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                "en": "# General\nGeoprivacy Open Data is an anonymised tracking dataset in gpx format based on voluntary donations of personal human mobility data. Anonymisation means that all direct and indirect references to a person have been removed, while at the same time, the original data is preserved as much as possible. The raw data donations have been done through the Geoprivacy platform operating at [https://geoprivacy.fi/](https://geoprivacy.fi/).\n\nThe Geoprivacy platform is a service where cyclists, joggers, and pedestrians can donate GPS (Global Positioning System) and other GNSS (Global Navigation Satellite System) tracking data for science. Additionally, the portal offers an open data repository to which users can choose to provide a privacy-protected version of their data. The open data is freely available to urban planners, scientists, and industry, i.e., everyone interested in the innovation potential of detailed personal-level mobility data. The hourly updates of the data are available from the platform, and this data is one of the monthly/yearly frozen versions of live data having exhaustive metadata descriptions, a persistent identifier, and access through the [https://etsin.fairdata.fi](https://etsin.fairdata.fi) service.\n\nThe platform was born as part of our research on privacy issues related to using precise individual-level location data. A prime example of this is activity tracking data, which citizens are recording using various mobile sports tracking applications. **Our vision is that this tracking data could be used to improve the infrastructure for non-motorized means of travel.** Making cycling and walking more safe and convenient could greatly help reduce the number of cars in cities.\n\nActivity tracking data is not easily accessible. Even when tracks are publicly visible on the web, the terms of use usually limit the ways in which the data can be used. Some companies grant specific types of users, e.g., urban planners, access to the data, but only in a heavily processed form. There are good reasons to limit the distribution of the data: Activity tracking data is sensitive data and can reveal surprising personal details. These include, for example, home and workplace, and repeating patterns such as commuting behavior.\n\nWe started the Geoprivacy platform to request voluntary participants to donate their tracking data for science. The original tracks are used only for research related to location data privacy within our research group. However, the participants have the additional option to donate a processed version of their tracks to an open data repository.\n\nWith the open, privacy-preserving data repository, we hope to provide the scientific community with a benchmark dataset for non-motorized mobility data, making research in this area more comparable and reproducible. Furthermore, the open repository can serve as a proof-of-concept for a service that allows citizens to share their data directly with urban planning authorities.\n\n# Privacy protection\nThe details of the privacy protection method are described at [https://geoprivacy.fi/#/privacy-mechanisms](https://geoprivacy.fi/#/privacy-mechanisms). In addition to the listed mechanisms, the population density of the data area needs to be more than 6 inhabitants per square kilometer, and the data has to be inside Finland.\n\n# Versions\nThis dataset is one of the frozen datasets in the series of Geoprivacy Open Data. The other frozen datasets can be found from the Fairdata.fi service [Etsin with the search term \"geoprivacy\"](https://etsin.fairdata.fi/datasets/geoprivacy?keys=&terms=&p=1&sort=best) .\n\n# Format and coordinate system\nThe data is provided in the standard GPX format. The general GPX XML schema is available at [https://www.topografix.com/GPX/1/1/](https://www.topografix.com/GPX/1/1/).\n\nEach GPX file starts with definitions of the XML version and character encoding, the GPX version, and the library used for creating the file. The actual location data is given in <trk> and <trkseq> elements, where the latitude and longitude values of each track point are given after <lat> and <lon> attributes using decimal degrees in the WGS84 coordinate system (EPSG: 4326). The time stamp for each point is given in the <time> element in UTC. For day-time critical applications, conversion to EET/EEST taking into account the day-light saving is important (EET = UTC + 2h, EEST = UTC + 3h).\n\n# Terms of use\nThe dataset is provided as open data, and its use is controlled by [the Terms of Use for the GeoPrivacy Open Data](https://geoprivacy.fi/#/open-data-terms-of-use).\n\nIf you use the data in your work, please use the citation\n\n>Mäkinen, V., Brauer, A. and Oksanen, J. 2023. GeoPrivacy platform, available at: https://geoprivacy.fi\n\nand acknowledge\n\n>\"We made use of geospatial data provided by the Open Geospatial Information Infrastructure for Research (Geoportti, urn:nbn:fi:research-infras-2016072513) funded by the Academy of Finland, CSC – IT Center for Science, and other Geoportti consortium members.\"\n\n# Acknowledgements\nThe Geoprivacy project and platform have been funded by the Finnish Cultural Foundation and the Academy of Finland. The platform is the service pilot of the Geoportti RI (Open Geospatial Information Infrastructure for Research, urn:nbn:fi:research-infras-2016072513)."
