This paper provides a historical perspective of computing technology along with its evolutionary phases. It is a scientific endeavour to understand and further investigate the significant role played by human which leads to the development of innovative technologies. A comprehensive study of invention from personal to cooperative and then to social computing has been done and its impacts have been highlighted. This paper focuses on two aspects explicitly. The first part renders how cultural computing evolved as a technological paradigm. The second part explicates the interaction of culture and technology through dynamics of mind, to define cultural computing.

This paper attempts to give an insight into emerging ethical issues due to the increased usage of the Internet in our lives. We discuss three main theoretical approaches relating to the ethics involved in the information technology (IT) era: first, the use of IT as a tool; second, the use of social constructivist methods; and third, the approach of phenomenologists. Certain aspects of ethics and IT have been discussed based on a phenomenological approach and moral development. Further, ethical issues related to social networking sites are discussed. A plausible way to make the virtual world ethically responsive is collective responsibility which proposes that society has the power to influence but not control behavior in the virtual world.

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Cultural data and information on the web are continuously increasing, evolving, and reshaping in the form of big data due to globalization, digitization, and its vast exploration, with common people realizing the importance of ancient values. Therefore, before it becomes unwieldy and too complex to manage, its integration in the form of big data repositories is essential. This article analyzes the complexity of the growing cultural data and presents a Cultural Big Data Repository as an efficient way to store and retrieve cultural big data. The repository is highly scalable and provides integrated high-performance methods for big data analytics in cultural heritage. Experimental results demonstrate that the proposed repository outperforms in terms of space as well as storage and retrieval time of Cultural Big Data.