I’m trying to parse academic publication data from Open Academic Graph, which stores the data in JSON format, but am running into an issue with parsing the below sample JSON they provide on the website because it is nested. I’m fairly new to working with JSON and could use some help. Any tips for how to parse it?
using JSONTables, DataFrames, CSV, JSON3
js_string = "{
\"id\":\"53e9ab9eb7602d970354a97e\",
\"title\":\"Data mining: concepts and techniques\",
\"authors\":[
{
\"name\":\"jiawei han\",
\"org\":\"department of computer science university of illinois at urbana champaign\"
},
{
\"name\":\"micheline kamber\",
\"org\":\"department of computer science university of illinois at urbana champaign\"
},
{
\"name\":\"jian pei\",
\"org\":\"department of computer science university of illinois at urbana champaign\"
}
],
\"year\":2000,
\"keywords\":[
\"data mining\",
\"structured data\",
\"world wide web\",
\"social network\",
\"relational data\"
],
\"fos\":[
\"relational database\",
\"data model\",
\"social network\"
],
\"n_citation\":29790,
\"references\":[
\"53e99ef4b7602d97027c2346\",
\"53e9aa23b7602d970338fb5e\",
\"53e99cf5b7602d97025aac75\"
],
\"doc_type\":\"book\",
\"lang\":\"en\",
\"publisher\":\"Elsevier\",
\"isbn\":\"1-55860-489-8\",
\"doi\":\"10.4114/ia.v10i29.873\",
\"pdf\":\"//static.aminer.org/upload/pdf/1254/370/239/53e9ab9eb7602d970354a97e.pdf\",
\"url\":[
\"http://dx.doi.org/10.4114/ia.v10i29.873\",
\"http://polar.lsi.uned.es/revista/index.php/ia/article/view/479\"
],
\"abstract\":\"Our ability to generate and collect data has been increasing rapidly. Not only are all of our business, scientific, and government transactions now computerized, but the widespread use of digital cameras, publication tools, and bar codes also generate data. On the collection side, scanned text and image platforms, satellite remote sensing systems, and the World Wide Web have flooded us with a tremendous amount of data. This explosive growth has generated an even more urgent need for new techniques and automated tools that can help us transform this data into useful information and knowledge. Like the first edition, voted the most popular data mining book by KD Nuggets readers, this book explores concepts and techniques for the discovery of patterns hidden in large data sets, focusing on issues relating to their feasibility, usefulness, effectiveness, and scalability. However, since the publication of the first edition, great progress has been made in the development of new data mining methods, systems, and applications. This new edition substantially enhances the first edition, and new chapters have been added to address recent developments on mining complex types of data? including stream data, sequence data, graph structured data, social network data, and multi-relational data.\"
}";
js = JSON3.read(js_string)
jtable = jsontable(js)
The last line returns the error: “ArgumentError: input JSON3.Object must only have JSON3.Array values to be considered a table”