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Data Analysis and Knowledge Discovery  2021, Vol. 5 Issue (1): 16-35    DOI: 10.11925/infotech.2096-3467.2020.1088
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Understanding Serendipity in Science: A Survey
Yu Shuo1,Hayat Dino Bedru1,Chu Xinbei1,Yuan Yuyuan1,Wan Liangtian1,Xia Feng2()
1School of Software, Dalian University of Technology, Dalian 116620, China
2School of Engineering, IT and Physical Sciences, Federation University Australia, Ballarat, VIC 3353, Australia
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Abstract  

[Objective] This paper summarizes the components and definitions of serendipity, reviews representative supporting technologies and applications of serendipity in science, and discusses challenges and future directions in this field. [Coverage] We searched relevant keywords such as “serendipity”, “novelty” and “diversity” in research repositories such as Microsoft Academic and Google Scholar. A total of 102 well-selected references are finally cited. [Methods] We reviewed serendipitous discoveries in various scenarios, and discussed the concept of serendipity in the context of science. Relevant tools and applications are categorized. [Results] The tools that support serendipity are conducive to scientific research. However, there is no uniform definition of serendipity, thus making it difficult to measure serendipity in science. [Limitations] The factors affecting serendipity in science are complex, and yet to be explored. [Conclusions] Serendipity is one of the indispensable factors for scientific advances. However, many challenges are facing the exploration of serendipity in science, such as lack of metrics and difficulty to control.

Key wordsSerendipity in science      Interdisciplinarity      Unexpectedness      Recommender system     
Received: 04 October 2020      Published: 15 December 2020
ZTFLH:  TP393  
Corresponding Authors: Xia Feng     E-mail: f.xia@ieee.org

Cite this article:

Yu Shuo,Hayat Dino Bedru,Chu Xinbei,Yuan Yuyuan,Wan Liangtian,Xia Feng. Understanding Serendipity in Science: A Survey. Data Analysis and Knowledge Discovery, 2021, 5(1): 16-35.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2020.1088     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2021/V5/I1/16

ArticlesDefinition of serendipityFactors
Chakraborti et al. [36]
Wen et al. [37]
McCay-Peet et al. [38]
Maccatrozzo et al. [12]

Kaminskas et al. [39]


Moral et al. [40]

Koesten et al. [41]


Fink et al. [5]
Wang et al. [42]
Copeland [43]

Yaqub [44]
The accidental discovery of something that, post hoc, turns out to be valuable”.
The happy convergence of the mind with conditions”.
The unique and contingent mix of insight coupled with chance”.
a new connection is made that involves a mix of unexpectedness and insight and has the potential to lead to a valuable outcome”.
1) The finding of unexpected information (relevant to the goal or not) while engaged in any information activity; 2) the making of an intellectual leap of understanding with that information to arrive at an insight”.
A method for achieving breadth and identifying information or sources from unknown or partially unknown directions”.
The action of, or aptitude for, encountering relevant information by accident”.
The interactive outcome of unique and contingent “mixes” of insight coupled with chance”.
Falling somewhere between accidental and sagacity,
serendipity is synonymous with neither one nor the other”.
an emergent property of scientific discoveries, describing an oblique relationship between the outcome of a discovery process and the intentions that drove it forward”.
Serendipity may depend on the attributes of the observer and her situation (such as her perceptiveness, instruments and observation systems), or it may depend on the characteristics of the field of inquiry itself (such as when the growth of theory becomes conspicuous for discovery)”.
Chance and positivity
Positivity and mental effort
Chance and insight
Unexpectedness and insight

Unexpectedness and insight


Intention

Skill and ability


Insight and chance
Accidental and sagacity
Variation and value

Variety and different forms
Types of toolsSectionSpecific nameReferences
Search Engine3.1MaxBrickley et al. [51]
FeegliRahman et al. [52]
SOL-ToolEichler et al. [53]
LTRC modelHuang et al [54]
Micro-blogging3.2TwitterChen et al.[55], Piao et al. [56], Jiang et al.[57], Kazai et al.[58]
Google BlogLi et al. [59]
Recommender System3.3serendipity-related scholarly papers recommendationSugiyama et al. [60]
serendipity-oriented greedy (SOG) algorithmPradhan et al. [61]
SIRUP modelMaccatrozzo et al. [62]
DESRLi et al. [63]
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