W3C Semantic Web Research Articles

Comparative Study of Tools for Modeling, Storage, and Integration of Data on the Semantic Web for the ELLAS Network Platform

The layered architecture of the World Wide Web (W3C) defines standards, technologies, languages, and methods needed to build applications that involve the semantic web. From this W3C semantic web architecture was developed the data modeling of the ELLAS (Equality in Leadership for Latin American STEM) network platform. The ELLAS aims to map the policies and context aspects that influence women in STEM (Science, Technology, Engineering and Mathematics) in the countries of Bolivia, Brazil and Peru, which are at different levels of development. The main objective of this work is a comparison of the main storage and semantic integration tools to develop a data model (modeling, storage and integration of data) related to the mapping of policies, initiatives and factors that influence the career development of women in STEM.

Development of Semantic-Web Based Forest Resources Database

There are some forest resources (such as Trees, Shrubs, and Water bodies) in the university main campus. These resources are used for various purposes ranging from teaching, researches medicinal and domestic purposes and among many others. However, there is no record of official documentation on them. Thus, this study aims to provide a semantic-web based database system for efficient management of forest resources. We adopted the W3C semantic web framework in the design and development of this work. Specifically, we focused on the layers 1 to 5 of the framework. The layers include; Resource Description Framework (RDF), Web Ontology Language (OWL), Extensible Markup Language (XML), User Interface). The Uschold’s and Kings’ method was applied in creating the ontology. The implementation process was carried out by populating the database with the Taxonomies of the Trees on University of Energy and Natural Resources (U.E.N.R) campus by means of creating an Ontology File using protégé. Some of the basic information that we provided by the proposed semantic web database include trees, their scientific name, geographical coordinate, physical location, medicinal value and other important data. We performed alpha test by involving six senior forest science students who used the application, evaluated it and came out with a good result which is shown in the chapter four of this documentation.

ContSOnto: A Formal Ontology for Continuity of Care.

The global pandemic over the past two years has reset societal agendas by identifying both strengths and weaknesses across all sectors. Focusing in particular on global health delivery, the ability of health care facilities to scale requirements and to meet service demands has detected the need for some national services and organisations to modernise their organisational processes and infrastructures. Core to requirements for modernisation is infrastructure to share information, specifically structural standardised approaches for both operational procedures and terminology services. Problems of data sharing (aka interoperability) is a main obstacle when patients are moving across healthcare facilities or travelling across border countries in cases where emergency treatment is needed. Experts in healthcare service delivery suggest that the best possible way to manage individual care is at home, using remote patient monitoring which ultimately reduces cost burden both for the citizen and service provider. Core to this practice will be advancing digitalisation of health care underpinned with safe integration and access to relevant and timely information. To tackle the data interoperability issue and provide a quality driven continuous flow of information from different health care information systems semantic terminology needs to be provided intact. In this paper we propose and present ContSonto a formal ontology for continuity of care based on ISO 13940:2015 ContSy and W3C Semantic Web Standards Language OWL (Web Ontology Language). ContSonto has several benefits including semantic interoperability, data harmonization and data linking. It can be use as a base model for data integration for different healthcare information models to generate knowledge graph to support shared care and decision making.

WarSampo knowledge graph: Finland in the Second World War as Linked Open Data

The Second World War (WW2) is arguably the most devastating catastrophe of human history, a topic of great interest to not only researchers but the general public. However, data about the Second World War is heterogeneous and distributed in various organizations and countries making it hard to utilize. In order to create aggregated global views of the war, a shared ontology and data infrastructure is needed to harmonize information in various data silos. This makes it possible to share data between publishers and application developers, to support data analysis in Digital Humanities research, and to develop data-driven intelligent applications. As a first step towards these goals, this article presents the WarSampo knowledge graph (KG), a shared semantic infrastructure, and a Linked Open Data (LOD) service for publishing data about WW2, with a focus on Finnish military history. The shared semantic infrastructure is based on the idea of representing war as a spatio-temporal sequence of events that soldiers, military units, and other actors participate in. The used metadata schema is an extension of CIDOC CRM, supplemented by various military history domain ontologies. With an infrastructure containing shared ontologies, maintaining the interlinked data brings upon new challenges, as one change in an ontology can propagate across several datasets that use it. To support sustainability, a repeatable automatic data transformation and linking pipeline has been created for rebuilding the whole WarSampo KG from the individual source datasets. The WarSampo KG is hosted on a data service based on W3C Semantic Web standards and best practices, including content negotiation, SPARQL API, download, automatic documentation, and other services supporting the reuse of the data. The WarSampo KG, a part of the international LOD Cloud and totalling ca. 14 million triples, is in use in nine end-user application views of the WarSampo portal, which has had over 690 000 end users since its opening in 2015.