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                            "en": "<jats:p>Abstract. Devices with integrated global navigation satellite system (GNSS) receivers have enabled citizens to accurately record activities such as bicycle trips, runs, and walks. Due to its spatiotemporal extent and high level of detail, GNSS-based activity tracking data is a valuable source of information on active modes of transportation. At the same time, movement recordings of individuals are sensitive data and are associated with privacy concerns. In this work, we present a privacy-aware platform where citizens can contribute GNSS tracks to an open repository. The repository is published according to the FAIR data principles: findable, accessible, interoperable, and reusable. This provides the opportunity to use the data as a benchmark for the development of GNSS trajectory processing methods. The platform’s privacy module processes each track before publication, concealing stay points, generalizing the tracks in the temporal dimension, and suppressing tracks in sparsely populated areas. This approach mitigates the most likely re-identification attacks and limits the amount of information that could leak if an attacker succeeds with re-identification. As a residual risk remains, the platform sensitizes users to privacy risks and enables them to make informed decisions about publishing their data.\n                    </jats:p>",
                            "fi": "<jats:p>Abstract. Devices with integrated global navigation satellite system (GNSS) receivers have enabled citizens to accurately record activities such as bicycle trips, runs, and walks. Due to its spatiotemporal extent and high level of detail, GNSS-based activity tracking data is a valuable source of information on active modes of transportation. At the same time, movement recordings of individuals are sensitive data and are associated with privacy concerns. In this work, we present a privacy-aware platform where citizens can contribute GNSS tracks to an open repository. The repository is published according to the FAIR data principles: findable, accessible, interoperable, and reusable. This provides the opportunity to use the data as a benchmark for the development of GNSS trajectory processing methods. The platform’s privacy module processes each track before publication, concealing stay points, generalizing the tracks in the temporal dimension, and suppressing tracks in sparsely populated areas. This approach mitigates the most likely re-identification attacks and limits the amount of information that could leak if an attacker succeeds with re-identification. As a residual risk remains, the platform sensitizes users to privacy risks and enables them to make informed decisions about publishing their data.\n                    </jats:p>",
                            "und": "<jats:p>Abstract. Devices with integrated global navigation satellite system (GNSS) receivers have enabled citizens to accurately record activities such as bicycle trips, runs, and walks. Due to its spatiotemporal extent and high level of detail, GNSS-based activity tracking data is a valuable source of information on active modes of transportation. At the same time, movement recordings of individuals are sensitive data and are associated with privacy concerns. In this work, we present a privacy-aware platform where citizens can contribute GNSS tracks to an open repository. The repository is published according to the FAIR data principles: findable, accessible, interoperable, and reusable. This provides the opportunity to use the data as a benchmark for the development of GNSS trajectory processing methods. The platform’s privacy module processes each track before publication, concealing stay points, generalizing the tracks in the temporal dimension, and suppressing tracks in sparsely populated areas. This approach mitigates the most likely re-identification attacks and limits the amount of information that could leak if an attacker succeeds with re-identification. As a residual risk remains, the platform sensitizes users to privacy risks and enables them to make informed decisions about publishing their data.\n                    </jats:p>"
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                            "en": "The Chinese University of Hong Kong"
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            "description": {
                "en": "This dataset contain maps of monthly averages of tropical forests understory (15 cm above ground) temperature, including all the material necessary for replicating the methodology used in the calculations.\n\nFiles:\n- Daytime temperature maps - Forest understory temperature monthly averages between 6am and 6pm. The averages were calculated using all data from 2000-2021. The file format is GeoTIFF.\n\n- Nighttime - Forest understory temperature monthly averages between 6pm and 6am. The averages were calculated using all data from 2000-2021. The file format is GeoTIFF.\n\n- Daily - Monthly averages of daily aggregated forest understory temperature at a 15 cm height above ground. The averages were calculated using all data from 2000-2021. The file format is GeoTIFF.\n\n**Notes:\n\nUnits = degrees Celsius\nNo_data = 0 (zero)\n\nSpatial resolution = 300 m \nMaps with 30 m resolution are available upon request. Please check the index map file for information on the available tiles.\n\nHere you will also find the Matlab codes and test data that can be used to replicate our methodology, including the location of all sensors used to calibrate and validate our model."
