A Linked Data Perspective for Collaboration in Mashup Development

Web mashup is becoming an approach more and more popular for developing Web applications both for general and enterprise purposes. Mashup development is fueled by Web sites, as Programmable Web and Mashape, offering large, ever growing, catalogues of software components accessible through Web APIs. Developing Web mashup applications requires specialized knowledge about Web APIs, technologies and the way to combine them in a meaningful way. This kind of knowledge is often available but distributed among different experts. In this paper we introduce the LINKSMAN (LINKed data Supported MAshup collaboratioN) approach for expert search in enterprise mashup development. The approach is based on integrating knowledge both internal and external to enterprises. The result is then published as linked data set. We show how typical collaboration patterns among mashup developers can be formalized and implemented on this linked data set to support expert search. A prototype application is also described.