Cybersecurity threat intelligence knowledge exchange based on blockchain

Although cyber threat intelligence (CTI) exchange is a theoretically useful technique for improving security of a society, the potential participants are often reluctant to share their CTI and prefer to consume only, at least in voluntary based approaches. Such behavior destroys the idea of information exchange. On the other hand, governments are forcing specific entities and operators to report them specific incidents depending on their impact, otherwise there could be sanctions to those operators which are not reporting them on time. Obligations and sanctions are usually discouraging participants to share information voluntarily which will just share and report what is strictly required. We propose a paradigm shift of cybersecurity information exchange by introducing a new way to encourage all participants involved, at all levels, to share relevant information dynamically. It will also contribute to the support and deployment of Dynamic Risk Management frameworks to keep risks under an acceptance level along the time. Participants will have new and specific incentives to share, invest and consume threat intelligence and risk intelligence information depending on their different roles (producers, consumers, investors, donors and owner). Our proposal leverages from standards like Structured Threat Information Exchange, as well as W3C semantic web standards to enable a workspace of knowledge related to behavioral threat intelligence patterning to characterize tactics, techniques and procedures. At the same time, we propose an Ethereum Blockchain Smart contract Marketplace to better incentivize the sharing of that knowledge between all parties involved as well as creating a standard CTI token as a digital asset with a promising value in the market. Simulations and an experimentation were performed to demonstrate its benefits and incentives, but also its potential limits with regard to storage and cost of transactions.

Promoting the capture of sensor data provenance: a role-based approach to enable data quality assessment, sensor management and interoperability

Sensor technologies and capabilities have an effect on observational data quality. Typically, data management begins, at best, when a data manager obtains the data and needs to describe it sufficiently to data consumers. Often, the sensing methods are not adequately described and the data manager does not know the appropriate questions to ask or where to direct questions about sensors, their configuration, and the deployment. Consequently, knowledge often remains buried in sensor manuals and field operator logs. Thus, most metadata requirements have been simplified to accommodate this gap in knowledge.When information is captured where it is best understood and tools are created to easily capture this knowledge, machine-actionable descriptions can be provided to adequately describe the processes taken in generating observations. The information can be associated with the data and thus be accessible, discoverable and used in data quality control by data providers and in data quality assessment by the data consumers.Here, we define actors and actions to promote role-based creation of fully-described, standards-based documents. These documents can be created in SensorML (OGC SWE) that includes links to resolvable term definitions (W3C Semantic Web), enabling the creation of associated mappings and ontologies to extend and resolve the meaning of each term.

The health care and life sciences community profile for dataset descriptions.

Access to consistent, high-quality metadata is critical to finding, understanding, and reusing scientific data. However, while there are many relevant vocabularies for the annotation of a dataset, none sufficiently captures all the necessary metadata. This prevents uniform indexing and querying of dataset repositories. Towards providing a practical guide for producing a high quality description of biomedical datasets, the W3C Semantic Web for Health Care and the Life Sciences Interest Group (HCLSIG) identified Resource Description Framework (RDF) vocabularies that could be used to specify common metadata elements and their value sets. The resulting guideline covers elements of description, identification, attribution, versioning, provenance, and content summarization. This guideline reuses existing vocabularies, and is intended to meet key functional requirements including indexing, discovery, exchange, query, and retrieval of datasets, thereby enabling the publication of FAIR data. The resulting metadata profile is generic and could be used by other domains with an interest in providing machine readable descriptions of versioned datasets.

OntoBroker

OntoBroker provides a comprehensive, scalable and high-performance Semantic Web middleware. It supports all of the W3C Semantic Web recommendations for ontology languages and query languages. It is an ontology repository that includes a high performance deductive reasoning engine. Especially reasoning with rules is a major unique selling point for ontoprise. OntoBroker integrates a connector framework which makes it easy to connect a multitude of data sources like databases, web services etc. Thus it combines structured and unstructured data in one framework, OntoBroker is easy to extend and to integrate into existing IT landscapes and applications as it offers a variety of open interfaces. OntoBroker is also closely connected to ontoprise's ontology modeling environment OntoStudio which is the development environment for handling ontologies, mappings to information sources, rules, generating queries, creating business intelligence reports etc. At many customers OntoBroker serves as a common semantic layer which is accessed by various applications and integrates different information sources. OntoBroker is the run-time environment for industrial solutions like SemanticGuide, SemanticXpress, and SemanticIntegrator. As part of those meanwhile thousands of installations are in productive use.