            },
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            "title": {
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                "en": "# General\nGeoprivacy Open Data is an anonymised tracking dataset in gpx format based on voluntary donations of personal human mobility data. Anonymisation means that all direct and indirect references to a person have been removed, while at the same time, the original data is preserved as much as possible. The raw data donations have been done through the Geoprivacy platform operating at [https://geoprivacy.fi/](https://geoprivacy.fi/).\n\nThe Geoprivacy platform is a service where cyclists, joggers, and pedestrians can donate GPS (Global Positioning System) and other GNSS (Global Navigation Satellite System) tracking data for science. Additionally, the portal offers an open data repository to which users can choose to provide a privacy-protected version of their data. The open data is freely available to urban planners, scientists, and industry, i.e., everyone interested in the innovation potential of detailed personal-level mobility data. The hourly updates of the data are available from the platform, and this data is one of the monthly/yearly frozen versions of live data having exhaustive metadata descriptions, a persistent identifier, and access through the [https://etsin.fairdata.fi](https://etsin.fairdata.fi) service.\n\nThe platform was born as part of our research on privacy issues related to using precise individual-level location data. A prime example of this is activity tracking data, which citizens are recording using various mobile sports tracking applications. **Our vision is that this tracking data could be used to improve the infrastructure for non-motorized means of travel.** Making cycling and walking more safe and convenient could greatly help reduce the number of cars in cities.\n\nActivity tracking data is not easily accessible. Even when tracks are publicly visible on the web, the terms of use usually limit the ways in which the data can be used. Some companies grant specific types of users, e.g., urban planners, access to the data, but only in a heavily processed form. There are good reasons to limit the distribution of the data: Activity tracking data is sensitive data and can reveal surprising personal details. These include, for example, home and workplace, and repeating patterns such as commuting behavior.\n\nWe started the Geoprivacy platform to request voluntary participants to donate their tracking data for science. The original tracks are used only for research related to location data privacy within our research group. However, the participants have the additional option to donate a processed version of their tracks to an open data repository.\n\nWith the open, privacy-preserving data repository, we hope to provide the scientific community with a benchmark dataset for non-motorized mobility data, making research in this area more comparable and reproducible. Furthermore, the open repository can serve as a proof-of-concept for a service that allows citizens to share their data directly with urban planning authorities.\n\n# Privacy protection\nThe details of the privacy protection method are described at [https://geoprivacy.fi/#/privacy-mechanisms](https://geoprivacy.fi/#/privacy-mechanisms). In addition to the listed mechanisms, the population density of the data area needs to be more than 6 inhabitants per square kilometer, and the data has to be inside Finland.\n\n# Versions\nThis dataset is one of the frozen datasets in the series of Geoprivacy Open Data. The other frozen datasets can be found from the Fairdata.fi service [Etsin with the search term \"geoprivacy\"](https://etsin.fairdata.fi/datasets/geoprivacy?keys=&terms=&p=1&sort=best) .\n\n# Format and coordinate system\nThe data is provided in the standard GPX format. The general GPX XML schema is available at [https://www.topografix.com/GPX/1/1/](https://www.topografix.com/GPX/1/1/).\n\nEach GPX file starts with definitions of the XML version and character encoding, the GPX version, and the library used for creating the file. The actual location data is given in <trk> and <trkseq> elements, where the latitude and longitude values of each track point are given after <lat> and <lon> attributes using decimal degrees in the WGS84 coordinate system (EPSG: 4326). The time stamp for each point is given in the <time> element in UTC. For day-time critical applications, conversion to EET/EEST taking into account the day-light saving is important (EET = UTC + 2h, EEST = UTC + 3h).\n\n# Terms of use\nThe dataset is provided as open data, and its use is controlled by [the Terms of Use for the GeoPrivacy Open Data](https://geoprivacy.fi/#/open-data-terms-of-use).\n\nIf you use the data in your work, please use the citation\n\n>Mäkinen, V., Brauer, A. and Oksanen, J. 2023. GeoPrivacy platform, available at: https://geoprivacy.fi\n\nand acknowledge\n\n>\"We made use of geospatial data provided by the Open Geospatial Information Infrastructure for Research (Geoportti, urn:nbn:fi:research-infras-2016072513) funded by the Academy of Finland, CSC – IT Center for Science, and other Geoportti consortium members.\"\n\n# Acknowledgements\nThe Geoprivacy project and platform have been funded by the Finnish Cultural Foundation and the Academy of Finland. The platform is the service pilot of the Geoportti RI (Open Geospatial Information Infrastructure for Research, urn:nbn:fi:research-infras-2016072513)."
