Armando Stellato

Semantic turkey: a browser-integrated environment for knowledge acquisition and management

With the continued growth of online semantic information, the processes of searching and managing this massive scale and heterogeneous content have become increasingly challenging. In this work, we present PowerAqua, an ontologybased Question Answering system that is able to answer queries by locating and integrating information, which can be distributed across heterogeneous semantic resources. We provide a complete overview of the system including: the research challenges that it addresses, its architecture, the evaluations that have been conducted to test it, and an in-depth discussion showing how PowerAqua effectively supports users in querying and exploring Semantic Web content.Born four years ago as a Semantic Web extension for the web browser Firefox, Semantic Turkey pushed forward the traditional concept of links&folders-based bookmarking to a new dimension, allowing users to keep track of relevant information from visited web sites and to organize the collected content according to standard or personally defined ontologies. Today, the tool has broken the boundaries of its original intents and can be considered, under every aspect, an extensible platform for knowledge management and acquisition. The semantic bookmarking and annotation facilities of Semantic Turkey are now supporting just a part of a whole methodology where different actors, from domain experts to knowledge engineers, can cooperate in developing, building and populating ontologies while navigating the Web.

The AGROVOC Linked Dataset

Born in the early 1980s as a multilingual agricultural thesaurus, AGROVOC has steadily evolved over the last fifteen years, moving to an electronic version around the year 2000, and embracing the Semantic Web shortly thereafter. Today AGROVOC is a SKOS-XL concept scheme published as Linked Open Data, containing links as well as backlinks and references to many other Linked Datasets in the LOD cloud. In this paper we provide a brief historical summary of AGROVOC and detail its specification as a Linked Dataset.

Thesaurus maintenance, alignment and publication as linked data: the AGROVOC use case

The AGROVOC multilingual thesaurus maintained by the Food and Agriculture Organisation (FAO) of the United Nations is now published as linked data. In order to reach this goal AGROVOC was expressed in Simple Knowledge Organisation System (SKOS) and its concepts provided with dereferenceable URIs. AGROVOC is now aligned with ten other multilingual Knowledge Organisation Systems (KOS) related to agriculture, using the SKOS properties exact match and close match. Alignments were automatically produced in Eclipse using a custom-designed tool and then validated by a domain expert. The resulting data is publicly available to both humans and machines using a SPARQL endpoint together with a modified version of Pubby, a lightweight front-end tool for publishing linked data. This paper describes the process that led to the current linked data AGROVOC and discusses current and future applications and directions. This paper extends a shorter version presented at MTSR 2011.

Semantic Turkey: A Semantic Bookmarking Tool (System Description)

In this work we introduce Semantic Turkey, a Semantic Extension for the popular web browser Mozilla Firefox. Semantic Turkey can be used to keep track of relevant information from visited web sites and organize collected content according to a personally defined ontology. Clear separation between knowledge data (the WHAT) and web links (the WHERE) is established into the knowledge model of the system, which allows for innovative navigation of both the acquired information and of the pages where it has been collected. This paper describes the architecture of the Semantic Turkey extension for Firefox, analyzes its development, shows its most interesting features and presents our plans for future improvements of the tool.

VocBench: A Web Application for Collaborative Development of Multilingual Thesauri

We introduce VocBench, an open source web application for editing thesauri complying with the SKOS and SKOS-XL standards. VocBench has a strong focus on collaboration, supported by workflow management for content validation and publication. Dedicated user roles provide a clean separation of competences, addressing different specificities ranging from management aspects to vertical competences on content editing, such as conceptualization versus terminology editing. Extensive support for scheme management allows editors to fully exploit the possibilities of the SKOS model, as well as to fulfill its integrity constraints. We discuss thoroughly the main features of VocBench, detail its architecture, and evaluate it under both a functional and user-appreciation ground, through a comparison with state-of-the-art and user questionnaires analysis, respectively. Finally, we provide insights on future developments.

