Pub Date : 2022-07-01DOI: 10.1109/IV56949.2022.00042
Passant Farouk, Nourhan Faransawy, Nada Sharaf
Good collaboration is about clearance between all the team members to let everyone work transparently towards one goal. Augmented Reality was one of the technologies used for data visualization for an immersive and better understanding and analysis of the data. Hence, the collaboration between users on the visualized data in extended reality can combine the analytic power of multiple individuals, and potentially leading to increased quality of solutions and discoveries. The work presented in this paper discusses a remote collaboration technique for enhancing collaboration on visualized data in Augmented Reality. This was done through allowing the user to be immersed to a certain extent, but not completely replacing their reality. The Microsoft Hololens was used to create an Augmented Reality application that transfers the movements of the remote users in real-time using Microsoft Kinect v2 in the form of a hologram of an avatar. This allowed multiple participants to see each other (embodied as avatars), collaborate and interact with 3-Dimension visualized data as shareable holograms between the remote users. An experiment was conducted on 14 participants. The results indicated that the application was useful and fulfills the requirement. We found that the application successfully provided a rich, interesting, and immersive collaborative experience for the students regarding remote collaboration on data visualization in extended reality.
{"title":"Using HoloLens for Remote Collaboration in Extended Data Visualization","authors":"Passant Farouk, Nourhan Faransawy, Nada Sharaf","doi":"10.1109/IV56949.2022.00042","DOIUrl":"https://doi.org/10.1109/IV56949.2022.00042","url":null,"abstract":"Good collaboration is about clearance between all the team members to let everyone work transparently towards one goal. Augmented Reality was one of the technologies used for data visualization for an immersive and better understanding and analysis of the data. Hence, the collaboration between users on the visualized data in extended reality can combine the analytic power of multiple individuals, and potentially leading to increased quality of solutions and discoveries. The work presented in this paper discusses a remote collaboration technique for enhancing collaboration on visualized data in Augmented Reality. This was done through allowing the user to be immersed to a certain extent, but not completely replacing their reality. The Microsoft Hololens was used to create an Augmented Reality application that transfers the movements of the remote users in real-time using Microsoft Kinect v2 in the form of a hologram of an avatar. This allowed multiple participants to see each other (embodied as avatars), collaborate and interact with 3-Dimension visualized data as shareable holograms between the remote users. An experiment was conducted on 14 participants. The results indicated that the application was useful and fulfills the requirement. We found that the application successfully provided a rich, interesting, and immersive collaborative experience for the students regarding remote collaboration on data visualization in extended reality.","PeriodicalId":153161,"journal":{"name":"2022 26th International Conference Information Visualisation (IV)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122600673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.1109/IV56949.2022.00020
Thiago Augusto Soares de Sousa, Walbert Cunha Monteiro, Tiago Araújo, Carlos G. R. Santos, B. Meiguins
This paper aims to present the design process of dynamic data physicalization for bar charts and their variants, simple bars, stacked bars, and clustered bars. The physical artifact has 12 bars that are automatically configured according to the dataset by electromechanical components controlled by an Arduino board. The models of the printed 3D parts, the electromechanical components used and their connection scheme, the design aspects to set up the dynamic physical visualization according to the data, how the users choose the dataset and the kind of physical chart, usage scenarios with different types of charts and physicalization parameters are presented in detail. Finally, some strengths and difficulties in creating dynamic physical visualizations are highlighted and future works are proposed.
{"title":"An Overview of the Design and Development for Dynamic and Physical Bar Charts","authors":"Thiago Augusto Soares de Sousa, Walbert Cunha Monteiro, Tiago Araújo, Carlos G. R. Santos, B. Meiguins","doi":"10.1109/IV56949.2022.00020","DOIUrl":"https://doi.org/10.1109/IV56949.2022.00020","url":null,"abstract":"This paper aims to present the design process of dynamic data physicalization for bar charts and their variants, simple bars, stacked bars, and clustered bars. The physical artifact has 12 bars that are automatically configured according to the dataset by electromechanical components controlled by an Arduino board. The models of the printed 3D parts, the electromechanical components used and their connection scheme, the design aspects to set up the dynamic physical visualization according to the data, how the users choose the dataset and the kind of physical chart, usage scenarios with different types of charts and physicalization parameters are presented in detail. Finally, some strengths and difficulties in creating dynamic physical visualizations are highlighted and future works are proposed.","PeriodicalId":153161,"journal":{"name":"2022 26th International Conference Information Visualisation (IV)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125784238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.1109/IV56949.2022.00035
Taiki Kodomaru, M. Nakayama
In order to improve the readability of metro maps, reading behavior for route search has been analyzed using eye movements in the previous studies. The factors of the numbers of route and transfers on the route were examined. Since the metro map images are different between cities, effectiveness of another factor for image features on eye movements was examined using features of saliency maps. The 48 metro maps were classified into three clusters, the difference of feature of eye movements was extracted. As the results, relationship between fixation time and values of the saliency was discussed.
