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  "access_rights": "Public",
            
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  "accrualPeriodicity": "",
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  "accrualPeriodicity": "",
            
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  "author": "Disha Purohit",
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  "author": "Disha Purohit",
            
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  "author_email": "disha.purohit@tib.eu",
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  "author_email": "disha.purohit@tib.eu",
            
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  "citation": [],
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  "citation": [],
            
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  "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700",
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  "defined_in": "",
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  "defined_in": "",
            
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  "doi": "10.57702/w3ghyku2",
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  "doi": "10.57702/w3ghyku2",
            
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  "doi_date_published": "2024-09-14",
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  "doi_date_published": "2024-09-14",
            
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  "doi_publisher": "TIB",
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  "doi_publisher": "TIB",
            
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  "doi_status": true,
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  "doi_status": true,
            
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  "domain": "https://ldm.kisski.de",
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  "domain": "https://ldm.kisski.de",
            
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  "end_date": "",
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  "extra_authors": [
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  "extra_authors": [
            
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    {
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    {
            
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      "extra_author": "Yashrajsinh Chudasama",
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      "extra_author": "Yashrajsinh Chudasama",
            
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      "orcid": "0000-0003-3422-366X"
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      "orcid": "0000-0003-3422-366X"
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "Maria Torrente",
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      "extra_author": "Maria Torrente",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "Maria-Esther Vidal",
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      "extra_author": "Maria-Esther Vidal",
            
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      "orcid": "0000-0003-1160-8727"
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      "orcid": "0000-0003-1160-8727"
            
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    }
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    }
            
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  ],
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  "extras": [
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  "groups": [
            
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    {
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    {
            
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      "description": "",
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      "description": "",
            
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      "display_name": "Medicine",
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      "display_name": "Medicine",
            
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      "name": "medicine",
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      "name": "medicine",
            
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      "title": "Medicine"
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      "title": "Medicine"
            
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    }
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    }
            
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  ],
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  ],
            
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  "id": "69043d59-72e2-4714-b914-dfced3f87b9a",
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  "id": "69043d59-72e2-4714-b914-dfced3f87b9a",
            
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  "isopen": true,
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  "isopen": true,
            
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  "landing_page": "",
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  "landing_page": "",
            
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  "language": "English",
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  "language": "English",
            
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  "license_id": "cc-by",
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  "license_id": "cc-by",
            
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  "license_title": "Creative Commons Attribution",
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  "license_title": "Creative Commons Attribution",
            
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  "license_url": "http://www.opendefinition.org/licenses/cc-by",
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  "license_url": "http://www.opendefinition.org/licenses/cc-by",
            
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  "link_orkg": "",
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  "link_orkg": "",
            
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  "maintainer": "Disha Purohit",
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  "maintainer": "Disha Purohit",
            
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  "maintainer_email": "disha.purohit@tib.eu",
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  "maintainer_email": "disha.purohit@tib.eu",
            
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  "metadata_created": "2024-09-14T12:01:01.489943",
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  "metadata_created": "2024-09-14T12:01:01.489943",
            
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  "metadata_modified": "2024-10-01T15:30:55.493842",
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  "metadata_modified": "2024-10-01T15:33:04.119000",
            
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  "name": "vise-kg",
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  "name": "vise-kg",
            
64
  "notes": "VISE: Validated and Invalidated Symbolic Explanations for 
64
  "notes": "VISE: Validated and Invalidated Symbolic Explanations for 
            
65
Knowledge Graph Integrity\r\n\r\nThis collection includes all the data 
65
Knowledge Graph Integrity\r\n\r\nThis collection includes all the data 
            
66
necessary to reproduce the results from the experimental evaluation of 
66
necessary to reproduce the results from the experimental evaluation of 
            
67
VISE at EXPLIMED @ ECAI'24.\r\nThe data is an anonymized synthetic 
67
VISE at EXPLIMED @ ECAI'24.\r\nThe data is an anonymized synthetic 
            
68
lung cancer benchmark that comprises clinical data extracted from 
68
lung cancer benchmark that comprises clinical data extracted from 
            
69
heterogeneous sources such as publications, clinical trials, and 
69
heterogeneous sources such as publications, clinical trials, and 
            
70
clinical records representing patients diagnosed with lung cancer. We 
70
clinical records representing patients diagnosed with lung cancer. We 
            
71
evaluate the VISE approach on three anonymized Lung Cancer KGs: 
71
evaluate the VISE approach on three anonymized Lung Cancer KGs: 
            
72
LC-\ud835\udc3e\ud835\udc3a1, LC-\ud835\udc3e\ud835\udc3a2,and 
72
LC-\ud835\udc3e\ud835\udc3a1, LC-\ud835\udc3e\ud835\udc3a2,and 
            
73
LC-\ud835\udc3e\ud835\udc3a3\r\n\r\nThe collection comprises nine data 
73
LC-\ud835\udc3e\ud835\udc3a3\r\n\r\nThe collection comprises nine data 
            
74
sets of three different sizes:\r\n\r\n- LC Knowledge Graph 1 (LC-KG1) 
74
sets of three different sizes:\r\n\r\n- LC Knowledge Graph 1 (LC-KG1) 
            
75
models 29 lung cancer patients\r\n- LC Knowledge Graph 2 (LC-KG2) 
75
models 29 lung cancer patients\r\n- LC Knowledge Graph 2 (LC-KG2) 
            
