A vocabulary for the modelling of image search microservices

José Ignacio Fernández-Villamor, Carlos A. Iglesias & Mercedes Garijo (2010). A vocabulary for the modelling of image search microservices. In Pericles Loucopoulos & Leszek Maciaszek (editors), Proceedings of the Fifth International Conference on Evaluation of Novel Approaches to Software Engineering, pages 199-206. Piraeus, Greece : SciPress.

In order to take advantage of the services that are available on the Web, several approaches that allow describing services have been proposed. With them, developers can publish service descriptions, allowing services to be automatically executed and composed. However, in most cases, the service description task is not carried out, partly because it is a time-consuming task. This has caused initiatives such as WSMO lite, SA-REST, hRESTS or Microservices, that try to reduce complexity in services, to appear. Also, an increasing number of web applications have followed the Linked Data initiative and publish information that is machine processable thanks to Semantic Web technologies such as RDF. However, sometimes direct access to information requires the usage of search forms and, in other cases, spidering techniques such as focused crawling in order to aggregate and filter data. Automatic execution of search services would improve access to information in the web by enabling agents to automatically aggregate, filter and directly access data. In this paper, it is presented how the Microservices framework can provide a feature-based vocabulary for the description of image search services. Microservices framework is a lightweight service description framework that take feature-oriented and aspect-oriented programming ideas to service description. The article illustrates how this vocabulary can characterise a set of popular search services, such as Google Images or Flickr. In addition, the article describes how this vocabulary can be used for the development of new services, such as a metasearcher that aggregates results from various search services.