{"title":"Effects of Image Features and Task Complexity on Eye Movement while searching Metro Map routes","authors":"Taiki Kodomaru, M. Nakayama","doi":"10.1109/IV56949.2022.00035","DOIUrl":"https://doi.org/10.1109/IV56949.2022.00035","url":null,"abstract":"In order to improve the readability of metro maps, reading behavior for route search has been analyzed using eye movements in the previous studies. The factors of the numbers of route and transfers on the route were examined. Since the metro map images are different between cities, effectiveness of another factor for image features on eye movements was examined using features of saliency maps. The 48 metro maps were classified into three clusters, the difference of feature of eye movements was extracted. As the results, relationship between fixation time and values of the saliency was discussed.","PeriodicalId":153161,"journal":{"name":"2022 26th International Conference Information Visualisation (IV)","volume":"152 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127313997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.1109/IV56949.2022.00024
Pedro Santos, Nuno Datia, Matilde Pato, J. Sobral
Asset management is a branch of facilities management that is responsible for the operation and maintenance of assets. The most common means of managing assets and their life-cycle is through requests and work orders. A request is used to report an occurrence that is detected either by a sensory device, a technician, or non-technical personnel; they are used to pointing out that something is wrong in a given asset, and needs appropriate attention. Depending on the problem, a request can give rise to a work order if the solution is not trivial. Work orders consist in technical reports that specify the asset that needs intervention and has the details about the work to be done or, in the case that the work is unknown from the start, the characteristics of the malfunctioning. Work orders contain a set of words, free text, that are not restricted from a fixed set of vocabulary, making it difficult to automatically analyse them. In this paper, we discuss the application of modern Natural Language Processing techniques to process the work order's description, while presenting a comparison between two Word Embedding models - Word2Vec and Fasttext- through semantic similarity tests between the encoded words, and a visualisation of the vector space through dimensionality reduction of the encoded vectors. The results show a better performance of the Fasttext approach, considering the semantics of the results.
{"title":"Comparing Word Embeddings through Visualisation","authors":"Pedro Santos, Nuno Datia, Matilde Pato, J. Sobral","doi":"10.1109/IV56949.2022.00024","DOIUrl":"https://doi.org/10.1109/IV56949.2022.00024","url":null,"abstract":"Asset management is a branch of facilities management that is responsible for the operation and maintenance of assets. The most common means of managing assets and their life-cycle is through requests and work orders. A request is used to report an occurrence that is detected either by a sensory device, a technician, or non-technical personnel; they are used to pointing out that something is wrong in a given asset, and needs appropriate attention. Depending on the problem, a request can give rise to a work order if the solution is not trivial. Work orders consist in technical reports that specify the asset that needs intervention and has the details about the work to be done or, in the case that the work is unknown from the start, the characteristics of the malfunctioning. Work orders contain a set of words, free text, that are not restricted from a fixed set of vocabulary, making it difficult to automatically analyse them. In this paper, we discuss the application of modern Natural Language Processing techniques to process the work order's description, while presenting a comparison between two Word Embedding models - Word2Vec and Fasttext- through semantic similarity tests between the encoded words, and a visualisation of the vector space through dimensionality reduction of the encoded vectors. The results show a better performance of the Fasttext approach, considering the semantics of the results.","PeriodicalId":153161,"journal":{"name":"2022 26th International Conference Information Visualisation (IV)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133126711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.1109/IV56949.2022.00073
R. Francese, M. Frasca, M. Risi, G. Tortora
In recent years it has been assessed that in people with type 2 diabetes the likelihood of developing Alzheimer's disease increases by more than 50%. The purpose of the analysis proposed in this paper is to identify visually the correlation between Alzheimer's disease and type 2 diabetes and determine whether Alzheimer's disease is a form of brain diabetes mellitus. A dataset containing genomic microarray data relating to the two diseases is used for the analysis. First, we conduct an exploratory analysis using clustering techniques to perform a first screening of the samples and divide them into two different clusters. Then, we propose a predictive model for the classification and identify the genes equally expressed in the two types of samples. This makes it possible to select genes with significant values for the research in progress, on which pathway analysis must be performed to identify the classes they belong to. We also study the gene expression alterations of genes belonging to a specific pathway to determine if the differential expression is statistically significant. We provide a visual representation of connections in the pathways of both the diseases. Results indicate that there is a set of genes of significant importance for both type 2 diabetes and Alzheimer's disease, but that there is also a significant correlation with other neurodegenerative diseases. Consequently, it is possible to define the Alzheimer's disease as a form of cerebral diabetes mellitus.
