Eleven quick tips to build a usable REST API for life sciences
2018
In recent years, technological advances have greatly expanded the range of data types generated by life sciences researchers. These span domains such as molecular structures, nucleotide and protein sequences, metabolomics, and chemogenomics, resulting in hundreds of public resources holding diverse data sets for reuse in multiple formats [1]. Most resources focus on a specific data type, yet their value for researchers is enhanced once cross-referenced and combined with expert annotation and knowledge. Cross-referencing has increasingly been achieved by implementing website application programming interfaces (web APIs), providing programming-language−agnostic methods to access online resources. Web APIs enable dynamic data exchange between resources, augment websites with additional data, and can provide access to large data sets. Web APIs also enhance adherence to FAIR data principles by making data Findable, Accessible, Interoperable, and Reusable [2], thus increasing the value of those resources.
Representational state transfer (REST) [3] is a popular method for providing interoperability between a client and server [4] using the hypertext transfer protocol (HTTP), the same building block as the world wide web, [5] and a common exchange format, e.g., JavaScript Object Notation (JSON) [6]. REST APIs are considered easier to develop than previous web-service standards, e.g., Simple Object Access Protocol (SOAP). However, REST specifies a set of requirements that any implementation of a REST API must address. Although well-known resources such as the World Wide Web Consortium (W3C) (https://www.w3.org) and the Internet Engineering Task Force (IETF) (https://www.ietf.org/) provide guidance on how to implement such a service, they can be difficult to understand and may have limited documentation. We present here 11 quick tips for creating and maintaining REST web APIs that were developed while implementing various web APIs (https://www.ebi.ac.uk/services) for European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI)’s data resources.
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