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Query-Based Data Valuation Strategy: An Exploratory View

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Proceedings of International Conference on Data Science and Applications

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 288))

Abstract

In this era of big data, the operational and user-related data is generated in huge scales or dimensions, by user platforms, high-end algorithms and computing devices. This data is an essential ‘asset’ for the organization/individual for diverse analytics. The recent plethora of data raised immense challenges and opportunities to a data-driven organization. Data valuation of potential data objects in a prodigious data/dataset is one such co-occurring and multifaceted task, due to inherent characteristics/features of data objects and lack of a global measure or mechanism to evaluate. A data valuation scheme assists the organizations to rank/outline or weighting the potential data objects for a computational objective. In this paper, we have explored the fundamentals aspects of traditional data valuation approaches to investigate the evolution in existing techniques and implicit aspects. In this process, an automated data-evaluation strategy is proposed. The strategy evaluates the values of data objects based on the assessment of user queries and ranked attributes of a target database. The key contribution of the work is its capability to evaluate the data value a desired granularity level, e.g. attribute level, tuple level, record level, etc., on just-in-time basis for the buyer/consumer. Each data objects will is assigned with rank values and could be adapted by several consumer/buyer. The paper also asserts the design challenges and issues for the development of the similar approaches in the future.

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Authors and Affiliations

  1. Computer Engineering Department, National Institute of Technology, Kurukshetra, Haryana, 136119, India

    Neha Verma & Vikram Singh

Authors
  1. Neha Verma
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  2. Vikram Singh
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Corresponding author

Correspondence to Vikram Singh .

Editor information

Editors and Affiliations

  1. Computer Science and Engineering and Information Technology, Jaypee Institute of Information Technology, Noida, Uttar Pradesh, India

    Mukesh Saraswat

  2. Department of Computer Science and Engineering, Jadavpur University, Kolkata, West Bengal, India

    Sarbani Roy

  3. Department of Computer Science and Engineering, Jadavpur University, Kolkata, West Bengal, India

    Chandreyee Chowdhury

  4. Faculty of Engineering and Information Technology, University of Technology Sydney, Ultimo, NSW, Australia

    Amir H. Gandomi

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Verma, N., Singh, V. (2022). Query-Based Data Valuation Strategy: An Exploratory View. In: Saraswat, M., Roy, S., Chowdhury, C., Gandomi, A.H. (eds) Proceedings of International Conference on Data Science and Applications . Lecture Notes in Networks and Systems, vol 288. Springer, Singapore. https://doi.org/10.1007/978-981-16-5120-5_52

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