Towards a knowledge base to support geoprocessing workflow development

Web services are the new paradigm for distributed computing. They offer interoperability of application and integration of large scale distributed systems. Amongst the web service standards, service registry is crucial to the overall utility of web service technology. However, the web services discovery mechanism pertaining with the UDDI [1] registry is inefficient because it only supports keyword-based and category-based matching, leading to irrelevant matches. Therefore, the provision of the scalable, flexible and robust web services publication and discovery system is crucial for the overall utility of web services. In this paper, we develop a scalable, robust and efficient infrastructure for web services publication and discovery amongst domain-based registries. More importantly, a novel algorithm is provided to classify web services into domain-based registries based on their semantic description. Experimental results show that our approach outperforms a centralized approach in terms of service discovery time.

Shared-Repository based Approach for Storing and Discovering web Services

Currently proposed Semantic Web Services technologies allow the creation of ontology-based semantic annotations of Web services so that software agents are able to discover, invoke, compose and monitor these services with a high degree of automation. The OWL Services (OWL-S) ontology is an upper ontology in OWL language, providing essential vocabularies to semantically describe Web services. Currently OWL-S services can only be developed independently; if one service is unavailable then finding a suitable alternative would require an expensive and difficult global search/match. It is desirable to have a new OWL-S construct that can systematically support substitution tracing as well as incremental development and reuse of services. Introducing relationship (IR) into OWL-S is a natural solution. However, OWL-S, as well as most of the other currently discussed formalisms for Semantic Web Services such as WSMO or SAWSDL, has yet to define a concrete and self-contained mechanism of establishing relationships among services, which we believe is very important for the automated annotation and discovery of Web services as well as human organization of services into a taxonomy-like structure. In this paper, we extend OWL-S with the ability to define and maintain relationships between services. Through the definition of an additional inheritance profile, relationships can be stated and reasoned about. Two types of IRs are allowed to grant service developers the choice to respect the contract between services or not. The proposed framework has also been implemented and the prototype will be briefly evaluated as well.

Directory services are a genuine constituent of any distributed architecture which facilitate binding attributes to names and then querying this information, that is, announcing and discovering resources. In such contexts, especially in a business environment, Quality of Service (QoS) and non-functional properties are usually the most important criteria to decide whether a specific resource will be used. To address this problem, we present an approach to the semantic description and discovery of web services which specifically takes into account their QoS properties. Our solution uses a robust trust and reputation model to provide an accurate picture of the actual QoS to user. The search engine is based on an algebraic discovery model and uses adaptive query-processing techniques to parallelise expensive operators. Architecturally, the engine can be run as a centralised service for small-scale environments or can be distributed among any number of cooperating registry providers.

The Web is becoming a truly multilingual hub in which speakers from different languages and cultures are producing, interacting and consuming information. Web services are an essential part of the Web which nowadays attract more and more people around the world. So, supporting multilingual Web services discovery is a crucial goal to achieve, so that providers and users publish or consume Web services independently from their culture and native language. In this paper, we propose to overcome language barrier by supporting multilingual Web services discovery using DBpedia, which is a cross-domain multilingual knowledge base. DBpedia is used to annotate services with semantic entities called resources as well as their categories and types. We take advantage of semantic and multilingual information provided by DBpedia to enable cross-language semantic Web services discovery. Implementation shows that DBpedia offers a valuable information source to achieve our goal.

Web service (WS) discovery is a prerequisite for achieving WS composition and orchestration. Although a lot of research has been conducted on the functional discovery of WSs, the proposed techniques fall short when faced with the foreseen increase in the number of (potentially functionally-equivalent) WSs. The above situation can be resolved with the addition of non-functional (quality of service (QoS)) discovery mechanisms to WS discovery engines. QoS-based WS matchmaking algorithms have been devised for this reason. However, they are either slow - as they are based on ontology reasoners - or produce inaccurate results. Inaccuracy is caused both by the syntactic matching of QoS concepts and by wrong matchmaking metrics. In this paper, we present two constraint programming (CP) QoS-based WS discovery algorithms for unary constrained WS specifications that produce accurate results with good performance. We also evaluate these algorithms on matchmaking time, precision and recall in different settings in order to demonstrate their efficiency and accuracy.

