APIs and Complex Data Type Task on JSON or XML ____________________________________________________________________ Work to do This exercise is

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APIs and Complex Data Type Task on JSON or XML ____________________________________________________________________ Work to do This exercise is intended to make you design and practice working with APIs and deal with the process of collecting data from APIs using one of the complex data types such as XML and JSON. This will help you better understand the logic of data management and building big datasets. You are not expected to be an expert in building such complex data types here. Rather, you are expected to be able to:

• Understand the logic of designing a relational database after reading the descriptive data dictionary, by reverse engineer the dataset presented in this exercise.

• Program a data collection program using API that collects complex data types such as JSON or XML. You will gain experience with practice if you start learning and engaging with such complex data types.

Therefore, this exercise requires you to write code that will collect data using an API, design a logical relational database to store the data collected, and finally store the dataset collected in the collection of tables designed. An example of an API you can use is Library Cloud API from Harvard Library1 . In the first part of the exercise, you must code and access the API and retrieve any sample of the data this API provides (5 Marks). The second part is to design an ER-D model that is logical and maps to the data collected from the API. Ex. The Library Cloud API retrieves collections of records in the Harvard library with the language of the item and the subject of the item included. A logical design in relational model would be having the language and subject as separate tables and have relations with the items table. Therefore, you must show good understanding of logical design by drawing a suitable ER-D model and building this relational model in any language suitable then store the sample dataset collected (5 Marks).

You Should use this API:

https://library.harvard.edu/services-tools/harvard-library-apis-datasets