Changes

On December 2, 2024 at 5:50:50 PM UTC, admin:
Set author of S3DIS to Wei Zhou (previously Iro Armeni)
Updated description of S3DIS from
Stanford Large-Scale 3D Indoor Spaces Dataset (S3DIS) consists of indoor scenes of 272 rooms in six indoor areas, annotated with 13 semantic categories. It is used for semantic segmentation tasks.
to
The dataset used in the paper is a real-world 3D point cloud dataset, which is used for 3D shape classification, part segmentation, and shape retrieval tasks.
Added the following tags to S3DIS
Changed value of field defined_in to https://doi.org/10.48550/arXiv.2309.00828 in S3DIS
Changed value of field extra_authors to [{'extra_author': 'Xin Cao', 'orcid': ''}, {'extra_author': 'Xiaodan Zhang', 'orcid': ''}, {'extra_author': 'Xingxing Hao', 'orcid': ''}, {'extra_author': 'Dekui Wang', 'orcid': ''}, {'extra_author': 'Ying He', 'orcid': ''}] in S3DIS
Changed value of field citation to ['https://doi.org/10.48550/arXiv.1904.02375', 'https://doi.org/10.48550/arXiv.2107.14230', 'https://doi.org/10.48550/arXiv.2111.13386', 'https://doi.org/10.48550/arXiv.1908.06295', 'https://doi.org/10.48550/arXiv.2007.11679', 'https://doi.org/10.48550/arXiv.1905.13445', 'https://doi.org/10.48550/arXiv.1909.09287', 'https://doi.org/10.48550/arXiv.1909.13603', 'https://doi.org/10.48550/arXiv.2302.02858', 'https://doi.org/10.48550/arXiv.2210.01558', 'https://doi.org/10.48550/arXiv.2212.14197', 'https://doi.org/10.48550/arXiv.2107.13152', 'https://doi.org/10.48550/arXiv.2312.11451', 'https://doi.org/10.48550/arXiv.2205.00630', 'https://doi.org/10.48550/arXiv.2103.10339', 'https://doi.org/10.48550/arXiv.2306.11051', 'https://doi.org/10.48550/arXiv.2004.12498', 'https://doi.org/10.1109/ICME52920.2022.9859996', 'https://doi.org/10.48550/arXiv.2309.07425', 'https://doi.org/10.48550/arXiv.2309.15702', 'https://doi.org/10.48550/arXiv.2007.15855'] in S3DIS
Changed value of field landing_page to https://s3dis.stanford.edu/ in S3DIS
Deleted resource Original Metadata from S3DIS
              
    
          
          
        
        
            f 1 { f 1 {
            2   "access_rights": "", 2   "access_rights": "",
            n 3   "author": "Iro Armeni", n 3   "author": "Wei Zhou",
            4   "author_email": "", 4   "author_email": "",
            n 5   "citation": [], n 5   "citation": [
            6     "https://doi.org/10.48550/arXiv.1904.02375",
            7     "https://doi.org/10.48550/arXiv.2107.14230",
            8     "https://doi.org/10.48550/arXiv.2111.13386",
            9     "https://doi.org/10.48550/arXiv.1908.06295",
            10     "https://doi.org/10.48550/arXiv.2007.11679",
            11     "https://doi.org/10.48550/arXiv.1905.13445",
            12     "https://doi.org/10.48550/arXiv.1909.09287",
            13     "https://doi.org/10.48550/arXiv.1909.13603",
            14     "https://doi.org/10.48550/arXiv.2302.02858",
            15     "https://doi.org/10.48550/arXiv.2210.01558",
            16     "https://doi.org/10.48550/arXiv.2212.14197",
            17     "https://doi.org/10.48550/arXiv.2107.13152",
            18     "https://doi.org/10.48550/arXiv.2312.11451",
            19     "https://doi.org/10.48550/arXiv.2205.00630",
            20     "https://doi.org/10.48550/arXiv.2103.10339",
            21     "https://doi.org/10.48550/arXiv.2306.11051",
            22     "https://doi.org/10.48550/arXiv.2004.12498",
            23     "https://doi.org/10.1109/ICME52920.2022.9859996",
            24     "https://doi.org/10.48550/arXiv.2309.07425",
            25     "https://doi.org/10.48550/arXiv.2309.15702",
            26     "https://doi.org/10.48550/arXiv.2007.15855"
            27   ],
            6   "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700", 28   "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700",
            n 7   "defined_in": "", n 29   "defined_in": "https://doi.org/10.48550/arXiv.2309.00828",
            8   "doi": "10.57702/zi852631", 30   "doi": "10.57702/zi852631",
            9   "doi_date_published": "2024-11-25", 31   "doi_date_published": "2024-11-25",
            10   "doi_publisher": "TIB", 32   "doi_publisher": "TIB",
            11   "doi_status": true, 33   "doi_status": true,
            12   "domain": "https://service.tib.eu/ldmservice", 34   "domain": "https://service.tib.eu/ldmservice",
            13   "extra_authors": [ 35   "extra_authors": [
            14     { 36     {
            n 15       "extra_author": "Ozan Sener", n 37       "extra_author": "Xin Cao",
            16       "orcid": "" 38       "orcid": ""
            17     }, 39     },
            18     { 40     {
            n 19       "extra_author": "Amir R Zamir", n 41       "extra_author": "Xiaodan Zhang",
            20       "orcid": "" 42       "orcid": ""
            21     }, 43     },
            22     { 44     {
            n 23       "extra_author": "Helen Jiang", n 45       "extra_author": "Xingxing Hao",
            24       "orcid": "" 46       "orcid": ""
            25     }, 47     },
            26     { 48     {
            n 27       "extra_author": "Ioannis Brilakis", n 49       "extra_author": "Dekui Wang",
            28       "orcid": "" 50       "orcid": ""
            29     }, 51     },
            30     { 52     {
            n 31       "extra_author": "Martin Fischer", n 53       "extra_author": "Ying He",
