Ghislain Auguste Atemezing

Linked Open Vocabularies (LOV): A gateway to reusable semantic vocabularies on the Web

One of the major barriers to the deployment of Linked Data is the difficulty that data publishers have in determining which vocabularies to use to describe the semantics of data. This system report describes Linked Open Vocabularies (LOV), a high quality catalogue of reusable vocabularies for the description of data on the Web. The LOV initiative gathers and makes visible indicators that have not been previously harvested such as the interconnections between vocabularies, version history along with past and current referent (individual or organization). LOV goes beyond existing Semantic Web vocabulary search engines and takes into consideration the values property type, matched with a query, to improve vocabulary terms scoring. By providing an extensive range of data access methods (SPARQL endpoint, API, data dump or UI), we try to facilitate the reuse of well-documented vocabularies in the Linked Data ecosystem. We conclude that the adoption in many applications and methods of LOV shows the benefits of such a set of vocabularies and related features to aid the design and publication of data on the Web.

Transforming meteorological data into Linked Data

We describe the AEMET meteorological dataset, which makes available some data sources from the Agencia Estatal de Meteorologia AEMET, Spanish Meteorological Office as Linked Data. The data selected for publication are generated every ten minutes by approximately 250 automatic weather stations deployed across Spain and made available as CSV files in the AEMET FTP server. These files are retrieved from the server, processed with Python scripts, transformed to RDF according to an ontology network which reuses the W3C SSN Ontology, published in a triple store and visualized using Map4RDF.

Semantic web methodologies, best practices and ontology engineering applied to Internet of Things

We discuss in this paper, semantic web methodologies, best practices and recommendations beyond the IERC Cluster Semantic Interoperability Best Practices and Recommendations (IERC AC4). The semantic web community designed best practices and methodologies which are unknown from the IoT community. In this paper, we synthesize and highlight the most relevant work regarding ontology methodologies, engineering, best practices and tools that could be applied to Internet of Things (IoT). To the best of our knowledge, this is the first work aiming at bridging such methodologies to the IoT community and go beyond the IERC AC4 cluster. This research is being applied to three uses cases: (1) the M3 framework assisting IoT developers in designing interoperable ontology-based IoT applications, (2) the FIESTA-IoT EU project encouraging semantic interoperability within IoT, and (3) a collaborative publication of legacy ontologies.

The landscape of multimedia ontologies in the last decade

Many efforts have been made in the area of multimedia to bridge the so-called “semantic-gap” with the implementation of ontologies from 2001 to the present. In this paper, we provide a comparative study of the most well-known ontologies related to multimedia aspects. This comparative study has been done based on a framework proposed in this paper and called FRAMECOMMON. This framework takes into account process-oriented dimension, such as the methodological one, and outcome-oriented dimensions, like multimedia aspects, understandability, and evaluation criteria. Finally, we derive some conclusions concerning this one decade state-of-art in multimedia ontologies.

An Ontology for African Traditional Medicine

This paper describes an ontology for African Traditional Medicine (ATM), which is the basis for a knowledge management system, controlled by a multi-agent system. The interest of this problem, from the point of view of artificial intelligence and software engineering lies on the issues that arise from integration of the requirements of the different stakeholders in such a system and the diverse nature of concepts to be considered in such an ontology. One of these issues is the need to allow the ontology to evolve as far as experts provide more knowledge and the mechanisms for validation of such knowledge.