Component retrieval/discovery is a well-established research direction in Software Engineering. With the surge of Service-Oriented Architecture (SOA), service discovery has become increasingly crucial. However, the public UDDI Business Registry - the primary service discovery mechanism over the Internet - has been shut down permanently since 2006. Moreover, keyword-based service discovery is insufficient in coping with complex discovery requirements posed by modern software developers. In this paper, we propose an empirical semantic- based Web service discovery approach. It provides an automatic Web service discovery mechanism that can locate relevant Web services based on concepts rather than keywords. The major contribution of this paper is three fold. First we articulate three requirements that software developers often raise during the component/service development and discovery process. Next, we propose the application of Latent Semantic Analysis into the area of Web services discovery. To our best knowledge, little work has been done in this area which leverages concept-based Information Retrieval models in service discovery. Last, we provide a proof-of-concept system prototype that can suffice three specific requirements of semantic service discovery.

Matching web services and client requirements in the form of goals is a significant challenge in the discovery of semantic web services. The most common but unsatisfactory approach to matching is set‐based, where both the client and web services declare what objects they require and what objects they can provide. Matching then becomes the simple task of comparing sets of objects. This approach is inadequate because it says nothing about the functionality required by the client or the functionality provided by the web service. As an alternative, we use the Frame Logic as implemented in Flora‐2 to specify web service capabilities and client requirements, including their preconditions, postconditions, and ontologies, implement a logic‐based discovery agent using Flora‐2, demonstrate its usefulness in a medical appointment making scenario, and show its efficiency both theoretically and by benchmarking. The result is an expressive yet concise representation scheme for semantic web services, and a practical, efficient, powerful, and fully implemented matching engine based purely on logical inference for web service discovery, with direct applicability to Web Service Modeling Ontology and Web Service Modeling Language, because both are based on Frame Logic.

Due to the emergence of Internet technologies and service-oriented computing, there is a rapid growth in the quantity and variety of services on the web. Discovering the web services as per the request is not an easy task because of the advancement of service-oriented computing which includes web services, cloud services, mobile services, etc. These services are dynamic and published according to the emerging standards in repositories. Web service clustering plays a crucial role in web service discovery. When services are grouped according to the similarity, then it reduces the search space and time, so that services can be discovered efficiently. Many eminent researchers have proposed approaches for efficient web service discovery by incorporating web service clustering. In this paper, we review different approaches that are proposed for web service clustering to enhance the discovery process. A comparison among existing approaches is carried out based on the vector representation approach, dimensionality reduction technique, method to capture semantic relationship among features, clustering technique, type of input dataset, number of web services in dataset and service repository. This review will help the researchers to understand the existing techniques to group services in similar clusters to improvise service discovery and the scope for improvement by future directions.KeywordsService-oriented architectureWeb services/Web APIWeb service clusteringWeb service discovery

Semantic Web services is considered as the concept bringing the web to its full potential by combining the best features of web services, agent technology, grid and the Semantic web. In this paper we present a semantic Web Services platform based on software agent (JASW), which introduces Semantic web and software agent and takes the automated discovery, selection, orchestration and invocation of Web services as application background. In the platform, we adopt Semantic web to accurately describe Web services, and use software agent to implement discovery, selection, and orchestration of Web services.