            32       "orcid": "" 
            33     }, 
            34     { 
            35       "extra_author": "Silvio Savarese", 
            36       "orcid": "" 54       "orcid": ""
            37     } 55     }
            38   ], 56   ],
            n 39   "groups": [], n 57   "groups": [
            58     {
            59       "description": "",
            60       "display_name": "3D Indoor Scene Understanding",
            61       "id": "1277aa66-82c9-4b25-afef-a65971caacd0",
            62       "image_display_url": "",
            63       "name": "3d-indoor-scene-understanding",
            64       "title": "3D Indoor Scene Understanding"
            65     },
            66     {
            67       "description": "",
            68       "display_name": "3D Indoor Scenes",
            69       "id": "d412ff56-9507-4707-980b-d70904021eea",
            70       "image_display_url": "",
            71       "name": "3d-indoor-scenes",
            72       "title": "3D Indoor Scenes"
            73     },
            74     {
            75       "description": "",
            76       "display_name": "3D Indoor Spaces",
            77       "id": "14e30722-ae2c-4ab8-a426-b83ab9fee517",
            78       "image_display_url": "",
            79       "name": "3d-indoor-spaces",
            80       "title": "3D Indoor Spaces"
            81     },
            82     {
            83       "description": "",
            84       "display_name": "3D Instance Segmentation",
            85       "id": "df7e5dbf-bb57-4ebd-a62f-f2a1b16d3ed3",
            86       "image_display_url": "",
            87       "name": "3d-instance-segmentation",
            88       "title": "3D Instance Segmentation"
            89     },
            90     {
            91       "description": "",
            92       "display_name": "3D Object Detection",
            93       "id": "b9c5385e-2cc8-4698-95f2-a1528ebb0182",
            94       "image_display_url": "",
            95       "name": "3d-object-detection",
            96       "title": "3D Object Detection"
            97     },
            98     {
            99       "description": "",
            100       "display_name": "3D Object Recognition",
            101       "id": "fb966b89-2ab8-4ac3-ae8e-55e18c4de9e1",
            102       "image_display_url": "",
            103       "name": "3d-object-recognition",
            104       "title": "3D Object Recognition"
            105     },
            106     {
            107       "description": "",
            108       "display_name": "3D Point Clouds",
            109       "id": "625c463b-8cb0-4180-af63-ed8448fb60dd",
            110       "image_display_url": "",
            111       "name": "3d-point-clouds",
            112       "title": "3D Point Clouds"
            113     },
            114     {
            115       "description": "",
            116       "display_name": "3D Scene Understanding",
            117       "id": "bbef9259-bb19-4e31-8610-6745016a53bc",
            118       "image_display_url": "",
            119       "name": "3d-scene-understanding",
            120       "title": "3D Scene Understanding"
            121     },
            122     {
            123       "description": "",
            124       "display_name": "3D Segmentation",
            125       "id": "5fb93d50-245b-457e-ad22-68dd93ce3dac",
            126       "image_display_url": "",
            127       "name": "3d-segmentation",
            128       "title": "3D Segmentation"
            129     },
            130     {
            131       "description": "",
            132       "display_name": "3D Semantic Segmentation",
            133       "id": "4b4f04aa-d4f5-497c-87dc-f8c937d3e844",
            134       "image_display_url": "",
            135       "name": "3d-semantic-segmentation",
            136       "title": "3D Semantic Segmentation"
            137     },
            138     {
            139       "description": "",
            140       "display_name": "Classification",
            141       "id": "57bb78f3-a48d-4716-a9cc-0028df74b1c5",
            142       "image_display_url": "",
            143       "name": "classification",
            144       "title": "Classification"
            145     },
            146     {
            147       "description": "",
            148       "display_name": "Computer Vision",
            149       "id": "d09caf7c-26c7-4e4d-bb8e-49476a90ba25",
            150       "image_display_url": "",
            151       "name": "computer-vision",
            152       "title": "Computer Vision"
            153     },
            154     {
            155       "description": "",
            156       "display_name": "Indoor Scene Understanding",
            157       "id": "6f671b4b-0b4d-4fe1-9769-e31ab164e205",
            158       "image_display_url": "",
            159       "name": "indoor-scene-understanding",
            160       "title": "Indoor Scene Understanding"
            161     },
            162     {
            163       "description": "",
            164       "display_name": "Indoor Scenes",
            165       "id": "1cdde29d-6358-4f23-823c-0e7caad9ae2e",
            166       "image_display_url": "",
            167       "name": "indoor-scenes",
