Changes

On December 2, 2024 at 10:16:11 PM UTC, admin:
Set author of METR-LA to Haoyang Yan (previously Yuankai Wu)
Updated description of METR-LA from
The METR-LA dataset contains traffic speed data from 207 sensors in Los Angeles over four months, providing a rich spatiotemporal dataset for traffic flow analysis.
to
Urban traffic speed prediction aims to estimate the future traffic speed for improving urban transportation services. The proposed framework is a generic wrapper-style solution to enhance the current GNN-based methods by integrating cross-scale topology-free patterns.
Added the following tags to METR-LA
Changed value of field defined_in to https://doi.org/10.48550/arXiv.2302.09746 in METR-LA
Changed value of field extra_authors to [{'extra_author': 'Xiaolei Ma', 'orcid': ''}] in METR-LA
Changed value of field citation to ['https://doi.org/10.48550/arXiv.2109.05225', 'https://doi.org/10.48550/arXiv.2307.05517'] in METR-LA
Changed value of field landing_page to https://doi.org/10.1016/j.tris.2012.09.002 in METR-LA
Deleted resource Original Metadata from METR-LA
              
    
          
          
        
        
            f 1 { f 1 {
            2   "access_rights": "", 2   "access_rights": "",
            n 3   "author": "Yuankai Wu", n 3   "author": "Haoyang Yan",
            4   "author_email": "", 4   "author_email": "",
            n 5   "citation": [], n 5   "citation": [
            6     "https://doi.org/10.48550/arXiv.2109.05225",
            7     "https://doi.org/10.48550/arXiv.2307.05517"
            8   ],
            6   "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700", 9   "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700",
            n 7   "defined_in": "https://doi.org/10.48550/arXiv.2006.07527", n 10   "defined_in": "https://doi.org/10.48550/arXiv.2302.09746",
            8   "doi": "10.57702/fkv1k5ei", 11   "doi": "10.57702/fkv1k5ei",
            9   "doi_date_published": "2024-11-25", 12   "doi_date_published": "2024-11-25",
            10   "doi_publisher": "TIB", 13   "doi_publisher": "TIB",
            11   "doi_status": true, 14   "doi_status": true,
            12   "domain": "https://service.tib.eu/ldmservice", 15   "domain": "https://service.tib.eu/ldmservice",
            13   "extra_authors": [ 16   "extra_authors": [
            14     { 17     {
            n 15       "extra_author": "Dingyi Zhuang", n 18       "extra_author": "Xiaolei Ma",
            16       "orcid": "" 
            17     }, 
            18     { 
            19       "extra_author": "Aurelie Labbe", 
            20       "orcid": "" 
            21     }, 
            22     { 
            23       "extra_author": "Lijun Sun", 
            24       "orcid": "" 19       "orcid": ""
            25     } 20     }
            26   ], 21   ],
            n 27   "groups": [], n 22   "groups": [
            23     {
            24       "description": "",
            25       "display_name": "Highway Traffic Flow",
            26       "id": "ded0a168-b35a-45c2-ac3f-afd98c694ced",
            27       "image_display_url": "",
            28       "name": "highway-traffic-flow",
            29       "title": "Highway Traffic Flow"
            30     },
            31     {
            32       "description": "",
            33       "display_name": "Traffic Congestion",
            34       "id": "0f186154-2e21-4c05-b6c4-01554cb20b4b",
            35       "image_display_url": "",
            36       "name": "traffic-congestion",
            37       "title": "Traffic Congestion"
            38     },
            39     {
            40       "description": "",
            41       "display_name": "Traffic Flow Forecasting",
            42       "id": "3e9661b1-3f4d-402b-a80e-a74b3e609830",
            43       "image_display_url": "",
            44       "name": "traffic-flow-forecasting",
            45       "title": "Traffic Flow Forecasting"
            46     },
            47     {
            48       "description": "",
            49       "display_name": "Traffic Forecasting",
            50       "id": "15ee440c-f28f-47ec-9e48-e69c56ccac2a",
            51       "image_display_url": "",
            52       "name": "traffic-forecasting",
            53       "title": "Traffic Forecasting"
            54     },
            55     {
            56       "description": "",
            57       "display_name": "Traffic Prediction",
            58       "id": "f109203a-08ca-47b9-afa5-cafc91114421",
            59       "image_display_url": "",
            60       "name": "traffic-prediction",
            61       "title": "Traffic Prediction"
            62     },
            63     {
            64       "description": "",
            65       "display_name": "Traffic Speed",
            66       "id": "714f3458-edc0-4aeb-bd1e-746d58147d98",
            67       "image_display_url": "",
            68       "name": "traffic-speed",
            69       "title": "Traffic Speed"
            70     },
            71     {
            72       "description": "",
            73       "display_name": "Traffic Speed Prediction",
            74       "id": "9723bbf6-5c7e-45c4-9690-1a3c62558eac",
            75       "image_display_url": "",
            76       "name": "traffic-speed-prediction",
            77       "title": "Traffic Speed Prediction"
            78     },
            79     {
