MidSemI

2019 ◽  
Vol 10 (2) ◽  
pp. 1-25 ◽  
Author(s):  
Samir Sellami ◽  
Taoufiq Dkaki ◽  
Nacer Eddine Zarour ◽  
Pierre-Jean Charrel
Keyword(s):  
Social Media ◽  
Linked Data ◽  
Large Scale ◽  
Keyword Search ◽  
Evaluation Study ◽  
Added Value ◽  
Web Of Data ◽  
Integration Techniques ◽  
User Friendly ◽  
The Web

The web diversification into the Web of Data and social media means that companies need to gather all the necessary data to help make the best-informed market decisions. However, data providers on the web publish data in various data models and may equip it with different search capabilities, thus requiring data integration techniques to access them. This work explores the current challenges in this area, discusses the limitations of some existing integration tools, and addresses them by proposing a semantic mediator-based approach to virtually integrate enterprise data with large-scale social and linked data. The implementation of the proposed approach is a configurable middleware application and a user-friendly keyword search interface that retrieves its input from internal enterprise data combined with various SPARQL endpoints and Web APIs. An evaluation study was conducted to compare its features with recent integration approaches. The results illustrate the added value and usability of the contributed approach.

scholarly journals A survey of large-scale reasoning on the Web of data

2018 ◽  
Vol 33 ◽  
Author(s):  
Grigoris Antoniou ◽  
Sotiris Batsakis ◽  
Raghava Mutharaju ◽  
Jeff Z. Pan ◽  
Guilin Qi ◽  
...  
Keyword(s):  
Systematic Review ◽  
Social Media ◽  
Parallel Algorithms ◽  
High Performance ◽  
Large Scale ◽  
Open Problems ◽  
Reasoning Systems ◽  
Web Of Data ◽  
Computational Properties ◽  
The Web

AbstractAs more and more data is being generated by sensor networks, social media and organizations, the Web interlinking this wealth of information becomes more complex. This is particularly true for the so-called Web of Data, in which data is semantically enriched and interlinked using ontologies. In this large and uncoordinated environment, reasoning can be used to check the consistency of the data and of associated ontologies, or to infer logical consequences which, in turn, can be used to obtain new insights from the data. However, reasoning approaches need to be scalable in order to enable reasoning over the entire Web of Data. To address this problem, several high-performance reasoning systems, which mainly implement distributed or parallel algorithms, have been proposed in the last few years. These systems differ significantly; for instance in terms of reasoning expressivity, computational properties such as completeness, or reasoning objectives. In order to provide a first complete overview of the field, this paper reports a systematic review of such scalable reasoning approaches over various ontological languages, reporting details about the methods and over the conducted experiments. We highlight the shortcomings of these approaches and discuss some of the open problems related to performing scalable reasoning.

Linked Data

2012 ◽  
Vol 3 (3) ◽  
pp. 1-12 ◽  
Author(s):  
Ricardo Colomo-Palacios ◽  
José Luis Sánchez-Cervantes ◽  
Giner Alor-Hernández ◽  
Alejandro Rodríguez-González
Keyword(s):  
Semantic Web ◽  
Linked Data ◽  
Large Scale ◽  
Semantic Web Technologies ◽  
Public And Private ◽  
Professional Perspective ◽  
Community Boundaries ◽  
Web Of Data ◽  
Common Framework ◽  
The Web

The Semantic Web provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries. To make the Semantic Web or Web of Data a reality, it is necessary to have a large volume of data available in a standard, reachable, and manageable format. This collection of interrelated data on the Web can also be referred to as Linked Data. Linked Data is the large scale integration of, and reasoning on, data on the Web. Supporting the adoption of semantic Web technologies, there exist tools oriented to creation, publication, and management of data, and a big subset for Linked Data. However, an important weakness in this area is that it has not completely established a formal reference that integrates the necessary infrastructure in terms of components. This lack implies a slower technological adoption, covering both the public and private sectors. This paper explores the emergence of the Semantic Web and Linked Data, and their potential impact on IT industry. The main advantages of using Linked Data are discussed from an IT professional perspective where the capability of having standard technologies and techniques to access and manipulate the information is an important achievement in the application of Linked Data.