With the rapid growth and adoption of web-based technologies, more and more service providers offer various services on the web. This can facilitate the organizations to develop business applications using web services composition over the Internet according to their business requirements. The primary requirement for developing composite web service is to discover the most relevant web service for realizing each function of the required composite web service. Finding the most relevant web service is still a challenging task. In this paper, we propose web service discovery approach that incorporates web services clustering. Clustering technique combines latent Dirichlet allocation(LDA) and k-Medoids and reduces search space for web service discovery. Web service discovery uses a match-making algorithm that utilizes WordNet database and Hungarian method to compute the semantic similarity score for a web service based on the requested query. Experimental results show that the proposed approach performs better than LDA-based approach.

Web services (WS) is called composite or compound when its execution involves interactions with other WS to utilize their features. The service providers published the web services through the internet as independent software components that are fulfilling the requirements of customer request. Clustering is more necessary for efficient web service discovery and web service composition processes. Clustering process groups the similar type of web services. In this paper, efficient clustering methods such as k-means clustering, Hierarchical agglomerative clustering and Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH) clustering are introduced for web service clustering. The k-means clustering is a kind of partitional clustering where the web pages are divided into subsets with no hierarchy defined over them and the hierarchical agglomerative clustering is a type of hierarchical clustering where the web pages are arranged in tree structure in which leaves represents the data points and nodes denotes the clusters. BIRCH is an integrated hierarchical clustering algorithm uses the clustering features and cluster feature tree for general cluster description. Based on these clustering methods, web pages are clustered which are used for web service discovery and web service composition. The experiments are conducted on number of web services and the efficiency is evaluated in terms of accuracy, precision, recall and run time.

Technologies for Web services facilitate the creation of business process solutions in an efficient, standard way. However, the automation of process integration with Web service technologies requires the automation of discovery and composition of Web services. In this paper, we focus on two problems of the Web service-based business process integration: (1) the discovery of Web services based on the capabilities and properties of published services, and (2) the composition of business processes based on the business requirements of submitted requests. We propose a solution to these problems, which comprises multiple matching algorithms, a micro-level matching algorithm, which matches the capabilities of services with activities in a process request, and macro-level matching algorithms, which are used to compose a business process by identifying services that satisfy the business requirements and constraints of the request. The solution from the macro-level matching algorithms is optimal in terms of meeting a certain business objective, e.g., minimizing the cost or execution time, or maximizing the total utility value of business properties of interest. Numerical examples are illustrated to show how to select the best Web service candidate for a chosen business process through the use of proposed macro-level matching algorithms. Furthermore, we show how existing Web service standards, UDDI and BPEL4WS, can be used and extended to specify the capabilities of services and the business requirements of requests, respectively.

UDDI registration center provides a set of management mechanism for Web services providers to publish their Web service and for Web service consumers to inquire what they needs. It solves the problem of Web service description, discovery and Integration. Web services graph is the semantic index established on the UDDI registration center according to the logical relations between web services [1,2]. It can enhance the Web service discovery efficiency. jUDDI is an open source Java implementation of UDDI specification for Web Services. Based on the research on UDDI and Web service graph, this article takes jUDDI as an example to show how the traditional UDDI registry center can be extended so as to supporting Web service graph.

Web services provide a promising solution to an age old need of fast and flexible information sharing among people and businesses. One of the key research issues in web services is selection of most pertinent web services. Selection of web service has become a tedious job because of the increasing number of service providers providing services with similar functionality. Therefore, a framework for selection and discovery of web service that can meet the non-functional requirements is needed. In this work, we have developed a selection tool (WSS-NFP) for web services which can rank services based on their non functional properties such as performance, delay etc. We have used soft computing techniques for selection and discovery of web services based on non functional properties. These properties are fuzzy in nature. A tool is developed and implemented that is generic in nature and can be customized for any application domain. As a core of this tool, it consists of Fuzzy System for ranking web services and Neural Network for fine tuning the membership functions for linguistic terms. Appropriate and fine tuned membership functions help in minimizing the output error measure and maximizing the performance index of the proposed tool. This tool is basically a Neuro-Fuzzy system for ranking web services of any domain.