            168       "title": "Indoor Scenes"
            169     },
            170     {
            171       "description": "",
            172       "display_name": "Indoor Semantic Segmentation",
            173       "id": "34764a61-9771-4ca9-bdde-50fb90076900",
            174       "image_display_url": "",
            175       "name": "indoor-semantic-segmentation",
            176       "title": "Indoor Semantic Segmentation"
            177     },
            178     {
            179       "description": "",
            180       "display_name": "Point Cloud Segmentation",
            181       "id": "addc11b6-af72-47ca-bc3d-69b2f4e15d10",
            182       "image_display_url": "",
            183       "name": "point-cloud-segmentation",
            184       "title": "Point Cloud Segmentation"
            185     },
            186     {
            187       "description": "",
            188       "display_name": "Point Clouds",
            189       "id": "71e868cb-bd30-4079-999e-4461dde9f071",
            190       "image_display_url": "",
            191       "name": "point-clouds",
            192       "title": "Point Clouds"
            193     },
            194     {
            195       "description": "",
            196       "display_name": "Scene Segmentation",
            197       "id": "69266901-10c5-4367-b59e-e438f0dd6e34",
            198       "image_display_url": "",
            199       "name": "scene-segmentation",
            200       "title": "Scene Segmentation"
            201     },
            202     {
            203       "description": "",
            204       "display_name": "Semantic Segmentation",
            205       "id": "8c3f2eee-f5f9-464d-9c0a-1a5e7a925c0e",
            206       "image_display_url": "",
            207       "name": "semantic-segmentation",
            208       "title": "Semantic Segmentation"
            209     }
            210   ],
            40   "id": "13509f84-5003-41e3-8307-6866cba373e1", 211   "id": "13509f84-5003-41e3-8307-6866cba373e1",
            41   "isopen": false, 212   "isopen": false,
            n 42   "landing_page": "", n 213   "landing_page": "https://s3dis.stanford.edu/",
            43   "license_title": null, 214   "license_title": null,
            44   "link_orkg": "", 215   "link_orkg": "",
            45   "metadata_created": "2024-11-25T14:45:27.574102", 216   "metadata_created": "2024-11-25T14:45:27.574102",
            n 46   "metadata_modified": "2024-11-25T14:45:27.933039", n 217   "metadata_modified": "2024-12-02T17:50:49.051955",
            47   "name": "s3dis", 218   "name": "s3dis",
            n 48   "notes": "Stanford Large-Scale 3D Indoor Spaces Dataset (S3DIS)  n 219   "notes": "The dataset used in the paper is a real-world 3D point 
            49 consists of indoor scenes of 272 rooms in six indoor areas, annotated  220 cloud dataset, which is used for 3D shape classification, part 
            50 with 13 semantic categories. It is used for semantic segmentation  221 segmentation, and shape retrieval tasks.",
            51 tasks.", 
            52   "num_resources": 1, 222   "num_resources": 0,
            53   "num_tags": 0, 223   "num_tags": 39,
            54   "organization": { 224   "organization": {
            55     "approval_status": "approved", 225     "approval_status": "approved",
            56     "created": "2024-11-25T12:11:38.292601", 226     "created": "2024-11-25T12:11:38.292601",
            57     "description": "", 227     "description": "",
            58     "id": "079d46db-32df-4b48-91f3-0a8bc8f69559", 228     "id": "079d46db-32df-4b48-91f3-0a8bc8f69559",
            59     "image_url": "", 229     "image_url": "",
            60     "is_organization": true, 230     "is_organization": true,
            61     "name": "no-organization", 231     "name": "no-organization",
            62     "state": "active", 232     "state": "active",
            63     "title": "No Organization", 233     "title": "No Organization",
            64     "type": "organization" 234     "type": "organization"
            65   }, 235   },
            66   "owner_org": "079d46db-32df-4b48-91f3-0a8bc8f69559", 236   "owner_org": "079d46db-32df-4b48-91f3-0a8bc8f69559",
            67   "private": false, 237   "private": false,
            68   "relationships_as_object": [], 238   "relationships_as_object": [],
            69   "relationships_as_subject": [], 239   "relationships_as_subject": [],
            n 70   "resources": [ n 240   "resources": [],
            71     { 241   "services_used_list": "",
            72       "cache_last_updated": null, 
            73       "cache_url": null, 
            74       "created": "2024-11-25T15:30:26", 
            75       "data": [ 
            76         "dcterms:title", 
            77         "dcterms:accessRights", 
            78         "dcterms:creator", 
            79         "dcterms:description", 
            80         "dcterms:issued", 
            81         "dcterms:language", 
            82         "dcterms:identifier", 
            83         "dcat:theme", 
            84         "dcterms:type", 
            85         "dcat:keyword", 
            86         "dcat:landingPage", 
            87         "dcterms:hasVersion", 
            88         "dcterms:format", 
            89         "mls:task" 
