Hi Manuela, Personally I’d recommend storing and managing your METS documents as XML and converting to JSON only at the point where you need to process them as JSON. That assumes you have the option of storing as XML. If your database is built mainly or only for JSON, then you’ll have to do a one-time conversion from XML to JSON. In any case, as has already been said it’s strictly a matter of conversion, and there are lots of tools that can take XML and output generic JSON in a lossless way. Whether you would then need to have another process to go from JSON to JSON-LD I don’t know; that’s outside my knowledge.
Hope this helps, Greg Gregory Murray Director of Digital Initiatives Wright Library Princeton Theological Seminary From: Code for Libraries <CODE4LIB@LISTS.CLIR.ORG> on behalf of parker, anson D (adp6j) <000000d5611add13-dmarc-requ...@lists.clir.org> Date: Tuesday, August 1, 2023 at 10:55 AM To: CODE4LIB@LISTS.CLIR.ORG <CODE4LIB@LISTS.CLIR.ORG> Subject: Re: [CODE4LIB] METS in JSON-LD? [You don't often get email from 000000d5611add13-dmarc-requ...@lists.clir.org. Learn why this is important at https://aka.ms/LearnAboutSenderIdentification ] might be worth spending a minute on some AI bots to play with this at the end of the day it's an XML->JSON project and there are a bunch of tools that will streamline that for instance here's a dumbed down python script with a streamlit interface i got out of claude.ai in a couple of queries import streamlit as st import xml.etree.ElementTree as ET import json st.title('METS to JSON-LD Converter') uploaded_file = st.file_uploader('Choose a METS XML file', type=['xml']) if uploaded_file is not None: # Load METS file tree = ET.parse(uploaded_file) root = tree.getroot() # JSON-LD context context = { '@vocab': 'https://nam10.safelinks.protection.outlook.com/?url=http%3A%2F%2Fschema.org%2F&data=05%7C01%7Cgregory.murray%40PTSEM.EDU%7Cab618e3e600b4bc6890108db929f6228%7C6fb1672fa768436d88c81585060baf28%7C0%7C0%7C638264985520735577%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=TYxQc%2BBh0kJYYb2Wy7IvpJjJqiiabnlpdsSVhFViWvw%3D&reserved=0<http://schema.org/>', 'dc': 'https://nam10.safelinks.protection.outlook.com/?url=http%3A%2F%2Fpurl.org%2Fdc%2Felements%2F1.1%2F&data=05%7C01%7Cgregory.murray%40PTSEM.EDU%7Cab618e3e600b4bc6890108db929f6228%7C6fb1672fa768436d88c81585060baf28%7C0%7C0%7C638264985520735577%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=pbxUZAJT2mBujKQJOHiPAOrZZTKf7AqKW8KcRUtdmZ4%3D&reserved=0<http://purl.org/dc/elements/1.1/>' } jsonld = {'@context': context} jsonld['metadata'] = [] # Parse METS and generate JSON-LD for dmdSec in root.iter('dmdSec'): # Extract metadata md = { 'name': dmdSec.find('mdWrap/xmlData/mods/titleInfo/title').text, 'author': [{'@type': 'Person', 'name': namePart.text} for namePart in dmdSec.find('mdWrap/xmlData/mods/name')], 'datePublished': dmdSec.find('mdWrap/xmlData/mods/originInfo/dateIssued').text, 'publisher': {'@type': 'Organization', 'name': dmdSec.find('mdWrap/xmlData/mods/originInfo/publisher').text}, 'genre': dmdSec.find('mdWrap/xmlData/mods/genre').text, 'description': dmdSec.find('mdWrap/xmlData/mods/abstract').text } jsonld['metadata'].append(md) # Output JSON-LD file for download json_txt = json.dumps(jsonld, indent=4) st.download_button('Download JSON-LD', json_txt, 'metadata.jsonld') ________________________________________ From: Code for Libraries <CODE4LIB@LISTS.CLIR.ORG> on behalf of Manuela Pallotto Strickland <000001243159acc2-dmarc-requ...@lists.clir.org> Sent: Tuesday, August 1, 2023 10:47 AM To: CODE4LIB@LISTS.CLIR.ORG Subject: [CODE4LIB] METS in JSON-LD? Hello, I am posting this question on a couple of lists, so sincere apologies to those who might see it twice (or thrice). Does anyone know of any work that has been/is being/will be done on 'a' METS JSON-LD serialization? Any relevant info or comment in this re will be very much appreciated. Thank you! 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