Aims & Scope
The Data Science and Informetrics (DSI) is published quarterly and one of most prospective international journals with multiple disciplines. It covers various aspects of data science and informetrics, such as the trends, scientific foundations, techniques, and applications of data science and informetrics. The journal includes but not limited to research papers, technical reports, subject reviews, short comments and book reviews on relevant aspects of the field. DSI is to provide a platform for data scientists, computer scientists, industry practitioners, and potential users of data science and analytics.
The journal publishes original papers including but not limited to the following fields:
• Theory and mathematical foundations for data science and informetrics.
• Data analytics, knowledge discovery, machine learning, and deep learning, and intelligent processing of various data (including text, image, video, graph and network).
• Big data architecture, infrastructure, computing, matching, indexing, query processing, mapping, search, retrieval, interoperability, exchange, and recommendation.
• Data science applications, intelligent services in scientific, business, governmental, cultural, behavioral, social and economic, health and medical, human, natural and artificial (including online/Web, cloud, IoT, mobile and social media) domains.
• Ethics, quality, privacy, safety and security, trust, and risk on data science and big data.
• The convergence of bibliometrics, scientometrics, webometrics, altmetrics, informetrics and data science.
• Informetric problems using methods from other quantitative fields, such as mathematics, statistics, computer science, network science and data science.
DSI adheres to academic standards, anonymous peer review, highlights the spirit of originality, aligns with its world-class academic counterparts, and strives to become a platform for experts and scholars in the field of data science and informetrics.
Read the For Authors for information on how to submit your article.