76
models 203 lung cancer patients\r\n- LC Knowledge Graph 3 (LC-KG3) 
76
models 203 lung cancer patients\r\n- LC Knowledge Graph 3 (LC-KG3) 
            
77
models 319 lung cancer patients\r\n\r\nThree distinct KGs of different 
77
models 319 lung cancer patients\r\n\r\nThree distinct KGs of different 
            
78
sizes are available, each with its own characteristics. \r\n\r\n- 
78
sizes are available, each with its own characteristics. \r\n\r\n- 
            
n
79
\"Original KG\": The original KG comprises of anonymized lung cancer 
n
79
\"Original KG\": The original KG comprises anonymized lung cancer 
            
80
patients with different medical characteristics. \r\n- \"Enriched 
80
patients with different medical characteristics. \r\n- \"Enriched 
            
n
81
KG\": Utilizes an inductive learnng technique of KG completion through 
n
81
KG\": Utilizes an inductive learning technique of KG completion 
            
82
self-supervised symbolic learning over the original KG. \r\n- 
82
through self-supervised symbolic learning over the original KG. \r\n- 
            
83
\"Transformed KG\": Denotes a transformation of the KG depending on 
83
\"Transformed KG\": Denotes a transformation of the KG depending on 
            
84
SHACL shapes evaluated across the enriched KGs. This procedure is used 
84
SHACL shapes evaluated across the enriched KGs. This procedure is used 
            
85
to determine the validity of the data. \r\n\r\nVISE is also evaluated 
85
to determine the validity of the data. \r\n\r\nVISE is also evaluated 
            
86
with KGs comprising 1242 lung cancer patients (LungCancer-OriginalKG, 
86
with KGs comprising 1242 lung cancer patients (LungCancer-OriginalKG, 
            
87
LungCancer-EnrichedKG, and LungCancer-TransformedKG).\r\n\r\nOur 
87
LungCancer-EnrichedKG, and LungCancer-TransformedKG).\r\n\r\nOur 
            
88
experimental results demonstrate the effectiveness of this hybrid 
88
experimental results demonstrate the effectiveness of this hybrid 
            
89
strategy, which combines the strengths of symbolic, numerical, and 
89
strategy, which combines the strengths of symbolic, numerical, and 
            
t
90
constraint validation\r\nparadigms. VISE implementation is publicly 
t
90
constraint validation\r\nparadigms.",
            
91
accessible on GitHub (https://github.com/SDM-TIB/VISE).",

            
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  "orcid": "0000-0002-1442-335X",
            
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  "organization": {
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  "organization": {
            
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    "approval_status": "approved",
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    "approval_status": "approved",
            
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    "created": "2017-11-23T17:30:37.757128",
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    "created": "2017-11-23T17:30:37.757128",
            
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    "description": "The German National Library of Science and 
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    "description": "The German National Library of Science and 
            
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Technology, abbreviated TIB, is the national library of the Federal 
98
Technology, abbreviated TIB, is the national library of the Federal 
            
100
Republic of Germany for all fields of engineering, technology, and the 
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Republic of Germany for all fields of engineering, technology, and the 
            
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natural sciences.",
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natural sciences.",
            
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    "image_url": 
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    "title": "TIB",
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    {
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      "auto_update": "No",
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      "created": "2024-09-14T12:01:25.289289",
            
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      "description": "Anonymized LungCancer-OriginalKG",
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      "description": "Anonymized LungCancer-OriginalKG",
            
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      "format": "NT",
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      "format": "NT",
            
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      "hash": "",
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      "hash": "",
            
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      "id": "0a16870f-8c11-414e-8e40-1ce2d7f8c0a8",
            
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      "language": "English",
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      "language": "English",
            
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      "last_modified": "2024-09-14T12:01:25.271055",
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      "name": "LungCancer-OriginalKG",
            
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      "size": 2350495,
            
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      "state": "active",
            
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      "url": 
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      "url": 
            
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16870f-8c11-414e-8e40-1ce2d7f8c0a8/download/lungcancer-originalkg.nt",
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16870f-8c11-414e-8e40-1ce2d7f8c0a8/download/lungcancer-originalkg.nt",
            
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      "url_type": "upload"
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      "url_type": "upload"
            
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    },
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    },
            
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    {
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    {
            
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      "auto_update": "No",
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      "auto_update": "No",
            
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      "auto_update_last_update": "",
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      "auto_update_last_update": "",
            
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      "created": "2024-09-14T12:02:06.217600",
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      "created": "2024-09-14T12:02:06.217600",
            
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      "description": "Anonymized LungCancer-TransformedKG ",
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      "description": "Anonymized LungCancer-TransformedKG ",
            
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      "format": "",
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      "format": "",
            
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      "hash": "",
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      "hash": "",
            
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      "language": "",
            
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      "last_modified": "2024-09-14T12:02:06.200894",
            
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      "media": "",
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      "media": "",
            
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      "name": "LungCancer-TransformedKG",
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      "name": "LungCancer-TransformedKG",
            
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      "package_id": "69043d59-72e2-4714-b914-dfced3f87b9a",
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      "state": "active",
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      "state": "active",
            
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      "url": 
            
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      "url_type": "upload"
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    },
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    },
            
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    {
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    {
            
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      "auto_update": "No",
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      "auto_update": "No",
            
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      "created": "2024-09-14T12:02:33.213210",
            
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      "description": "Anonymized LungCancer-EnrichedKG",
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      "description": "Anonymized LungCancer-EnrichedKG",
            
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      "format": "",
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      "format": "",
            
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      "media": "",
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