Reusing and Unifying Background Knowledge for Internet of Things with LOV4IoT

Ontology-based applications are becoming more and more popular and are usually domain-specific (e.g., eHealth or domotic). Designing ontologies and semantic-based applications manually is tedious and cumbersome for non-technical expert or semantic web beginners. Internet of Things (IoT) is a new field aiming to connect the physical world surrounded by devices such as sensors to the web to automatically interact with them and build innovative applications. The main challenges are to automate as much as possible the tasks of: (1) reusing the background knowledge previously designed by domain experts, (2) facilitating the tasks of IoT developers willing to integrate semantic web technologies into their applications, and (3) designing interoperable semantic-based IoT applications. Stemming from Linked Open Data and Linked Open Vocabularies, we designed Linked Open Vocabularies for Internet of Things (LOV4IoT), a catalogue of ontologies/datasets/rules relevant for IoT available online. LOV4IoT has been extended with more domains and ontology-based projects, a semantic-based dataset and a bot to enhance automation, and web services. Moreover, we demonstrate several use cases of the LOV4IoT dataset: (1) building Semantic Web of Things applications, (2) extracting frequent terms used in existing ontologies, and (3) stakeholders who can exploit, reuse and combine domain ontologies. Finally, we evaluated this dataset with users who exploit this dataset for their own purposes.

The ProtégéLOV Plugin: Ontology Access and Reuse for Everyone

Developing ontologies, by reusing already available and well-known ontologies, is commonly acknowledge to play a crucial role to facilitate inclusion and expansion of the Web of Data. Some recommendations exist to guide ontologists in ontology engineering, but they do not provide guidelines on how to reuse vocabularies at low fine grained, i.e., reusing specific classes and properties. Moreover, it is still hard to find a tool that provides users with an environment to reuse terms. This paper presents ProtegeLOV, a plugin for the ontology editor Protege, that combines the access to the Linked Open Vocabularies LOV during ontology modeling. It allows users to search a term in LOV and provides three actions if the term exists: i replace the selected term in the current ontology; ii add the rdfs:subClassOf or rdfs:subPropertyOf axiom between the selected term and the local term; and iii add the owl:equivalentClass or owl:equivalentProperty between the selected term and local term. Results from a preliminary user study indicate that ProtegeLOV does provide an intuitive access and reuse of terms in external vocabularies.

Adopting Semantic Technologies for Effective Corporate Transparency

A new transparency model with more and better corporate data is necessary to promote sustainable economic growth. In particular, there is a need to link factors regarding non-financial performance of corporations - such as social and environmental impacts, both positive and negative - into decision-making processes of investors and other stakeholders. To do this, we need to develop better ways to access and analyse corporate social, environmental and financial performance information, and to link together insights from these different sources. Such sources are already on the web in non-structured and structured data formats, a big part of them in XBRL (Extensible Business Reporting Language). This study is about promoting solutions to drive effective transparency for a sustainable economy, given the current adoption of XBRL, and the new opportunities that Linked Data can offer. We present (1) a methodology to formalise XBRL as RDF using Linked data principles and (2) demonstrate its usefulness through a use case connecting and making the data accessible.

What Are the Important Properties of an Entity

Entities play a key role in knowledge bases in general and in the Web of Data in particular. Entities are generally described with a lot of properties, this is the case for DBpedia. It is, however, difficult to assess which ones are more “important” than others for particular tasks such as visualizing the key facts of an entity or filtering out the ones which will yield better instance matching. In this paper, we perform a reverse engineering of the Google Knowledge graph panel to find out what are the most “important” properties for an entity according to Google. We compare these results with a survey we conducted on 152 users. We finally show how we can represent and explicit this knowledge using the Fresnel vocabulary.

Confomaton: A Conference Enhancer with Social Media from the Cloud

A scientific conference is a type of event for which the structured program is generally known in advance. The Semantic Web community has setup a so-called Semantic Web dog food server that exposes structured data about the detailed program of more and more conferences and their sub-events (e.g. sessions). Conferences are also events that trigger a tremendous activity on social media. Participants tweet or post longer status messages, engage in discussion with comments, share slides and other media captured during the conference. This information is spread over multiple platforms forcing the user to monitor many different channels at the same time to fully benefit of the event. In this paper, we present Confomaton, a semantic web application that aggregates and reconciles information such as tweets, slides, photos and videos shared on social media that could potentially be attached to a scientific conference.