{"title":"Identifying the Correlation between Alzheimer and type 2 Diabetes","authors":"R. Francese, M. Frasca, M. Risi, G. Tortora","doi":"10.1109/IV56949.2022.00073","DOIUrl":"https://doi.org/10.1109/IV56949.2022.00073","url":null,"abstract":"In recent years it has been assessed that in people with type 2 diabetes the likelihood of developing Alzheimer's disease increases by more than 50%. The purpose of the analysis proposed in this paper is to identify visually the correlation between Alzheimer's disease and type 2 diabetes and determine whether Alzheimer's disease is a form of brain diabetes mellitus. A dataset containing genomic microarray data relating to the two diseases is used for the analysis. First, we conduct an exploratory analysis using clustering techniques to perform a first screening of the samples and divide them into two different clusters. Then, we propose a predictive model for the classification and identify the genes equally expressed in the two types of samples. This makes it possible to select genes with significant values for the research in progress, on which pathway analysis must be performed to identify the classes they belong to. We also study the gene expression alterations of genes belonging to a specific pathway to determine if the differential expression is statistically significant. We provide a visual representation of connections in the pathways of both the diseases. Results indicate that there is a set of genes of significant importance for both type 2 diabetes and Alzheimer's disease, but that there is also a significant correlation with other neurodegenerative diseases. Consequently, it is possible to define the Alzheimer's disease as a form of cerebral diabetes mellitus.","PeriodicalId":153161,"journal":{"name":"2022 26th International Conference Information Visualisation (IV)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116962647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.1109/IV56949.2022.00057
Midhad Blazevic, Lennart B. Sina, Kawa Nazemi
Studies have shown that collaboration in scientific fields is rising and considered enormously important. However, collaboration has proved to be challenging for various reasons, among others, the requirements for human-machine workflows. The importance of scientific collaboration lies in the complexity of the challenges that are faced today. The more complex the challenge, the more scientists should work together. The current form of collaboration in the scientific community is not as intelligent as it should be. Scientists have to multitask with various applications, often losing cognitive focus. Collaboration itself is very nearsighted as it is usually conducted not solely based on expertise but instead on social or local networks. We introduce a single-source visual collaboration approach based on learning methods in this work. We use machine learning and natural language processing approaches to improve the traditional research and development process and create a system that facilitates and encourages collaboration based on expertise, enhancing the research collaboration process in many ways. Our approach combines collaborative Visual Analytics with enhanced collaboration techniques to support researchers from different disciplines.