Semi-Automatic Ontology Development: Processes and Resources

The exploitation of theoretical results in knowledge representation, language standardization by W3C and data publication initiatives such as Linked Open Data have given a level of concreteness to the field of ontology research. In light of these recent outcomes, ontology development has also found its way to the forefront, benefiting from years of R&D on development tools. Semi-Automatic Ontology Development: Processes and Resources includes state-of-the-art research results aimed at the automation of ontology development processes and the reuse of external resources becoming a reality, thus being of interest for a wide and diversified community of users. This book provides a thorough overview on the current efforts on this subject and suggests common directions for interested researchers and practitioners

An open and scalable framework for enriching ontologies with natural language content

Knowledge Sharing is a crucial issue in the Semantic Web: SW services expose and share knowledge content which arise from distinct languages, locales, and personal perspectives; a great effort has been spent in these years, in the form of Knowledge Representation standards and communication protocols, with the objective of acquiring semantic consensus across distributed applications. However, neither ontology mapping algorithm nor knowledge mediator agent can easily find a way through ontologies as they are organized nowadays: concepts expressed by hardly recognizable labels, lexical ambiguity represented by phenomena like synonymy and polysemy and use of different natural languages which derive from different cultures, all together push for expressing ontological content in a linguistically motivated fashion. This paper presents our approach in establishing a framework for semi-automatic linguistic enrichment of ontologies, which led to the development of Ontoling, a plug-in for the popular ontology development tool Protege. We describe here its features and design aspects which characterize its current release.

LIME: The Metadata Module for OntoLex

The OntoLex W3C Community Group has been working for more than three years on a shared lexicon model for ontologies, called lemon. The lemon model consists of a core model that is complemented by a number of modules accounting for specific aspects in the modeling of lexical information within ontologies. In many usage scenarios, the discovery and exploitation of linguistically grounded ontologies may benefit from summarizing information about their linguistic expressivity and lexical coverage by means of metadata. That situation is compounded by the fact that lemon allows the independent publication of ontologies, lexica and lexicalizations linking them. While the VoID vocabulary already addresses the need for general metadata about interlinked datasets, it is unable by itself to represent the more specific metadata relevant to lemon. To solve this problem, we developed a module of lemon, named LIME Linguistic Metadata, which extends VoID with a vocabulary of metadata about the ontology-lexicon interface.

CODA: computer-aided ontology development architecture

This paper introduces CODA (Computer-aided Ontology Development Architecture), which is both an architecture and an associated framework supporting the transformation of unstructured and semi-structured content into RDF (Resource Description Framework) datasets. The purpose of CODA is to support the entire process that ranges from data extraction and transformation to identity resolution. The final objective is to feed semantic repositories with knowledge extracted from unstructured content. The motivation behind CODA lies in the large effort and design issues required for developing knowledge acquisition systems using content analytics frameworks such as UIMA™ (Unstructured Information Management Architecture) and GATE (General Architecture for Text Engineering). Therefore, CODA extends UIMA with facilities and a powerful language for projection and transformation of UIMA-annotated content into RDF. The proposed platform is oriented towards a wide range of beneficiaries, from semantic applications developers to final users that can easily plug CODA components into compliant desktop tools. We describe and discuss the features of CODA through the article, and we conclude by reporting on the adoption of the CODA framework in the context of a usage scenario, related to knowledge acquisition in the agricultural domain.

An Architecture for Data and Knowledge Acquisition for the Semantic Web: The AGROVOC Use Case

We are surrounded by ever growing volumes of unstructured and weakly-structured information, and for a human being, domain expert or not, it is nearly impossible to read, understand and categorize such information in a fair amount of time. Moreover, different user categories have different expectations: final users need easy-to-use tools and services for specific tasks, knowledge engineers require robust tools for knowledge acquisition, knowledge categorization and semantic resources development, while semantic applications developers demand for flexible frameworks for fast and easy, standardized development of complex applications. This work represents an experience report on the use of the CODA framework for rapid prototyping and deployment of knowledge acquisition systems for RDF. The system integrates independent NLP tools and custom libraries complying with UIMA standards. For our experiment a document set has been processed to populate the AGROVOC thesaurus with two new relationships.