SEMI-AUTOMATIC ANNOTATION OF WEB SERVICES: A COMPARATIVE ANALYSIS AND RESEARCH AGENDA

2012 ◽  
Vol 06 (02) ◽  
pp. 243-259
Author(s):  
MOHAMMAD MOURHAF AL ASSWAD ◽  
AUHOOD ALFARIES ◽  
SERGIO DE CESARE ◽  
MARK LYCETT
Keyword(s):  
Web Services ◽  
Research Agenda ◽  
Semantic Annotation ◽  
Theory And Practice ◽  
Future Research ◽  
Semantic Web Services ◽  
Successful Implementation ◽  
Automatic Annotation ◽  
Research And Practice ◽  
Annotation Process

Semantic web services (SWS) have recently attracted much attention because of their potential to automate all common service tasks such as discovery, composition, invocation and execution. The successful implementation of SWS is profoundly based on the availability of appropriate methods for SWS description. There is, however, no consensus in the SWS arena on the significant service elements that make SWS description comprehensive. Furthermore, semantic annotation of those elements is still a manual process where human involvement is a must. Therefore, automating the annotation process is highly desired as the manual annotation is a difficult, costly and time-consuming process. Few approaches exist aiming to semi-automate the annotation task. These approaches have limitations preventing their wide adoption by the research and practice communities. This paper contributes by analysing and comparing those existing semi-automatic Web service annotation approaches in order to highlight the major challenges and provide fruitful guidelines to aid future research. Particularly, a synthesis of service elements that require semantic annotation is provided and then used to assess the completeness of semi-automated approaches. The comparison leads to significant implications for theory and practice.

Automatic categorization of Web service elements

2018 ◽  
Vol 14 (2) ◽  
pp. 233-258 ◽  
Author(s):  
Efthimia Mavridou ◽  
Konstantinos M. Giannoutakis ◽  
Dionysios Kehagias ◽  
Dimitrios Tzovaras ◽  
George Hassapis
Keyword(s):  
Web Services ◽  
Web Service ◽  
Semantic Annotation ◽  
Third Party ◽  
Systematic Evaluation ◽  
Evaluation Procedure ◽  
Data Set ◽  
Content Type ◽  
Semantic Categorization ◽  
Description File

Purpose Semantic categorization of Web services comprises a fundamental requirement for enabling more efficient and accurate search and discovery of services in the semantic Web era. However, to efficiently deal with the growing presence of Web services, more automated mechanisms are required. This paper aims to introduce an automatic Web service categorization mechanism, by exploiting various techniques that aim to increase the overall prediction accuracy. Design/methodology/approach The paper proposes the use of Error Correcting Output Codes on top of a Logistic Model Trees-based classifier, in conjunction with a data pre-processing technique that reduces the original feature-space dimension without affecting data integrity. The proposed technique is generalized so as to adhere to all Web services with a description file. A semantic matchmaking scheme is also proposed for enabling the semantic annotation of the input and output parameters of each operation. Findings The proposed Web service categorization framework was tested with the OWLS-TC v4.0, as well as a synthetic data set with a systematic evaluation procedure that enables comparison with well-known approaches. After conducting exhaustive evaluation experiments, categorization efficiency in terms of accuracy, precision, recall and F-measure was measured. The presented Web service categorization framework outperformed the other benchmark techniques, which comprise different variations of it and also third-party implementations. Originality/value The proposed three-level categorization approach is a significant contribution to the Web service community, as it allows the automatic semantic categorization of all functional elements of Web services that are equipped with a service description file.

scholarly journals Converting Biomedical Text Annotated Resources into FAIR Research Objects with an Open Science Platform

2021 ◽  
Vol 11 (20) ◽  
pp. 9648
Author(s):  
Alexandros Kanterakis ◽  
Nikos Kanakaris ◽  
Manos Koutoulakis ◽  
Konstantina Pitianou ◽  
Nikos Karacapilidis ◽  
...  
Keyword(s):  
Web Services ◽  
Open Source ◽  
Semantic Annotation ◽  
Workflow Management ◽  
Open Science ◽  
Free Access ◽  
Biomedical Text ◽  
Text Annotation ◽  
Text Corpora ◽  
Research Objects

Today, there are excellent resources for the semantic annotation of biomedical text. These resources span from ontologies, tools for NLP, annotators, and web services. Most of these are available either in the form of open source components (i.e., MetaMap) or as web services that offer free access (i.e., Whatizit). In order to use these resources in automatic text annotation pipelines, researchers face significant technical challenges. For open-source tools, the challenges include the setting up of the computational environment, the resolution of dependencies, as well as the compilation and installation of the software. For web services, the challenge is implementing clients to undertake communication with the respective web APIs. Even resources that are available as Docker containers (i.e., NCBO annotator) require significant technical skills for installation and setup. This work deals with the task of creating ready-to-install and run Research Objects (ROs) for a large collection of components in biomedical text analysis. These components include (a) tools such as cTAKES, NOBLE Coder, MetaMap, NCBO annotator, BeCAS, and Neji; (b) ontologies from BioPortal, NCBI BioSystems, and Open Biomedical Ontologies; and (c) text corpora such as BC4GO, Mantra Gold Standard Corpus, and the COVID-19 Open Research Dataset. We make these resources available in OpenBio.eu, an open-science RO repository and workflow management system. All ROs can be searched, shared, edited, downloaded, commented on, and rated. We also demonstrate how one can easily connect these ROs to form a large variety of text annotation pipelines.

A Query-based Approach for Semi-Automatic Annotation of Web Services

2011 ◽  
Vol 2 (2) ◽  
pp. 37-54 ◽  
Author(s):  
Mohammad Mourhaf AL Asswad ◽  
Sergio de Cesare ◽  
Mark Lycett
Keyword(s):  
Web Services ◽  
Semantic Web ◽  
Semantic Annotation ◽  
Semantic Web Services ◽  
Manual Annotation ◽  
Automatic Annotation ◽  
Query Execution ◽  
Annotation Task ◽  
Compound Nouns ◽  
Execution Engine

Semantic Web services (SWS) have attracted increasing attention due to their potential to automate discovery and composition of current syntactic Web services. An issue that prevents a wider adoption of SWS relates to the manual nature of the semantic annotation task. Manual annotation is a difficult, error-prone, and time-consuming process and automating the process is highly desirable. Though some approaches have been proposed to semi-automate the annotation task, they are difficult to use and cannot perform accurate annotation for the following reasons: (1) They require building application ontologies to represent candidate services and (2) they cannot perform accurate name-based matching when labels of candidate service elements and ontological entities contain Compound Nouns (CN). To overcome these two deficiencies, this paper proposes a query-based approach that can facilitate semi-automatic annotation of Web services. The proposed approach is easy to use because it does not require building application ontologies to represent services. Candidate service elements that need to be annotated are extracted from a WSDL file and used to generate query instances by filling a Standard Query Template. The resulting query instances are executed against a repository of ontologies using a novel query execution engine to find appropriate correspondences for candidate service elements. This query execution engine employs name-based and structural matching mechanisms that can perform effective and accurate similarity measurements between labels containing CNs. The proposed semi-automatic annotation approach is evaluated by employing it to annotate existing Web services using published domain ontologies. Precision and recall are used as evaluation metrics. The resulting precision and recall values demonstrate the effectiveness and applicability of the proposed approach.

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