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  "access_rights": "",
            
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  "accrualPeriodicity": "",
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  "accrualPeriodicity": "",
            
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  "author": "Philipp D. Rohde",
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  "author": "Philipp D. Rohde",
            
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  "author_email": "",
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  "author_email": "",
            
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  "citation": [],
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  "citation": [],
            
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  "creator_user_id": "b6005781-6560-475f-aeea-d834a83f0d8f",
            
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  "defined_in": "https://doi.org/10.1016/j.inffus.2024.102557",
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  "defined_in": "https://doi.org/10.1016/j.inffus.2024.102557",
            
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  "doi": "10.57702/4qixxfy9",
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  "doi": "10.57702/4qixxfy9",
            
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  "doi_date_published": null,
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  "doi_date_published": null,
            
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  "doi_publisher": "TIB",
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  "doi_publisher": "TIB",
            
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  "doi_status": false,
            
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  "domain": "https://ldm.kisski.de",
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  "domain": "https://ldm.kisski.de",
            
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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": "Antonio Jesus Diaz-Honrubia",
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      "extra_author": "Antonio Jesus Diaz-Honrubia",
            
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      "orcid": "0000-0001-5464-0714"
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "Emetis Niazmand",
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      "extra_author": "Emetis Niazmand",
            
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      "orcid": "0000-0001-8194-8079"
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      "orcid": "0000-0001-8194-8079"
            
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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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  "language": "",
            
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  "license_id": "cc-by-sa",
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  "license_id": "cc-by-sa",
            
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  "license_title": "Creative Commons Attribution Share-Alike",
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  "license_title": "Creative Commons Attribution Share-Alike",
            
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  "license_url": "http://www.opendefinition.org/licenses/cc-by-sa",
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  "license_url": "http://www.opendefinition.org/licenses/cc-by-sa",
            
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  "link_orkg": "https://www.orkg.org/orkg/paper/R705607",
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  "link_orkg": "https://www.orkg.org/orkg/paper/R705607",
            
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  "maintainer": "",
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  "maintainer": "",
            
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  "maintainer_email": "",
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  "metadata_created": "2024-09-12T10:50:03.237738",
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  "metadata_modified": "2024-09-12T10:52:26.014027",
            
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  "name": "synthetic-breast-cancer-data",
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  "name": "synthetic-breast-cancer-data",
            
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  "notes": "The data is generated using the [Synthetic Data 
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  "notes": "The data is generated using the [Synthetic Data 
            
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Generator](https://github.com/SDM-TIB/Synthetic-Data-Generator) which 
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Generator](https://github.com/SDM-TIB/Synthetic-Data-Generator) which 
            
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generates process-based breast cancer treatment data following the 
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generates process-based breast cancer treatment data following the 
            
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distribution in a real population of breast cancer patients. The 
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distribution in a real population of breast cancer patients. The 
            
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collection comprises a total of 18 data sets, nine for relational 
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collection comprises a total of 18 data sets, nine for relational 
            
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databases and nine for RDF-based knowledge graphs. For each data 
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databases and nine for RDF-based knowledge graphs. For each data 
            
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format, there are three different sizes of data sets:\r\n\r\n+ _Small_ 
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format, there are three different sizes of data sets:\r\n\r\n+ _Small_ 
            
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models 1,000 patients\r\n+ _Medium-sized_ models 10,000 patients\r\n+ 
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models 1,000 patients\r\n+ _Medium-sized_ models 10,000 patients\r\n+ 
            
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_Large_ models 100,000 patients\r\n\r\nThere are three data sets of 
52
_Large_ models 100,000 patients\r\n\r\nThere are three data sets of 
            
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each size. They differ in the parameter used for the mutation 
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each size. They differ in the parameter used for the mutation 
            
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probability of the data generator. The lower this value is, the closer 
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probability of the data generator. The lower this value is, the closer 
            
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the data is to following the treatment guideline for breast cancer 
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the data is to following the treatment guideline for breast cancer 
            
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patients with an amplified HER2 gene.",
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patients with an amplified HER2 gene.",
            
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  "orcid": "0000-0002-9835-4354",
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  "orcid": "0000-0002-9835-4354",
            
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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 
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Technology, abbreviated TIB, is the national library of the Federal 
            
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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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    "id": "0c5362f5-b99e-41db-8256-3d0d7549bf4d",
            
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    "image_url": 
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    "image_url": 
            
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3conf/ext/tib_tmpl_bootstrap/Resources/Public/images/TIB_Logo_en.png",
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3conf/ext/tib_tmpl_bootstrap/Resources/Public/images/TIB_Logo_en.png",
            
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    "name": "tib",
            
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    "state": "active",
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    "state": "active",
            
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    "title": "TIB",
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    "title": "TIB",
            
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    "type": "organization"
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    "type": "organization"
            
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  },
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  "owner_org": "0c5362f5-b99e-41db-8256-3d0d7549bf4d",
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  "owner_org": "0c5362f5-b99e-41db-8256-3d0d7549bf4d",
            
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  "page": "",
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  "private": false,
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    {
            
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      "created": "2024-09-12T10:52:26.024392",
            
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      "description": "Small dataset of patients respecting the 
            
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treatment guideline.",
            
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      "format": "CSV",
            
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      "mimetype": "text/csv",
            
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      "name": "Patient Clean Small",
            
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      "url": 
            
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      "url_type": "upload"
            
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  "spatial": "",
            
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  "spatial_resolution": "",
            
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  "start_date": "",
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  "start_date": "",
            
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  "state": "draft",
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  "state": "draft",
            
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  "tags": [
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  "tags": [
            
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    {
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    {
            
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      "display_name": "breast cancer",
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      "display_name": "breast cancer",
            
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      "id": "84c0bfaf-6c8a-4d02-b950-b2eaa4486f54",
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      "id": "84c0bfaf-6c8a-4d02-b950-b2eaa4486f54",
            
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      "name": "breast cancer",
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      "name": "breast cancer",
            
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      "state": "active",
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      "state": "active",
            
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      "vocabulary_id": null
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    },
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    },
            
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    {
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    {
            
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      "display_name": "cancer",
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      "display_name": "cancer",
            
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      "id": "11f1523b-6815-4b7a-921e-9ee6087631ac",
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      "id": "11f1523b-6815-4b7a-921e-9ee6087631ac",
            
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      "name": "cancer",
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      "name": "cancer",
            
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      "state": "active",
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      "state": "active",
            
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      "vocabulary_id": null
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      "vocabulary_id": null
            
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    }
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    }
            
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  ],
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  ],
            
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  "temporal_resolution": "",
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  "temporal_resolution": "",
            
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  "title": "Synthetic Breast Cancer Data",
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  "title": "Synthetic Breast Cancer Data",
            
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  "type": "dataset",
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  "type": "dataset",
            
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  "url": "https://github.com/SDM-TIB/Synthetic-Data-Generator",
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  "url": "https://github.com/SDM-TIB/Synthetic-Data-Generator",
            
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  "version": "",
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  "version": "",
            
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  "version_note": ""
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  "version_note": ""
            
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}
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}