            80       "description": "",
            81       "display_name": "Urban Transportation",
            82       "id": "8d1b7076-c42e-4167-ab1e-793eddc19fb7",
            83       "image_display_url": "",
            84       "name": "urban-transportation",
            85       "title": "Urban Transportation"
            86     }
            87   ],
            28   "id": "bd4e3404-a2db-401e-b9aa-36a441c5dd77", 88   "id": "bd4e3404-a2db-401e-b9aa-36a441c5dd77",
            29   "isopen": false, 89   "isopen": false,
            n 30   "landing_page": "", n 90   "landing_page": "https://doi.org/10.1016/j.tris.2012.09.002",
            31   "license_title": null, 91   "license_title": null,
            32   "link_orkg": "", 92   "link_orkg": "",
            33   "metadata_created": "2024-11-25T14:47:44.531437", 93   "metadata_created": "2024-11-25T14:47:44.531437",
            n 34   "metadata_modified": "2024-11-25T14:47:44.858296", n 94   "metadata_modified": "2024-12-02T22:16:10.178212",
            35   "name": "metr-la", 95   "name": "metr-la",
            n 36   "notes": "The METR-LA dataset contains traffic speed data from 207  n 96   "notes": "Urban traffic speed prediction aims to estimate the future 
            37 sensors in Los Angeles over four months, providing a rich  97 traffic speed for improving urban transportation services. The 
            38 spatiotemporal dataset for traffic flow analysis.", 98 proposed framework is a generic wrapper-style solution to enhance the 
            99 current GNN-based methods by integrating cross-scale topology-free 
            100 patterns.",
            39   "num_resources": 1, 101   "num_resources": 0,
            40   "num_tags": 0, 102   "num_tags": 18,
            41   "organization": { 103   "organization": {
            42     "approval_status": "approved", 104     "approval_status": "approved",
            43     "created": "2024-11-25T12:11:38.292601", 105     "created": "2024-11-25T12:11:38.292601",
            44     "description": "", 106     "description": "",
            45     "id": "079d46db-32df-4b48-91f3-0a8bc8f69559", 107     "id": "079d46db-32df-4b48-91f3-0a8bc8f69559",
            46     "image_url": "", 108     "image_url": "",
            47     "is_organization": true, 109     "is_organization": true,
            48     "name": "no-organization", 110     "name": "no-organization",
            49     "state": "active", 111     "state": "active",
            50     "title": "No Organization", 112     "title": "No Organization",
            51     "type": "organization" 113     "type": "organization"
            52   }, 114   },
            53   "owner_org": "079d46db-32df-4b48-91f3-0a8bc8f69559", 115   "owner_org": "079d46db-32df-4b48-91f3-0a8bc8f69559",
            54   "private": false, 116   "private": false,
            55   "relationships_as_object": [], 117   "relationships_as_object": [],
            56   "relationships_as_subject": [], 118   "relationships_as_subject": [],
            n 57   "resources": [ n 119   "resources": [],
            58     { 
            59       "cache_last_updated": null, 
            60       "cache_url": null, 
            61       "created": "2024-11-25T15:30:26", 
            62       "data": [ 
            63         "dcterms:title", 
            64         "dcterms:accessRights", 
            65         "dcterms:creator", 
            66         "dcterms:description", 
            67         "dcterms:issued", 
            68         "dcterms:language", 
            69         "dcterms:identifier", 
            70         "dcat:theme", 
            71         "dcterms:type", 
            72         "dcat:keyword", 
            73         "dcat:landingPage", 
            74         "dcterms:hasVersion", 
            75         "dcterms:format", 
            76         "mls:task", 
            77         "datacite:isDescribedBy" 
            78       ], 
            79       "description": "The json representation of the dataset with its  
            80 distributions based on DCAT.", 
            81       "format": "JSON", 
            82       "hash": "", 
            83       "id": "b152948e-f452-4143-86ae-54e775612b7c", 
            84       "last_modified": "2024-11-25T14:47:44.851889", 
            85       "metadata_modified": "2024-11-25T14:47:44.861321", 
            86       "mimetype": "application/json", 
            87       "mimetype_inner": null, 
            88       "name": "Original Metadata", 
            89       "package_id": "bd4e3404-a2db-401e-b9aa-36a441c5dd77", 
            90       "position": 0, 
            91       "resource_type": null, 
            92       "size": 764, 
            93       "state": "active", 
            94       "url":  
            95 resource/b152948e-f452-4143-86ae-54e775612b7c/download/metadata.json", 
            96       "url_type": "upload" 
            97     } 
            98   ], 
            99   "services_used_list": "", 120   "services_used_list": "",
            100   "state": "active", 121   "state": "active",
            t 101   "tags": [], t 122   "tags": [
            123     {
            124       "display_name": "GNN-based methods",
            125       "id": "b447169a-e850-4608-b458-c8368bdadea8",
            126       "name": "GNN-based methods",
            127       "state": "active",
            128       "vocabulary_id": null
            129     },
