Dataset Open Access
Schäfer, Matthias;
Strohmeier, Martin;
Leonardi, Mauro;
Lenders, Vincent
{ "files": [ { "links": { "self": "https://zenodo.org/api/files/9f7d306c-2808-4ef2-8048-549257667036/LICENSE.txt" }, "checksum": "md5:fba3b94d88bfb9b81369b869a1e9a20f", "bucket": "9f7d306c-2808-4ef2-8048-549257667036", "key": "LICENSE.txt", "type": "txt", "size": 20131 }, { "links": { "self": "https://zenodo.org/api/files/9f7d306c-2808-4ef2-8048-549257667036/NOTE.txt" }, "checksum": "md5:eb30a57e60b92d09493c37f69891ce61", "bucket": "9f7d306c-2808-4ef2-8048-549257667036", "key": "NOTE.txt", "type": "txt", "size": 326 }, { "links": { "self": "https://zenodo.org/api/files/9f7d306c-2808-4ef2-8048-549257667036/subset_1.zip" }, "checksum": "md5:ca2e163f437ff8b9dfaef64bed871ff3", "bucket": "9f7d306c-2808-4ef2-8048-549257667036", "key": "subset_1.zip", "type": "zip", "size": 453251794 }, { "links": { "self": "https://zenodo.org/api/files/9f7d306c-2808-4ef2-8048-549257667036/subset_2.zip" }, "checksum": "md5:9e40dcb90cad589e9d7f3ffc2a1af753", "bucket": "9f7d306c-2808-4ef2-8048-549257667036", "key": "subset_2.zip", "type": "zip", "size": 459732296 }, { "links": { "self": "https://zenodo.org/api/files/9f7d306c-2808-4ef2-8048-549257667036/subset_3.zip" }, "checksum": "md5:950319a9b6791f3111bf4cb01a510846", "bucket": "9f7d306c-2808-4ef2-8048-549257667036", "key": "subset_3.zip", "type": "zip", "size": 460399765 }, { "links": { "self": "https://zenodo.org/api/files/9f7d306c-2808-4ef2-8048-549257667036/subset_4.zip" }, "checksum": "md5:2d1a788ee8fca8550e8bb758b11824c5", "bucket": "9f7d306c-2808-4ef2-8048-549257667036", "key": "subset_4.zip", "type": "zip", "size": 448089665 }, { "links": { "self": "https://zenodo.org/api/files/9f7d306c-2808-4ef2-8048-549257667036/subset_5.zip" }, "checksum": "md5:8cbd3f3af5f341e0dd65baad9066f05a", "bucket": "9f7d306c-2808-4ef2-8048-549257667036", "key": "subset_5.zip", "type": "zip", "size": 426054356 }, { "links": { "self": "https://zenodo.org/api/files/9f7d306c-2808-4ef2-8048-549257667036/subset_6.zip" }, "checksum": "md5:bbea4a6e777d35d2bd5c1f54394586b6", "bucket": "9f7d306c-2808-4ef2-8048-549257667036", "key": "subset_6.zip", "type": "zip", "size": 440840860 }, { "links": { "self": "https://zenodo.org/api/files/9f7d306c-2808-4ef2-8048-549257667036/subset_7.zip" }, "checksum": "md5:e312d2e974173220ee4d0887374ec0c7", "bucket": "9f7d306c-2808-4ef2-8048-549257667036", "key": "subset_7.zip", "type": "zip", "size": 442703368 }, { "links": { "self": "https://zenodo.org/api/files/9f7d306c-2808-4ef2-8048-549257667036/subset_8.zip" }, "checksum": "md5:45413ab8ee02db6dc43f75e5bebcadd7", "bucket": "9f7d306c-2808-4ef2-8048-549257667036", "key": "subset_8.zip", "type": "zip", "size": 437080284 } ], "owners": [ 96905 ], "doi": "10.5281/zenodo.4739276", "stats": { "version_unique_downloads": 757.0, "unique_views": 522.0, "views": 589.0, "version_views": 1713.0, "unique_downloads": 182.0, "version_unique_views": 1407.0, "volume": 202489046534.0, "version_downloads": 2903.0, "downloads": 553.0, "version_volume": 1140594913181.0 }, "links": { "doi": "https://doi.org/10.5281/zenodo.4739276", "conceptdoi": "https://doi.org/10.5281/zenodo.4298998", "bucket": "https://zenodo.org/api/files/9f7d306c-2808-4ef2-8048-549257667036", "conceptbadge": "https://zenodo.org/badge/doi/10.5281/zenodo.4298998.svg", "html": "https://zenodo.org/record/4739276", "latest_html": "https://zenodo.org/record/4739276", "badge": "https://zenodo.org/badge/doi/10.5281/zenodo.4739276.svg", "latest": "https://zenodo.org/api/records/4739276" }, "conceptdoi": "10.5281/zenodo.4298998", "created": "2021-05-05T16:41:04.331423+00:00", "updated": "2021-05-06T01:48:11.011770+00:00", "conceptrecid": "4298998", "revision": 2, "id": 4739276, "metadata": { "access_right_category": "success", "doi": "10.5281/zenodo.4739276", "description": "<p>Accompanying dataset to the LocaRDS paper.</p>\n\n<p>With this work, we attempt to improve the current state of the art in localization research and put it on a solid scientific grounding for the future. Concretely, LocaRDS is an open reference dataset of real-world crowdsourced flight data from the OpenSky Network featuring more than 222 million measurements from over 50 million transmissions recorded by 323 sensors. LocaRDS can be used to test, analyze and directly compare different localization techniques. It is intended to answer in particular the open question of the aircraft localization problem in crowdsourced sensor networks.</p>", "license": { "id": "CC-BY-SA-4.0" }, "title": "LocaRDS: A Localization Reference Data Set", "notes": "Set 1 was used in the Aircraft Localization Competition at https://www.aicrowd.com/challenges/cyd-campus-aircraft-localization-competition It has now been added after the end of the competition in March 2021.", "relations": { "version": [ { "count": 4, "index": 3, "parent": { "pid_type": "recid", "pid_value": "4298998" }, "is_last": true, "last_child": { "pid_type": "recid", "pid_value": "4739276" } } ] }, "version": "1.0", "references": [ "https://arxiv.org/abs/2012.00116" ], "keywords": [ "localization", "crowdsourcing", "opensky", "aircraft", "flight data" ], "publication_date": "2020-11-30", "creators": [ { "affiliation": "University of Kaiserslautern", "name": "Sch\u00e4fer, Matthias" }, { "orcid": "0000-0002-1936-0933", "affiliation": "armasuisse W+T, University of Oxford", "name": "Strohmeier, Martin" }, { "affiliation": "University of Roma, Tor Vergata", "name": "Leonardi, Mauro" }, { "affiliation": "armasuisse W+T", "name": "Lenders, Vincent" } ], "access_right": "open", "resource_type": { "type": "dataset", "title": "Dataset" }, "related_identifiers": [ { "scheme": "arxiv", "identifier": "arXiv:2012.00116", "relation": "isSupplementTo", "resource_type": "publication-preprint" }, { "scheme": "doi", "identifier": "10.5281/zenodo.4298998", "relation": "isVersionOf" } ] } }
All versions | This version | |
---|---|---|
Views | 1,713 | 589 |
Downloads | 2,903 | 553 |
Data volume | 1.1 TB | 202.5 GB |
Unique views | 1,407 | 522 |
Unique downloads | 757 | 182 |