Since these two data types can be visualized as 3D models, I need to be able to visualize the transformed data at the end of the process. During all these processes, there should be no loss of geometric and semantic information in the data. After that, the conversion process needs to be done based on these mappings. For this, first of all, IFC data should be defined ontologically and then logical mappings should be made between IFC-CityGML data. But this needs to be done using semantic web. As for the conversion part, I want to convert a data I have from ifc to citygml using Python. However, IFC may also contain geographic coordinates. CityGML, on the other hand, is GML-based, that is, it contains geographical definitions. This data is based on IFC Express and encoded with XML. is a structure description data type used in applications, while CityGML focuses more on geographic details and describes both structures and their geographic relationship to other structures. įrom json2xml.utils import readfromurl, readfromstring, readfromjsonlĭata = readfromjson("/content/HL7DUMMY.IFC, construction architecture etc. I will Then Use The Following Snippets To Convert The Json Format To XML Format. Then I Will Call The Data Using This snippet, It Will Shows The Content Of The JSON file Below. I Will Then Open The Mentioned File Using The Following Code Snippet In My Case, I Named My File HL7DUMMY.Json Where It Contains Medical Data. Now You Are Ready To Upload Your File Either To Google Drive Then Import It to Goggle Colaboratory Or you Can Upload It Directly To Google Colaboratory. In This Google Colaboratory Notebook I will Show You How to Convert JSON file To XML Using Python Programming.įirstly We Need to Install Some Dependencies Dealing With Different Healthcare Systems In the Field of Health Informatics Usually Mandate Some Integration Skills That Enables You To Convert Different File Forms Interchangeably.
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