            130     {
            131       "display_name": "Loop detectors",
            132       "id": "e5fe3845-f663-4489-a9e0-59aecb200855",
            133       "name": "Loop detectors",
            134       "state": "active",
            135       "vocabulary_id": null
            136     },
            137     {
            138       "display_name": "Los Angeles",
            139       "id": "f6f9182e-4a11-4c47-8eae-e99f285f7ab3",
            140       "name": "Los Angeles",
            141       "state": "active",
            142       "vocabulary_id": null
            143     },
            144     {
            145       "display_name": "Los Angeles County",
            146       "id": "01b2d3e1-fbde-4346-9ec3-c7d5fcb08f81",
            147       "name": "Los Angeles County",
            148       "state": "active",
            149       "vocabulary_id": null
            150     },
            151     {
            152       "display_name": "METR-LA",
            153       "id": "17789aa2-c0b5-47fa-b65f-9ad7c0aac6a3",
            154       "name": "METR-LA",
            155       "state": "active",
            156       "vocabulary_id": null
            157     },
            158     {
            159       "display_name": "METR-LA dataset",
            160       "id": "ff4f9192-f9b4-48fd-9d6f-fbc8c5347231",
            161       "name": "METR-LA dataset",
            162       "state": "active",
            163       "vocabulary_id": null
            164     },
            165     {
            166       "display_name": "Traffic congestion",
            167       "id": "76fb3724-7c00-4454-9bce-757504fe162d",
            168       "name": "Traffic congestion",
            169       "state": "active",
            170       "vocabulary_id": null
            171     },
            172     {
            173       "display_name": "Traffic flow",
            174       "id": "00a5b131-69c0-49a1-bf67-ae287201f023",
            175       "name": "Traffic flow",
            176       "state": "active",
            177       "vocabulary_id": null
            178     },
            179     {
            180       "display_name": "Urban transportation",
            181       "id": "a281354b-6e1b-41c2-abd1-9e3dc9c52fe7",
            182       "name": "Urban transportation",
            183       "state": "active",
            184       "vocabulary_id": null
            185     },
            186     {
            187       "display_name": "highway traffic flow",
            188       "id": "b9a6133c-b127-41e9-9ae0-5da778ca4f9c",
            189       "name": "highway traffic flow",
            190       "state": "active",
            191       "vocabulary_id": null
            192     },
            193     {
            194       "display_name": "spatio-temporal graph",
            195       "id": "7a7ef307-388f-4243-9e44-476ea23223af",
            196       "name": "spatio-temporal graph",
            197       "state": "active",
            198       "vocabulary_id": null
            199     },
            200     {
            201       "display_name": "traffic flow",
            202       "id": "ab23f413-0330-4176-9ed3-f04176a6f6e7",
            203       "name": "traffic flow",
            204       "state": "active",
            205       "vocabulary_id": null
            206     },
            207     {
            208       "display_name": "traffic flow forecasting",
            209       "id": "82445629-4701-4c32-88d1-a3fa79eee946",
            210       "name": "traffic flow forecasting",
            211       "state": "active",
            212       "vocabulary_id": null
            213     },
            214     {
            215       "display_name": "traffic forecasting",
            216       "id": "8cf9898f-7989-4730-b96f-2c8578609453",
            217       "name": "traffic forecasting",
            218       "state": "active",
            219       "vocabulary_id": null
            220     },
            221     {
            222       "display_name": "traffic prediction",
            223       "id": "3a370313-339d-45e0-b76d-918bb08a2790",
            224       "name": "traffic prediction",
            225       "state": "active",
            226       "vocabulary_id": null
            227     },
            228     {
            229       "display_name": "traffic speed",
            230       "id": "f495b8ae-cfee-4e80-9c9f-d7f9185cd294",
            231       "name": "traffic speed",
            232       "state": "active",
            233       "vocabulary_id": null
            234     },
            235     {
            236       "display_name": "traf\ufb01c speed",
            237       "id": "90022b46-7a6f-4300-b222-5a41e035f50e",
            238       "name": "traf\ufb01c speed",
            239       "state": "active",
            240       "vocabulary_id": null
            241     },
            242     {
            243       "display_name": "urban transportation",
            244       "id": "cbf13ed1-a714-460b-b107-cf19e698225a",
            245       "name": "urban transportation",
            246       "state": "active",
            247       "vocabulary_id": null
            248     }
            249   ],
            102   "title": "METR-LA", 250   "title": "METR-LA",
            103   "type": "dataset", 251   "type": "dataset",
            104   "version": "" 252   "version": ""
            105 } 253 }