{"title":"Visual Collaboration - An Approach for Visual Analytical Collaborative Research","authors":"Midhad Blazevic, Lennart B. Sina, Kawa Nazemi","doi":"10.1109/IV56949.2022.00057","DOIUrl":"https://doi.org/10.1109/IV56949.2022.00057","url":null,"abstract":"Studies have shown that collaboration in scientific fields is rising and considered enormously important. However, collaboration has proved to be challenging for various reasons, among others, the requirements for human-machine workflows. The importance of scientific collaboration lies in the complexity of the challenges that are faced today. The more complex the challenge, the more scientists should work together. The current form of collaboration in the scientific community is not as intelligent as it should be. Scientists have to multitask with various applications, often losing cognitive focus. Collaboration itself is very nearsighted as it is usually conducted not solely based on expertise but instead on social or local networks. We introduce a single-source visual collaboration approach based on learning methods in this work. We use machine learning and natural language processing approaches to improve the traditional research and development process and create a system that facilitates and encourages collaboration based on expertise, enhancing the research collaboration process in many ways. Our approach combines collaborative Visual Analytics with enhanced collaboration techniques to support researchers from different disciplines.","PeriodicalId":153161,"journal":{"name":"2022 26th International Conference Information Visualisation (IV)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131008547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.1109/IV56949.2022.00041
Adriano Requena, Juliana da Costa Feitosa, Luiz Felipe de Camargo, J. Brega
The use of Information Visualization techniques and research into genetics have greatly improved knowledge in medicine, health, animal breeding, and even in commerce itself. The data is often complex in structure and difficult to understand. Researchers have obtained patterns and knowledge about these data, and with this, the processes of discovery about drugs for diseases, improvement in the cultivation of crops, and in animal breeding itself for a better yield in each of these areas. The goal is, through a tool with visualization techniques, to assist in the monitoring of genetic improvement in fish breeding belonging to the genetics laboratory of a partner university. The requirements survey was carried out with Ph.D. and Ph.D. students in the Aquaculture area.
{"title":"Using Information Visualization Techniques for Fish Genetic Management","authors":"Adriano Requena, Juliana da Costa Feitosa, Luiz Felipe de Camargo, J. Brega","doi":"10.1109/IV56949.2022.00041","DOIUrl":"https://doi.org/10.1109/IV56949.2022.00041","url":null,"abstract":"The use of Information Visualization techniques and research into genetics have greatly improved knowledge in medicine, health, animal breeding, and even in commerce itself. The data is often complex in structure and difficult to understand. Researchers have obtained patterns and knowledge about these data, and with this, the processes of discovery about drugs for diseases, improvement in the cultivation of crops, and in animal breeding itself for a better yield in each of these areas. The goal is, through a tool with visualization techniques, to assist in the monitoring of genetic improvement in fish breeding belonging to the genetics laboratory of a partner university. The requirements survey was carried out with Ph.D. and Ph.D. students in the Aquaculture area.","PeriodicalId":153161,"journal":{"name":"2022 26th International Conference Information Visualisation (IV)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127445310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.1109/IV56949.2022.00025
Luc-Etienne Pommé, Romain Bourqui, R. Giot, D. Auber
Current machine learning and deep learning approaches are cutting-edge methods for solving classification tasks. Comparing the performances of classification models has become a prominent task since the outbreak of these techniques. The performance of such classification models is measured by the ratio between the correctly predicted samples and the others. The most widely used visualization to represent this information is the Confusion matrix. Yet, if this technique is suited to apprehend one model performances, very few works use this representation to compare models. In that paper, we present the Relative Confusion Matrix (RCM), a new matrix visualization that leverages Confusion matrices and a color encoding to expose the class-wise differences of performances between two models. We conduct a user evaluation to compare RCM with two confusion matrix variants. Our results show that RCM encoding leads to a more efficient comparison of two models than existing approaches.
{"title":"Relative Confusion Matrix: Efficient Comparison of Decision Models","authors":"Luc-Etienne Pommé, Romain Bourqui, R. Giot, D. Auber","doi":"10.1109/IV56949.2022.00025","DOIUrl":"https://doi.org/10.1109/IV56949.2022.00025","url":null,"abstract":"Current machine learning and deep learning approaches are cutting-edge methods for solving classification tasks. Comparing the performances of classification models has become a prominent task since the outbreak of these techniques. The performance of such classification models is measured by the ratio between the correctly predicted samples and the others. The most widely used visualization to represent this information is the Confusion matrix. Yet, if this technique is suited to apprehend one model performances, very few works use this representation to compare models. In that paper, we present the Relative Confusion Matrix (RCM), a new matrix visualization that leverages Confusion matrices and a color encoding to expose the class-wise differences of performances between two models. We conduct a user evaluation to compare RCM with two confusion matrix variants. Our results show that RCM encoding leads to a more efficient comparison of two models than existing approaches.","PeriodicalId":153161,"journal":{"name":"2022 26th International Conference Information Visualisation (IV)","volume":"428 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132106011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.1109/IV56949.2022.00070
Jukka Holm, R. Laaksonen, P. Dendale, C. Bonneux, M. Scherrenberg
Coronary heart disease (CHD) remains the leading cause of premature death worldwide. Better risk stratification tools and personalized care of patients are needed for reducing the morbidity and mortality of CHD and the associated economic burden. However, contemporary e-learning solutions lack personalization and shared decision making and as a result, overwhelm patients with large amounts of information. CoroPrevention is a multiyear, EU-funded Horizon 2020 research project aiming to shape and implement a personalized secondary prevention strategy for patients with established CHD. As a part of the project, new digital tools will also be validated. In this paper, we discuss the process of creating audio-visual content for the CoroPrevention mobile application during the challenging COVID-19 pandemic.
