Use Of Data ◽  
Government Data ◽  
Guidance Needs

Ethical frameworks provide helpful guidance about what you should—and should not—do in relation to data projects. But they do not provide definitive yes/no answers about what an ethical data project is or is not. Indeed, research (Ipsos-MORI 2015 Public dialogue into the ethics of data science in government) conducted for the initial development of the Government's Data Ethics Framework shows that the public does not hold any clear red lines; rather, they make nuanced assessments based on a number of variables, including public good and privacy. Ethical frameworks provide a list of these variables to consider in shaping the form of the work. Some are now starting to provide more practical tools and guidance to reshape data projects and push it along those variables into a more ethical space. Alongside technical tools, service design approaches can help enhance the degree to which a data project is ethical, and provides a toolkit for data scientists, analysts and policymakers to take projects from ‘what should we do’ to ‘how can we do it’. This paper sets out the emergence of data science ethical frameworks within the context of the use of data for social good, and—with the recent release of the updated UK Government Data Ethics Framework—shows the recognition more practical guidance needs to be provided. The author then argues that service design approaches provide a helpful ‘wrap around’ for data projects, and draws on experience in using service design tools on four projects, as well as wider examples. This article is part of a discussion meeting issue ‘The growing ubiquity of algorithms in society: implications, impacts and innovations’.

Model-Based Clustering and Classification for Data Science

2019 ◽  
Author(s):  
Charles Bouveyron ◽  
Gilles Celeux ◽  
T. Brendan Murphy ◽  
Adrian E. Raftery
Keyword(s):  
Data Science ◽  
Model Based Clustering ◽  
Model Based ◽  
Clustering And Classification

Social Design for Services Framework

2018 ◽  
Vol 1 (1) ◽  
Author(s):  
Melanie SARANTOU ◽  
Satu MIETTINEN
Keyword(s):  
South Africa ◽  
Sustainable Development ◽  
Research Group ◽  
Design Research ◽  
Service Design ◽  
Social Design ◽  
Practical Action ◽  
The Social ◽  
The World

This paper addresses the fields of social and service design in development contexts, practice-based and constructive design research. A framework for social design for services will be explored through the survey of existing literature, specifically by drawing on eight doctoral theses that were produced by the World Design research group. The work of World Design researcher-designers was guided by a strong ethos of social and service design for development in marginalised communities. The paper also draws on a case study in Namibia and South Africa titled ‘My Dream World’. This case study presents a good example of how the social design for services framework functions in practice during experimentation and research in the field. The social design for services framework transfers the World Design group’s research results into practical action, providing a tool for the facilitation of design and research processes for sustainable development in marginal contexts.

A Study on Service Improvement of Department Store Using Service Design Methodologies

2015 ◽  
Vol 16 (1) ◽  
pp. 225-243 ◽  
Author(s):  
Lee, Kyung Sun ◽  
최정일 ◽  
김서영 ◽  
Youn Sung Kim
Keyword(s):  
Service Design ◽  
Department Store ◽  
Service Improvement ◽  
Design Methodologies

Issues in security and privacy of big data

2018 ◽  
Vol 7 (12) ◽  
pp. 1
Author(s):  
Shaveta Bhatia
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Approximate Method ◽  
Biomedical Research ◽  
Cyber Security ◽  
Data Science ◽  
Third Party ◽  
Security And Privacy ◽  
Security Threats ◽  
The Third

 The epoch of the big data presents many opportunities for the development in the range of data science, biomedical research cyber security, and cloud computing. Nowadays the big data gained popularity.  It also invites many provocations and upshot in the security and privacy of the big data. There are various type of threats, attacks such as leakage of data, the third party tries to access, viruses and vulnerability that stand against the security of the big data. This paper will discuss about the security threats and their approximate method in the field of biomedical research, cyber security and cloud computing.

Use of data science in the renewable energy resources

2017 ◽  
Author(s):  
Predrag Stolić ◽  
◽  
Danijela Milošević ◽  
Zoran Stević ◽  
◽  
...  
Keyword(s):  
Renewable Energy ◽  
Data Science ◽  
Energy Resources ◽  
Renewable Energy Resources ◽  
Use Of Data

About digital transformation of the transport industry in Russia

2020 ◽  
Vol 19 (3) ◽  
pp. 95-105
Author(s):  
Natalia V. Vysotskaya ◽  
T. V. Kyrbatskaya
Keyword(s):  
Artificial Intelligence ◽  
Business Model ◽  
Data Science ◽  
Digital Transformation ◽  
Digital Culture ◽  
Blockchain Technology ◽  
Community Approach ◽  
Non Linear ◽  
Transport Industry ◽  
Artificial Intelligence Systems

The article is devoted to the consideration of the main directions of digital transformation of the transport industry in Russia. It is proposed in the process of digital transformation to integrate the community approach into the company's business model using blockchain technology and methods and results of data science; complement the new digital culture with a digital team and new communities that help management solve business problems; focus the attention of the company's management on its employees and develop those competencies in them that robots and artificial intelligence systems cannot implement: develop algorithmic, computable and non-linear thinking in all employees of the company.

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