            90       ], 
            91       "description": "The json representation of the dataset with its  
            92 distributions based on DCAT.", 
            93       "format": "JSON", 
            94       "hash": "", 
            95       "id": "808e527b-8b08-4da2-911a-f13568387d37", 
            96       "last_modified": "2024-11-25T14:45:27.925569", 
            97       "metadata_modified": "2024-11-25T14:45:27.936112", 
            98       "mimetype": "application/json", 
            99       "mimetype_inner": null, 
            100       "name": "Original Metadata", 
            101       "package_id": "13509f84-5003-41e3-8307-6866cba373e1", 
            102       "position": 0, 
            103       "resource_type": null, 
            104       "size": 778, 
            105       "state": "active", 242   "state": "active",
            106       "url":  243   "tags": [
            107 resource/808e527b-8b08-4da2-911a-f13568387d37/download/metadata.json", 244     {
            108       "url_type": "upload" 245       "display_name": "3D",
            246       "id": "c98a3ca2-e5c9-4173-93fb-420e0b48e9d8",
            247       "name": "3D",
            248       "state": "active",
            249       "vocabulary_id": null
            250     },
            251     {
            252       "display_name": "3D Indoor Scene Understanding",
            253       "id": "cb581899-5746-460a-87a7-f7c25d15a40e",
            254       "name": "3D Indoor Scene Understanding",
            255       "state": "active",
            256       "vocabulary_id": null
            257     },
            258     {
            259       "display_name": "3D Indoor Spaces",
            260       "id": "d07b9522-61c6-4ce5-bbc6-fa7aaea066b8",
            261       "name": "3D Indoor Spaces",
            262       "state": "active",
            263       "vocabulary_id": null
            264     },
            265     {
            266       "display_name": "3D Instance Segmentation",
            267       "id": "4b4284eb-d2b9-44f3-bd2f-32c104179769",
            268       "name": "3D Instance Segmentation",
            269       "state": "active",
            270       "vocabulary_id": null
            271     },
            272     {
            273       "display_name": "3D Object Detection",
            274       "id": "fb2b0721-3175-4d9d-9481-9032ddee2dfa",
            275       "name": "3D Object Detection",
            276       "state": "active",
            277       "vocabulary_id": null
            278     },
            279     {
            280       "display_name": "3D Point Clouds",
            281       "id": "55c31270-45cd-40ec-8846-a614fb63a2a8",
            282       "name": "3D Point Clouds",
            283       "state": "active",
            284       "vocabulary_id": null
            285     },
            286     {
            287       "display_name": "3D Scene Understanding",
            288       "id": "9cfd0d9e-9ee3-4a0f-9007-8dc737ac6c90",
            289       "name": "3D Scene Understanding",
            290       "state": "active",
            291       "vocabulary_id": null
            292     },
            293     {
            294       "display_name": "3D Segmentation",
            295       "id": "4a9a6fdc-66c5-4d47-bdf3-f7c1d1fc51be",
            296       "name": "3D Segmentation",
            297       "state": "active",
            298       "vocabulary_id": null
            299     },
            300     {
            301       "display_name": "3D indoor scenes",
            302       "id": "f71aa6bd-f05e-4af9-837a-3913fb607730",
            303       "name": "3D indoor scenes",
            304       "state": "active",
            305       "vocabulary_id": null
            306     },
            307     {
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            310       "name": "3D point cloud",
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            313     },
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            317       "name": "3D point clouds",
            318       "state": "active",
            319       "vocabulary_id": null
            320     },
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            324       "name": "3D segmentation",
            325       "state": "active",
            326       "vocabulary_id": null
            327     },
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            330       "id": "cc82e2f5-be18-4e27-9bd8-0cb307b8a455",
            331       "name": "Classification",
            332       "state": "active",
            333       "vocabulary_id": null
            334     },
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            337       "id": "77b96eda-8a43-406f-9c54-d87b14f3f63e",
            338       "name": "Computer Vision",
            339       "state": "active",
            340       "vocabulary_id": null
            341     },
            342     {
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            344       "id": "ad3b4249-bcd5-49f2-98f7-974eaadcb46f",
            345       "name": "Gaussian Processes",
            346       "state": "active",
            347       "vocabulary_id": null
            348     },
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            352       "name": "Indoor Scene Understanding",