{"title":"Creating Audio-Visual Content for a Personalized Prevention Programme in Coronary Heart Disease","authors":"Jukka Holm, R. Laaksonen, P. Dendale, C. Bonneux, M. Scherrenberg","doi":"10.1109/IV56949.2022.00070","DOIUrl":"https://doi.org/10.1109/IV56949.2022.00070","url":null,"abstract":"Coronary heart disease (CHD) remains the leading cause of premature death worldwide. Better risk stratification tools and personalized care of patients are needed for reducing the morbidity and mortality of CHD and the associated economic burden. However, contemporary e-learning solutions lack personalization and shared decision making and as a result, overwhelm patients with large amounts of information. CoroPrevention is a multiyear, EU-funded Horizon 2020 research project aiming to shape and implement a personalized secondary prevention strategy for patients with established CHD. As a part of the project, new digital tools will also be validated. In this paper, we discuss the process of creating audio-visual content for the CoroPrevention mobile application during the challenging COVID-19 pandemic.","PeriodicalId":153161,"journal":{"name":"2022 26th International Conference Information Visualisation (IV)","volume":"13 46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134140566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.1109/IV56949.2022.00067
A. Afonso, J. Pires, Nuno Datia, Fernando Birra
With urban development in cities, shared bicycle systems are increasingly used as a way to avoid traffic caused by cars, promoting sustainable mobility and contributing for traffic and pollution reduction in urban areas. The imbalance in the availability of bicycles and docks at the stations of the systems makes it impossible to rent and return bicycles, making it necessary to redistribute them across the network. However, this process has flaws, mainly during rush hours. In this paper, we analyse data provided by the Lisbon City Council regarding their bike sharing system, which has the rebalancing operations' influence. Since the original data was contaminated with the rebalancing operations, an analysis was conducted in an attempt to remove this influence from the data. Following this analysis, a new dataset was created using only the trip data to enable model development for each station and predict the bicycle demand. The plateaus in the created dataset were then analysed to determine if they're due to lack of demand from costumers, or due to stations being full or empty.
{"title":"Bicycle Demand Prediction to Optimize the Rebalancing of a Bike Sharing System in Lisbon","authors":"A. Afonso, J. Pires, Nuno Datia, Fernando Birra","doi":"10.1109/IV56949.2022.00067","DOIUrl":"https://doi.org/10.1109/IV56949.2022.00067","url":null,"abstract":"With urban development in cities, shared bicycle systems are increasingly used as a way to avoid traffic caused by cars, promoting sustainable mobility and contributing for traffic and pollution reduction in urban areas. The imbalance in the availability of bicycles and docks at the stations of the systems makes it impossible to rent and return bicycles, making it necessary to redistribute them across the network. However, this process has flaws, mainly during rush hours. In this paper, we analyse data provided by the Lisbon City Council regarding their bike sharing system, which has the rebalancing operations' influence. Since the original data was contaminated with the rebalancing operations, an analysis was conducted in an attempt to remove this influence from the data. Following this analysis, a new dataset was created using only the trip data to enable model development for each station and predict the bicycle demand. The plateaus in the created dataset were then analysed to determine if they're due to lack of demand from costumers, or due to stations being full or empty.","PeriodicalId":153161,"journal":{"name":"2022 26th International Conference Information Visualisation (IV)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129291037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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