Abstract：Twinning data science with information science in schools of library and information science Purpose As an emerging disciplinedata science represents a vital new current of school of library and information scienceLISeducationHoweverit remains unclear how it relates to information science within LIS schoolsThe purpose of this paper is to clarify this issueDesignmethodologyapproach Mission statement and nature of both data science and information science are analyzed by reviewing existing work in the two disciplines and drawing DIKW hierarchyIt looks at the ways in which information science theories bring new insights and shed new light on fundamentals of data scienceFindings Data science and information science are twin disciplines by natureThe missiontask and nature of data science are consistent with those of information scienceThey greatly overlap and share similar concernsFurthermorethey can complement each otherLIS school should integrate both sciences and develop organizational ambidexterityInformation science can make unique contributions to data science researchincluding conception of datadata quality controldata librarianship and theory dualismDocument theoryas a promising direction of unified information scienceshould be introduced to data science to solve the disciplinary divideOriginalityvalue The results of this paper may contribute to the integration of data science and information science within LIS schools and iSchoolsIt has particular value for LIS school development and reform in the age of big dataThe article refers to the dual theory of data library and theorywhich means that AI may be in library automationCOLLECTION CLLECTION ClassificationRetrieval and INDEXINGand Institution Application in areas such as Instificational CollectionThis article mainly discusses the relationship and integration of data science and information scienceIt involves data explorationespecially in the science of data scienceinvolving useful knowledge and information from large data sets