Semantic annotation of Web APIs with SWEET

Recently technology developments in the area of services on the Web are marked by the proliferation of Web applications and APIs. The development and evolution of applications based on Web APIs is, however, hampered by the lack of automation that can be achieved with current technologies. In this paper we present SWEET - Semantic Web sErvices Editing Tool - a lightweight Web application for creating semantic descriptions of Web APIs. SWEET directly supports the creation of mashups by enabling the semantic annotation of Web APIs, thus contributing to the automation of the discovery, composition and invocation service tasks. Furthermore, it enables the development of composite SWS based applications on top of Linked Data

A Semantic Web Annotation Tool for a Web-Based Audio Sequencer

Music and sound have a rich semantic structure which is so clear to the composer and the listener, but that remains mostly hidden to computing machinery. Nevertheless, in recent years, the introduction of software tools for music production have enabled new opportunities for migrating this knowledge from humans to machines. A new generation of these tools may exploit sound samples and semantic information coupling for the creation not only of a musical, but also of a "semantic" composition. In this paper we describe an ontology driven content annotation framework for a web-based audio editing tool. In a supervised approach, during the editing process, the graphical web interface allows the user to annotate any part of the composition with concepts from publicly available ontologies. As a test case, we developed a collaborative web-based audio sequencer that provides users with the functionality to remix the audio samples from the Freesound website and subsequently annotate them. The annotation tool can load any ontology and thus gives users the opportunity to augment the work with annotations on the structure of the composition, the musical materials, and the creator's reasoning and intentions. We believe this approach will provide several novel ways to make not only the final audio product, but also the creative process, first class citizens of the Semantic We

A Framework for Automating the Invocation of Web APIs

Web APIs, characterized by their relative simplicity and their natural suitability for the Web, have become increasingly dominant in the world of services on the Web. Despite their popularity, Web APIs are so heterogeneous in terms of the underlying principles adopted and the means used for publishing them that discovering, understanding and notably invoking Web APIs is nowadays more an art than a science. In this paper, we present our work towards supporting the automated invocation of Web APIs. In particular, we describe a framework that provides a unique entry point for the invocation of most Web APIs that can be found on the Web, by exploiting non-intrusive semantic annotations of HTML pages describing Web APIs in order to capture both their semantics as well as information necessary to carry out their invocation

Semantics-aware planning methodology for automatic web service composition

Service-Oriented Computing (SOC) has been a major research topic in the past years. It is based on the idea of composing distributed applications even in heterogeneous environments by discovering and invoking network-available Web Services to accomplish some complex tasks when no existing service can satisfy the user request. Service-Oriented Architecture (SOA) is a key design principle to facilitate building of these autonomous, platform-independent Web Services. However, in distributed environments, the use of services without considering their underlying semantics, either functional semantics or quality guarantees can negatively affect a composition process by raising intermittent failures or leading to slow performance. More recently, Artificial Intelligence (AI) Planning technologies have been exploited to facilitate the automated composition. But most of the AI planning based algorithms do not scale well when the number of Web Services increases, and there is no guarantee that a solution for a composition problem will be found even if it exists. AI Planning Graph tries to address various limitations in traditional AI planning by providing a unique search space in a directed layered graph. However, the existing AI Planning Graph algorithm only focuses on finding complete solutions without taking account of other services which are not achieving the goals. It will result in the failure of creating such a graph in the case that many services are available, despite most of them being irrelevant to the goals. This dissertation puts forward a concept of building a more intelligent planning mechanism which should be a combination of semantics-aware service selection and a goal-directed planning algorithm. Based on this concept, a new planning system so-called Semantics Enhanced web service Mining (SEwsMining) has been developed. Semantic-aware service selection is achieved by calculating on-demand multi-attributes semantics similarity based on semantic annotations (QWSMO-Lite). The planning algorithm is a substantial revision of the AI GraphPlan algorithm. To reduce the size of planning graph, a bi-directional planning strategy has been developed

Linked data wrapper curation: A platform perspective

131 p.Linked Data Wrappers (LDWs) turn Web APIs into RDF end-points, leveraging the LOD cloud with current data. This potential is frequently undervalued, regarding LDWs as mere by-products of larger endeavors, e.g. developing mashup applications. However, LDWs are mainly data-driven, not contaminated by application semantics, hence with an important potential for reuse. If LDWs could be decoupled from their breakout projects, this would increase the chances of LDWs becoming truly RDF end-points. But this vision is still under threat by LDW fragility upon API upgrades, and the risk of unmaintained LDWs. LDW curation might help. Similar to dataset curation, LDW curation aims to clean up datasets but, in this case, the dataset is implicitly described by the LDW definition, and ¿stains¿ are not limited to those related with the dataset quality but also include those related to the underlying API. This requires the existence of LDW Platforms that leverage existing code repositories with additional functionalities that cater for LDW definition, deployment and curation. This dissertation contributes to this vision through: (1) identifying a set of requirements for LDW Platforms; (2) instantiating these requirements in SYQL, a platform built upon Yahoo's YQL; (3) evaluating SYQL through a fully-developed proof of concept; and (4), validating the extent to which this approach facilitates LDW curation