            },
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                        "title": {
                            "en": "Brauer, Mäkinen, Oksanen: Human mobility tracks as FAIR data: Designing a privacy-preserving repository for GNSS-based activity tracking data",
                            "fi": "Brauer, Mäkinen, Oksanen: Human mobility tracks as FAIR data: Designing a privacy-preserving repository for GNSS-based activity tracking data"
                        },
                        "description": {
                            "en": "<jats:p>Abstract. Devices with integrated global navigation satellite system (GNSS) receivers have enabled citizens to accurately record activities such as bicycle trips, runs, and walks. Due to its spatiotemporal extent and high level of detail, GNSS-based activity tracking data is a valuable source of information on active modes of transportation. At the same time, movement recordings of individuals are sensitive data and are associated with privacy concerns. In this work, we present a privacy-aware platform where citizens can contribute GNSS tracks to an open repository. The repository is published according to the FAIR data principles: findable, accessible, interoperable, and reusable. This provides the opportunity to use the data as a benchmark for the development of GNSS trajectory processing methods. The platform’s privacy module processes each track before publication, concealing stay points, generalizing the tracks in the temporal dimension, and suppressing tracks in sparsely populated areas. This approach mitigates the most likely re-identification attacks and limits the amount of information that could leak if an attacker succeeds with re-identification. As a residual risk remains, the platform sensitizes users to privacy risks and enables them to make informed decisions about publishing their data.\n                    </jats:p>",
                            "fi": "<jats:p>Abstract. Devices with integrated global navigation satellite system (GNSS) receivers have enabled citizens to accurately record activities such as bicycle trips, runs, and walks. Due to its spatiotemporal extent and high level of detail, GNSS-based activity tracking data is a valuable source of information on active modes of transportation. At the same time, movement recordings of individuals are sensitive data and are associated with privacy concerns. In this work, we present a privacy-aware platform where citizens can contribute GNSS tracks to an open repository. The repository is published according to the FAIR data principles: findable, accessible, interoperable, and reusable. This provides the opportunity to use the data as a benchmark for the development of GNSS trajectory processing methods. The platform’s privacy module processes each track before publication, concealing stay points, generalizing the tracks in the temporal dimension, and suppressing tracks in sparsely populated areas. This approach mitigates the most likely re-identification attacks and limits the amount of information that could leak if an attacker succeeds with re-identification. As a residual risk remains, the platform sensitizes users to privacy risks and enables them to make informed decisions about publishing their data.\n                    </jats:p>",
                            "und": "<jats:p>Abstract. Devices with integrated global navigation satellite system (GNSS) receivers have enabled citizens to accurately record activities such as bicycle trips, runs, and walks. Due to its spatiotemporal extent and high level of detail, GNSS-based activity tracking data is a valuable source of information on active modes of transportation. At the same time, movement recordings of individuals are sensitive data and are associated with privacy concerns. In this work, we present a privacy-aware platform where citizens can contribute GNSS tracks to an open repository. The repository is published according to the FAIR data principles: findable, accessible, interoperable, and reusable. This provides the opportunity to use the data as a benchmark for the development of GNSS trajectory processing methods. The platform’s privacy module processes each track before publication, concealing stay points, generalizing the tracks in the temporal dimension, and suppressing tracks in sparsely populated areas. This approach mitigates the most likely re-identification attacks and limits the amount of information that could leak if an attacker succeeds with re-identification. As a residual risk remains, the platform sensitizes users to privacy risks and enables them to make informed decisions about publishing their data.\n                    </jats:p>"
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