Clinical and genomic data integration in support of biomedical research and clinical practice

Eric Neumann is a graduate from MIT and holds a PhD in neurobiology, developmental genetics, and pharmacology from Case Western Reserve University. He is a recognized expert in semantic information, and has worked on many information initiatives for the pharmaceutical and life sciences, including the W3C Semantic Web Healthcare and Life Science Interest Group (HCLSIG). Eric Neumann was the Global Head of Knowledge Management for Scientific and Medical Affairs within Sanofi-Aventis and the VP of Informatics at BG Medicine. He founded Genstruct (now Sleventa) and has also worked at Bolt, Beranek, and Newman (now BBN Technologies - Raytheon) on several advanced scientific computation projects over the span of several years. He is Founder and CTO of PanGenX, a personalized medicine company, whose mission is to optimize therapeutic care by facilitating the discovery and application of medical knowledge towards patient segmentation. Starting from the current definition of pharmacogeomics, in his talk Eric Neumann will show how it drives the personalized medicine vision, and will discuss what new forms of clinical and genomic information will be required for making clinical decision in personalized medicine. He will illustrate some available public data sources, showing what they still lack and the value of deep focus curation. He will contrast data vs. "Actionable Knowledge" and discuss how leveraging semantically linked data to help progress personalized medicine. He will also address large-scale analytics and argue about who will benefit from linked knowledge.

A semantic collaborative system for the management of translational research projects

A semantic collaborative system for the management of translational research projects

Use of Semantic Technologies - Semantic Chemistry

AbstractOur Chemical e-Science Information Cloud (ChemCloud) – a Semantic Web based eScience infrastructure – integrates and automates a multitude of databases, tools and services in the domain of chemistry, pharmacy and bio-chemistry available at the Fachinformationszentrum Chemie (FIZ Chemie), at the Freie Universitaet Berlin (FUB), and on the public Web. Based on the approach of the W3C Linked Open Data initiative and the W3C Semantic Web technologies for ontologies and rules it semantically links and integrates knowledge from our W3C HCLS knowledge base hosted at the FUB, our multi-domain knowledge base DBpedia (Deutschland) implemented at FUB, which is extracted from Wikipedia (De) providing a public semantic resource for chemistry, and our well-established databases at FIZ Chemie such as ChemInform for organic reaction data, InfoTherm the leading source for thermophysical data, Chemisches Zentralblatt, the complete chemistry knowledge from 1830 to 1969, and ChemgaPedia the largest and most frequented e-Learning platform for Chemistry and related sciences in German language.

ChemCloud: Chemical e-Science Information Cloud

AbstractOur Chemical e-Science Information Cloud (ChemCloud) – a Semantic Web based eScience infrastructure – integrates and automates a multitude of databases, tools and services in the domain of chemistry, pharmacy and bio-chemistry available at the Fachinformationszentrum Chemie (FIZ Chemie), at the Freie Universitaet Berlin (FUB), and on the public Web. Based on the approach of the W3C Linked Open Data initiative and the W3C Semantic Web technologies for ontologies and rules it semantically links and integrates knowledge from our W3C HCLS knowledge base hosted at the FUB, our multi-domain knowledge base DBpedia (Deutschland) implemented at FUB, which is extracted from Wikipedia (De) providing a public semantic resource for chemistry, and our well-established databases at FIZ Chemie such as ChemInform for organic reaction data, InfoTherm the leading source for thermophysical data, Chemisches Zentralblatt, the complete chemistry knowledge from 1830 to 1969, and ChemgaPedia the largest and most frequented e-Learning platform for Chemistry and related sciences in German language.

Countering Service Information Challenges in the Internet of Services

Business Webs apply the idea of value networks to the WWW. The underlying delivery platform is commonly referred to as the Internet of Services and will certainly have to deal with a great variety and amount of information about services along several service information dimensions. As soon as brokerage, discovery, or community feedback parts are decentralized, there emerge a number of service information challenges (modeling the information in a holistic way, documentation, interlinkage, tool interoperability, distributed querying, inconsistent information, and cooperation of different stakeholders). In this paper, we propose to counter such service information challenges by two artifacts. First, we contribute a Service Ontology based on a sound and rigid foundational ontology. The Service Ontology provides a holistic and consistent way of capturing service information. We apply the recommendations of the W3C Semantic Web Activity whose recent standardization has already opened new possibilities for tool interoperability, interlinkage of information, and distributed querying on the web. However, building and prescribing an ontology in standardized languages is not enough to address all service information challenges. Therefore, as a second contribution, we provide a method around the ontology including a governance framework, guidelines for applying the W3C Semantic Web recommendations, a lifecycle-spanning tool chain, and different levels of applicability. We label our method Semantic Business Web approach, since we build on W3C Semantic Web standards, use and extend them in the Business Web setting. Both artifacts are constructed in an interdisciplinary way by experts participating in the German lighthouse project THESEUS/TEXO. The project’s scenario also serves as a proof of concept evaluation of the artifacts.