Linked Data, Towards Realizing the Web of Data

2018 ◽  
pp. 292-312
Author(s):  
Leila Zemmouchi-Ghomari
Keyword(s):  
Semantic Web ◽  
Linked Data ◽  
Web Applications ◽  
Online Data ◽  
Web Of Data ◽  
Promising Solution ◽  
Basic Ideas ◽  
Online Sources ◽  
Significant Effort ◽  
The Web

Data play a central role in the effectiveness and efficiency of web applications, such as the Semantic Web. However, data are distributed across a very large number of online sources, due to which a significant effort is needed to integrate this data for its proper utilization. A promising solution to this issue is the linked data initiative, which is based on four principles related to publishing web data and facilitating interlinked and structured online data rather than the existing web of documents. The basic ideas, techniques, and applications of the linked data initiative are surveyed in this paper. The authors discuss some Linked Data open issues and potential tracks to address these pending questions.

Context, Gender and Intended Use of Mobile Messaging, Entertainment and Social Media Services

2012 ◽  
Vol 3 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Anna Sell ◽  
Mark de Reuver ◽  
Pirkko Walden ◽  
Christer Carlsson
Keyword(s):  
Social Media ◽  
Large Scale ◽  
Service Providers ◽  
Mobile Services ◽  
Added Value ◽  
Survey Study ◽  
General Context ◽  
Media Services ◽  
Context Of Use ◽  
Intended Use

The added value of mobile services is decided by the context in which they are used. In this paper, the authors study how the context-of-use influences the intention to adopt mobile messaging, entertainment and social media services. While doing so, the authors compare the intended use between males and females. The results are based on a large scale survey study among Finnish consumers. According to the findings, the context-of-use matters for mobile entertainment and messaging services, but not for social media services. Fit with social context is only important for social media services, whilst work-related context matters only for messaging services. In general, context-of-use is more decisive for men than women. However, while ubiquitous context-of-use is much more important for males, social and work context are relevant only for females. The results have important implications for service providers on how to develop and implement specific context-aware mobile services.

Web Data Quality

2014 ◽  
Vol 10 (2) ◽  
pp. 1-6 ◽  
Author(s):  
Amrapali Zaveri ◽  
Andrea Maurino ◽  
Laure-Berti Equille
Keyword(s):  
Semantic Web ◽  
Data Quality ◽  
Linked Data ◽  
Web Data ◽  
Semantic Web Technologies ◽  
Future Directions ◽  
Web Technologies ◽  
Current State ◽  
Web Of Data ◽  
The Web

The standardization and adoption of Semantic Web technologies has resulted in an unprecedented volume of data being published as Linked Data (LD). However, the “publish first, refine later” philosophy leads to various quality problems arising in the underlying data such as incompleteness, inconsistency and semantic ambiguities. In this article, we describe the current state of Data Quality in the Web of Data along with details of the three papers accepted for the International Journal on Semantic Web and Information Systems' (IJSWIS) Special Issue on Web Data Quality. Additionally, we identify new challenges that are specific to the Web of Data and provide insights into the current progress and future directions for each of those challenges.

scholarly journals Linked Data - The Story So Far

2009 ◽  
Vol 5 (3) ◽  
pp. 1-22 ◽  
Author(s):  
Christian Bizer ◽  
Tom Heath ◽  
Tim Berners-Lee
Keyword(s):  
Best Practices ◽  
Research Agenda ◽  
Linked Data ◽  
Structured Data ◽  
Data Space ◽  
Web Of Data ◽  
Technological Developments ◽  
Technical Principles ◽  
Global Data ◽  
The Web

The term “Linked Data” refers to a set of best practices for publishing and connecting structured data on the Web. These best practices have been adopted by an increasing number of data providers over the last three years, leading to the creation of a global data space containing billions of assertions— the Web of Data. In this article, the authors present the concept and technical principles of Linked Data, and situate these within the broader context of related technological developments. They describe progress to date in publishing Linked Data on the Web, review applications that have been developed to exploit the Web of Data, and map out a research agenda for the Linked Data community as it moves forward.

