{"title":"tramoTDA:使用拓扑数据分析的轨迹监测系统","authors":"Miriam Esteve, Antonio Falcó","doi":"10.1016/j.softx.2024.101953","DOIUrl":null,"url":null,"abstract":"<div><div>Due to the rapid proliferation of mobile devices and advanced tracking sensors, there is a significant increase in data production daily. In response, we have created <em>tramoTDA</em>, a Python library that uses Topological Data Analysis (TDA) to enable intuitive and visually-oriented classification of trajectory data. This tool offers a unique approach by focusing on the data’s topological properties, which enables the identification of subtle and critical patterns often missed by conventional methods. <em>tramoTDA</em> combines scientific rigor with user-friendly design, making it suitable for both technical and non-technical users in diverse applications such as urban planning and maritime navigation. Through its innovative use of TDA, <em>tramoTDA</em> not only enhances data interpretation but also facilitates new research opportunities in complex system analysis, positioning it as a pivotal resource in data science and analytics.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"28 ","pages":"Article 101953"},"PeriodicalIF":2.4000,"publicationDate":"2024-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"tramoTDA: A trajectory monitoring system using Topological Data Analysis\",\"authors\":\"Miriam Esteve, Antonio Falcó\",\"doi\":\"10.1016/j.softx.2024.101953\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Due to the rapid proliferation of mobile devices and advanced tracking sensors, there is a significant increase in data production daily. In response, we have created <em>tramoTDA</em>, a Python library that uses Topological Data Analysis (TDA) to enable intuitive and visually-oriented classification of trajectory data. This tool offers a unique approach by focusing on the data’s topological properties, which enables the identification of subtle and critical patterns often missed by conventional methods. <em>tramoTDA</em> combines scientific rigor with user-friendly design, making it suitable for both technical and non-technical users in diverse applications such as urban planning and maritime navigation. Through its innovative use of TDA, <em>tramoTDA</em> not only enhances data interpretation but also facilitates new research opportunities in complex system analysis, positioning it as a pivotal resource in data science and analytics.</div></div>\",\"PeriodicalId\":21905,\"journal\":{\"name\":\"SoftwareX\",\"volume\":\"28 \",\"pages\":\"Article 101953\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2024-11-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SoftwareX\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352711024003236\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SoftwareX","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352711024003236","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
tramoTDA: A trajectory monitoring system using Topological Data Analysis
Due to the rapid proliferation of mobile devices and advanced tracking sensors, there is a significant increase in data production daily. In response, we have created tramoTDA, a Python library that uses Topological Data Analysis (TDA) to enable intuitive and visually-oriented classification of trajectory data. This tool offers a unique approach by focusing on the data’s topological properties, which enables the identification of subtle and critical patterns often missed by conventional methods. tramoTDA combines scientific rigor with user-friendly design, making it suitable for both technical and non-technical users in diverse applications such as urban planning and maritime navigation. Through its innovative use of TDA, tramoTDA not only enhances data interpretation but also facilitates new research opportunities in complex system analysis, positioning it as a pivotal resource in data science and analytics.
期刊介绍:
SoftwareX aims to acknowledge the impact of software on today''s research practice, and on new scientific discoveries in almost all research domains. SoftwareX also aims to stress the importance of the software developers who are, in part, responsible for this impact. To this end, SoftwareX aims to support publication of research software in such a way that: The software is given a stamp of scientific relevance, and provided with a peer-reviewed recognition of scientific impact; The software developers are given the credits they deserve; The software is citable, allowing traditional metrics of scientific excellence to apply; The academic career paths of software developers are supported rather than hindered; The software is publicly available for inspection, validation, and re-use. Above all, SoftwareX aims to inform researchers about software applications, tools and libraries with a (proven) potential to impact the process of scientific discovery in various domains. The journal is multidisciplinary and accepts submissions from within and across subject domains such as those represented within the broad thematic areas below: Mathematical and Physical Sciences; Environmental Sciences; Medical and Biological Sciences; Humanities, Arts and Social Sciences. Originating from these broad thematic areas, the journal also welcomes submissions of software that works in cross cutting thematic areas, such as citizen science, cybersecurity, digital economy, energy, global resource stewardship, health and wellbeing, etcetera. SoftwareX specifically aims to accept submissions representing domain-independent software that may impact more than one research domain.