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            354       "vocabulary_id": null
            355     },
            356     {
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            359       "name": "Indoor Scenes",
            360       "state": "active",
            361       "vocabulary_id": null
            362     },
            363     {
            364       "display_name": "Instance Segmentation",
            365       "id": "b58d8dfe-1216-401d-8a2a-ceb09e07a013",
            366       "name": "Instance Segmentation",
            367       "state": "active",
            368       "vocabulary_id": null
            369     },
            370     {
            371       "display_name": "Object Classi\ufb01cation",
            372       "id": "fa16e756-2685-4dc4-8d0b-42f1f0d7676b",
            373       "name": "Object Classi\ufb01cation",
            374       "state": "active",
            375       "vocabulary_id": null
            376     },
            377     {
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            380       "name": "Point Cloud",
            381       "state": "active",
            382       "vocabulary_id": null
            383     },
            384     {
            385       "display_name": "Point Cloud Instance Segmentation",
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            387       "name": "Point Cloud Instance Segmentation",
            388       "state": "active",
            389       "vocabulary_id": null
            390     },
            391     {
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            394       "name": "Point Clouds",
            395       "state": "active",
            396       "vocabulary_id": null
            397     },
            398     {
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            402       "state": "active",
            403       "vocabulary_id": null
            404     },
            405     {
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            408       "name": "Scene Understanding",
            409       "state": "active",
            410       "vocabulary_id": null
            411     },
            412     {
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            414       "id": "afba543e-f91f-4800-834e-77535c9e8dac",
            415       "name": "Segmentation",
            416       "state": "active",
            417       "vocabulary_id": null
            418     },
            419     {
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            422       "name": "Semantic Segmentation",
            423       "state": "active",
            424       "vocabulary_id": null
            425     },
            426     {
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            428       "id": "30b96a8e-ded8-465e-9a77-e4163624d903",
            429       "name": "classification",
            430       "state": "active",
            431       "vocabulary_id": null
            432     },
            433     {
            434       "display_name": "convexity-based segmentation",
            435       "id": "e684a0f9-f52b-4539-8524-74b72a1b5115",
            436       "name": "convexity-based segmentation",
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            438       "vocabulary_id": null
            439     },
            440     {
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            457       "name": "indoor scene understanding",
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            459       "vocabulary_id": null
            460     },
            461     {
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            473       "vocabulary_id": null
            474     },
            475     {
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            478       "name": "point cloud",
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            480       "vocabulary_id": null
            481     },
            482     {
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            487       "vocabulary_id": null
            488     },
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            492       "name": "scene segmentation",
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            499       "name": "scene understanding",
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            501       "vocabulary_id": null
            502     },
            503     {
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            506       "name": "semantic labels",
            507       "state": "active",
            508       "vocabulary_id": null
            509     },
            510     {
            511       "display_name": "semantic segmentation",
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            513       "name": "semantic segmentation",
            514       "state": "active",
            515       "vocabulary_id": null
            109     } 516     }
            110   ], 517   ],
            t 111   "services_used_list": "", t 
            112   "state": "active", 
            113   "tags": [], 
            114   "title": "S3DIS", 518   "title": "S3DIS",
            115   "type": "dataset", 519   "type": "dataset",
            116   "version": "" 520   "version": ""
            117 } 521 }