IMPROVED LINKED DATA INTERACTION THROUGH AN AUTOMATIC INFORMATION ARCHITECTURE

2012 ◽  
Vol 22 (03) ◽  
pp. 325-343 ◽  
Author(s):  
JOSEP MARIA BRUNETTI ◽  
ROSA GIL ◽  
JUAN MANUEL GIMENO ◽  
ROBERTO GARCIA
Keyword(s):  
User Experience ◽  
Linked Data ◽  
Open Data ◽  
Information Architecture ◽  
Data Publishing ◽  
Tabular Data ◽  
Automatic Information ◽  
Web Of Data ◽  
New Perspective ◽  
The Web

Thanks to Open Data initiatives the amount of data available on the Web is rapidly increasing. Unfortunately, most of these initiatives only publish raw tabular data, which makes its analysis and reuse very difficult. Linked Data principles allow for a more sophisticated approach by making explicit both the structure and semantics of the data. However, from the user experience viewpoint, published datasets continue to be monolithic files which are completely opaque or difficult to explore by making complex semantic queries. Our objective is to facilitate the user to grasp what kind of entities are in the dataset, how they are interrelated, which are their main properties and values, etc. Rhizomer is a data publishing tool whose interface provides a set of components borrowed from Information Architecture (IA) that facilitate getting an insight of the dataset at hand. Rhizomer automatically generates navigation menus and facets based on the kinds of things in the dataset and how they are described through metadata properties and values. This tool is currently being evaluated with end users that discover a whole new perspective of the Web of Data.

scholarly journals Recuperação da Informação em Ambientes Semânticos: uma ferramenta aplicada à publicações científicas

2015 ◽  
Vol 1 (1) ◽  
pp. 30 ◽  
Author(s):  
Caio Saraiva Coneglian ◽  
Elvis Fusco
Keyword(s):  
Social Media ◽  
Big Data ◽  
Information Retrieval ◽  
Great Difficulty ◽  
Unstructured Data ◽  
Added Value ◽  
Informational Needs ◽  
Retrieval Process ◽  
Extraction Agent ◽  
The Web

The data available on the Web is growing exponentially, providing information of high added value to organizations. Such information can be arranged in diverse bases and in varied formats, like videos and photos in social media. However, unstructured data present great difficulty for the information retrieval, not efficiently meeting the informational needs of the users, because there are problems in understanding the meaning of documents stored on the Web. In the context of an Information Retrieval architecture, this research aims to The implementation of a semantic extraction agent in the context of the Web that allows the location, treatment and retrieval of information in the context of Big Data in the most varied informational sources that serves as the basis for the implementation of informational environments that aid the Information Retrieval process , Using ontology to add semantics to the process of retrieval and presentation of results obtained to users, thus being able to meet their needs.

scholarly journals GRALD: an Approach for Goal and Risk Analysis in the Development of Information Systems for the Web of Data

2019 ◽  
Vol 7 ◽  
pp. 4
Author(s):  
Marcio Louzada De Freitas ◽  
Renata Silva Souza Guizzardi ◽  
Vítor Estêvão Silva Souza
Keyword(s):  
Information Systems ◽  
Linked Data ◽  
Conceptual Modeling ◽  
Risk Identification ◽  
Domain Ontology ◽  
Intrinsic Activity ◽  
Published Data ◽  
Functional Requirements ◽  
Web Of Data ◽  
The Web

The publication of Linked Data on the Web regarding several application domains leads to new problems related to Requirements Engineering, which needs to take into account aspects related to new ways of developing systems and delivering information integrated with the Web of Data. Tasks such as (functional and non-functional) requirements elicitation and ontology-based conceptual modeling can be applied to the development of systems that publish Linked Data, in order to obtain a better shared conceptualization (i.e., a domain ontology) of the published data. The use of vocabularies is an intrinsic activity when publishing or consuming Linked Data and their choice can be supported by the elicited requirements and domain ontology. However, it is important to assess the risk when choosing external vocabularies, as their use can lead to problems, such as misinterpretation of meanings due to poor documentation, connection timeouts due to infrastructure problems, etc. Thus, risk identification, modeling and analysis techniques can be employed, in order to identify risks and their impacts on stakeholder goals. In this work, we propose GRALD: Goals and Risks Analysis for Linked Data, an approach for modeling goals and risks for information systems for the Web of Data.

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