Introduction
Last updated
Last updated
Time Machine offers an integrated platform for the visualization and analysis of plate tectonic models, raster data, online databases, and analytical tools. It enables users to access online plate reconstruction models, time-sequenced paleogeographic atlases, and a variety of paleogeographic databases and tools. Time Machine organizes these datasets coherently across both spatial and temporal dimensions, supporting the visualisation and manipulation of plate tectonic reconstructions and associated data through geological time. The platform is available on the web, Windows, macOS, and Linux. Users can choose to access Time Machine via a web browser or download native installers for enhanced performance.
to integrate and visualise plate tectonic reconstructions, raster datasets, and paleogeographic information in a unified, time-aware platform
to provide seamless access to online plate models, time-series atlases, and domain-specific databases
to support real-time interaction, analysis, and annotation within spatial-temporal contexts across geological time
to enable researchers to create, explore, and share high-quality paleogeographic reconstructions directly through web and desktop environments
🚀 Real-time plate reconstruction with GPU-accelerated rasterization for rapid plate ID assignment
🌐 Web-based 3D visualization of global plate models and paleogeographic maps across geological timescales
📊 Spatiotemporal framework managing both spatial features and temporal attributes
🔍 Cross-database integration of paleontological, stratigraphic, and geochemical datasets (PBDB, Macrostrat, etc.)
📈 Dynamic evolution charts for quantitative analysis of paleoclimate, topography, and environmental changes
☁️ Cloud-based project system ensuring reproducible research with version-controlled workflows
Time Machine's data repository is comprised entirely of publicly accessible datasets, with a portion of this data having obtained explicit consent from the respective data owners for its use. Our commitment to data transparency and collaboration is paramount, ensuring that users have access to a rich and ethically sourced database.
Our dataset is up-to-date as of December 2023. While we endeavor to maintain the highest level of accuracy, we can only ensure the precision of the original data obtained up until this date. Users are encouraged to verify the data independently, especially for research or applications where data accuracy is critical.
Time Machine is committed to providing a platform that offers publicly accessible data or data that has been made available with the consent of the data owners. While we strive to ensure the quality and integrity of the data presented, we do not assume direct responsibility for the usage or absolute accuracy of the data. Users are encouraged to independently verify the data's validity for their specific needs.
Time Machine assumes responsibility only for safeguarding the privacy and security of the data uploaded by users to the platform that is not designated for public access. We are committed to protecting such data from unauthorized access and disclosure.
It is the user's responsibility to adhere to applicable laws and regulations when using data from the Time Machine platform. Users should be aware of and respect the intellectual property rights and privacy considerations associated with the datasets.
Time Machine disclaims all liability for any harm, loss, or damage that may occur directly or indirectly as a result of using the platform, including but not limited to data inaccuracies or data misuse. By using the platform, users acknowledge and accept this limitation of responsibility.
Haipeng Li
Title / Role: Project Leader / Product Director
Haipeng Li serves as the Product Director. He primarily engages in the design of paleogeographic research platforms and studies related to paleogeographic reconstruction.
Jun Meng
Title / Role: Scientific Advisor
Jun Meng serves as the Scientific Advisor for the Time Machine project. He is a professor at China University of Geosciences (Beijing), with extensive expertise in paleomagnetism. His research interests include geoscience big data, paleomagnetic databases, and paleogeographic reconstruction. Jun has provided numerous valuable insights and constructive suggestions that have significantly contributed to the development of this platform.
Yisa Wang
Title / Role: Chief Technology Officer
Yisa Wang is the Chief Technology Officer at Time Machine project, where he is chiefly in charge of the platform's technical development, including the architectural design of the entire product ecosystem, server infrastructure, and the execution of core algorithms. With a remarkable 16-year tenure in computer science, Yisa has consistently kept Time Machine at the cutting edge of technological innovation. His forward-thinking approach to system architecture significantly enhances the platform's performance, scalability, and security, making substantial contributions to its robust framework.
Han Cheng
Title / Role: Product Manager
Han is a Product Manager with a Master's degree from the China University of Geosciences (Beijing). Han plays a pivotal role in shaping the future of paleogeographic research platforms. He is particularly focused on the product design and project management of the Time Machine project, ensuring its timely progress and alignment with the center's innovative research objectives.
Guixin Zhu
Title / Role: Front-end Developer
Guixin is a promising undergraduate from Zhejiang University of Technology. With a strong foundation in computer science and coding, Guixin has significantly contributed to the user interface and interaction design of Time Machine, enhancing user experience and interface intuitiveness. Her dedication and skill make her an invaluable part of the Time Machine development team.
If you have any questions, please contact us at johncheng0115@gmail.com
