{ "version": "https://jsonfeed.org/version/1.1", "title": "chem-bla-ics", "description": "Chemblaics (pronounced chem-bla-ics) is the science that uses open science and computers to solve problems in chemistry, biochemistry and related fields.", "home_page_url": "https://chem-bla-ics.linkedchemistry.info/", "feed_url": "https://chem-bla-ics.linkedchemistry.info/2013/10/30/programming-in-life-sciences-10.json", "icon": "https://chem-bla-ics.linkedchemistry.info/assets/images/chem-bla-ics_logo.png", "language": "en", "authors": [ { "name": "Egon Willighagen", "url": "https://orcid.org/0000-0001-7542-0286", "_orcid": "0000-0001-7542-0286" } ], "items": [ { "id": "https://doi.org/10.59350/xdnrb-rrc91", "url": "https://chem-bla-ics.linkedchemistry.info/2013/10/30/programming-in-life-sciences-10.html", "title": "Programming in the Life Sciences #10: JavaScript Object Notation (JSON)", "content_html": "

As said, JSON is the format we will use as serialization format\nfor answers given by the Open PHACTS LDA. The API actually supports\nXML, RDF, HTML, and TSV too, but I think JSON is a good balance between expressiveness and compactness.\nMoreover, and perhaps a much better argument, JSON works very well in a JavaScript environment: it is\nvery easy to convert the serialization into a data model:

\n\n
var jsonData = JSON.parse(jsonString);\n
\n\n

Now, we previously covered maps. Maps have keys and values: the keys unlock a particular value.\nFor example, take this JavaScript:

\n\n
var map = { \"key\": \"value\", \"key2\": \"value2\" };\n
\n\n

We define here a key-value object, and we can access the two values with the two keys:

\n\n
map[\"key2\"]; // == value2\n
\n\n

These examples are JavaScript source code. Not a string. The content of the map variable is a data\nstructure. But when we communicate with a web service, we need a (string) serialization of the data\nmodel, because we cannot send around memory pointers (which a variable is) because they are only\nvalid on a single machine.

\n\n

This is where the JSON format comes in. We can convert the content of the above map variable into a\nstring representation with this code:

\n\n
var mapStringified = JSON.stringify(map);\n
\n\n

which gives us the following output:

\n\n
{\"key\":\"value\",\"key2\":\"value2\"}\n
\n\n

This string looks an awful lot like the JavaScript code we wrote earlier.

\n\n

And, likewise we can convert the JSON string back into a JavaScript data model again, with:

\n\n
var mapAgain = JSON.parse(mapStringified);\n
\n\n

Now, I did warn you earlier that values can be lists and maps itself again, so consider this\nJSON example from Wikipedia:

\n\n
{\n    \"id\": 1,\n    \"name\": \"Foo\",\n    \"price\": 123,\n    \"tags\": [ \"Bar\", \"Eek\" ],\n    \"stock\": {\n        \"warehouse\": 300,\n        \"retail\": 20\n    }\n}\n
\n\n

Here we see that the value behind the stock key is another map, and the value behind the tags\nkey is a list. This creates a quite flexible serialization format, which is happily used by\nOpen PHACTS. (And for the semantic web readers, yes, we can make JSON more semantic. The Open\nPHACTS LDA supports a “rdfjson” format.)

", "summary": "As said, JSON is the format we will use as serialization format for answers given by the Open PHACTS LDA. The API actually supports XML, RDF, HTML, and TSV too, but I think JSON is a good balance between expressiveness and compactness. Moreover, and perhaps a much better argument, JSON works very well in a JavaScript environment: it is very easy to convert the serialization into a data model:", "date_published": "2013-10-30T00:10:00+00:00", "date_modified": "2025-02-15T00:00:00+00:00", "tags": ["pra3006","json"], "authors": [ { "name": "Egon Willighagen", "url": "https://orcid.org/0000-0001-7542-0286" } ] } ] }