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Data Science

A guide to library resources about Data Analytics

Data Science and Resources

  • Data science is an interdisciplinary field that uses scientific methods to extract high-value information or knowledge and insights from available data in various forms, both structured and unstructured (Dhar, 2013; Kalidindi & ).

  (Venn diagram credit: Data Science for Beginners)

  • Data science: A term intended to unify statistics, data analysis and related methods. Consists of three phases, design for data, collection of data and analysis of data (Everitt, 2002).

Note:

Dhar, V. (2013). Data science and prediction. Communications of the ACM, 56 (12), 64–73.

Everitt, B. S. (2002). Data Science. In B. S. Everitt (Ed.), Cambridge Dictionary of Statistics (2nd ed., p. 109). Cambridge University Press.

Kalidindi, S. R. &  Materials data science: current status and future outlook. Annual Review of Materials Research, 45, 171–193.

Computer Information Systems 

Featured Data Sources

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Browse Fulltext Data Science Journals by Title

  • ACM SIGKDD Explorations Newsletter
  • Provides the premier forum for advancement and adoption of the "science" of knowledge discovery and data mining.
  • ACM Transactions on Intelligent Systems and Technology (TIST)
  • Publishes the highest quality papers on intelligent systems, applicable algorithms and technology with a multi-disciplinary perspective.
  • Big Data & Society
  • Publishes interdisciplinary work principally in the social sciences, humanities and computing and their intersections with the arts and natural sciences about the implications of Big Data for societies.
  • Big Data Analytics
  • Multi-disciplinary open-access, peer reviewed journal, which contains cutting-edge articles describing original basic and applied work involving biologically-inspired computational accounts of all aspects of big data science analytics.
  • Data Mining and Knowledge Discovery
  • Publishes original technical papers in both the research and practice of data mining and knowledge discovery, surveys and tutorials of important areas and techniques.
  • Decision Support Systems
  • Publishes articles relevant to theoretical and technical issues in the support of enhanced decision making.
  • EPJ Data Science
  • Focuses on conceptually new scientific methods for analyzing and synthesizing massive data sets, and on fresh ideas to link these insights to theory building and corresponding computer simulations.
  • Expert Systems with Applications
  • Focuses on exchanging information relating to expert and intelligent systems applied in industry, government, and universities worldwide.
  • IEEE Transactions on Knowledge and Data Engineering
  • Informs researchers, developers, managers, strategic planners, users, and others interested in state-of-the-art and state-of-the-practice activities in the knowledge and data engineering area.
  • Intelligent Data Analysis
  • Provides a forum for the examination of issues related to the research & applications of Artificial Intelligence techniques in data analysis across a variety of disciplines.
  • Journal of Big Data
  • Publishes high-quality, scholarly research papers, methodologies and case studies covering a broad range of topics, from big data analytics to data-intensive computing and all applications of big data research.
  • Journal of Data Mining and Digital Humanities
  • Focuses on the intersection of computing and the disciplines of the humanities, with tools provided by computing such as data visualization, information retrieval, statistics, text mining by publishing scholarly work beyond the traditional humanities.
  • Social Network Analysis and Mining
  • Contains experimental and theoretical work on social network analysis and mining.
  • ACM Transactions on Knowledge Discovery from Data (TKDD)
  • Publishes full range of research in the knowledge discovery and analysis of diverse forms of data.

Bookshelf

Data Science for Fundraising: Build Data-Driven Solutions Using R