Using social networking and semantic web technology in software engineering – Use cases, patterns, and a case study

We present an approach that uses social networking and semantic web technology to share knowledge within the software engineering community. We propose to use existing Web 2.0 services such as social bookmarking and blogs as the infrastructure to share knowledge artefacts. Due to the openness of these services, it is crucial to provide support to establish the trustworthiness of knowledge artefacts. The solution proposed is designed following the original semantic web stack architecture and uses existing and emerging W3C semantic web standards such as the Resource Description Framework (RDF), the Web Ontology Language (OWL), and the Semantic Web Rule Language (SWRL). The WebOfPatterns project is presented as a case study, which includes an Eclipse plug-in that can be used to discover design pattern definitions in social networks, to define and publish patterns, to rate patterns, to establish the trustworthiness of patterns found, and finally to scan Java projects for instances of discovered patterns. We also propose the ContributedProperties design pattern that can be used to bridge the conceptual gap between RDF resources and objects in an object-oriented programming language.

A Flexible Ontology Reasoning Architecture for the Semantic Web

Knowledge-based systems in the semantic Web era can make use of the power of the semantic Web languages and technologies, in particular those related to ontologies. Recent research has shown that user-defined data types are very useful for semantic Web and ontology applications. The W3C semantic Web best practices and development working group has set up a task force to address this issue. Very recently, OWL-Eu and OWL-E, two decidable extensions of the W3C standard ontology language OWL DL, have been proposed to support customized data types and customized data type predicates, respectively. In this paper, we propose a flexible reasoning architecture for these two expressive semantic Web ontology languages and describe our prototype implementation of the reasoning architecture, based on the well-known FaCT DL reasoner, which witnesses the two key flexibility features of our proposed architecture: 1) It allows users to define their own data types and data type predicates based on built-in ones and 2) new data type reasoners can be added into the architecture without having to change the concept reasoner

OWL-Eu: Adding Customised Datatypes Into OWL

Although OWL is rather expressive, it has a very serious limitation on datatypes; i.e., it does not support customised datatypes. It has been pointed out that many potential users will not adopt OWL unless this limitation is overcome, and the W3C SemanticWeb Best Practices and DevelopmentWorking Group has set up a task force to address this issue. This paper makes the following two contributions: (i) it provides a brief summary of OWL-related datatype formalisms, and (ii) it provides a decidable extension of OWL DL, called OWL-Eu, that supports customised datatypes. A detailed proof of the decidability of OWL-Eu is presented.

OWL-Eu: Adding customised datatypes into OWL

Although OWL is rather expressive, it has a very serious limitation on datatypes; i.e., it does not support customised datatypes. It has been pointed out that many potential users will not adopt OWL unless this limitation is overcome, and the W3C Semantic Web Best Practices and Development Working Group has set up a task force to address this issue. This paper makes the following two contributions: (i) it provides a brief summary of OWL-related datatype formalisms, and (ii) it provides a decidable extension of OWL DL, called OWL-Eu, that supports customised datatypes. A detailed proof of the decidability of OWL-Eu is presented.

DAML+OIL: an ontology language for the Semantic Web

By all measures, the Web is enormous and growing at a staggering rate, which has made it increasingly difficult-and important-for both people and programs to have quick and accurate access to Web information and services. The Semantic Web offers a solution, capturing and exploiting the meaning of terms to transform the Web from a platform that focuses on presenting information, to a platform that focuses on understanding and reasoning with information. To support Semantic Web development, the US Defense Advanced Research Projects Agency launched the DARPA Agent Markup Language (DAML) initiative to fund research in languages, tools, infrastructure, and applications that make Web content more accessible and understandable. Although the US government funds DAML, several organizations-including US and European businesses and universities, and international consortia such as the World Wide Web Consortium-have contributed to work on issues related to DAML's development and deployment. We focus on DAML's current markup language, DAML+OIL, which is a proposed starting point for the W3C's Semantic Web Activity's Ontology Web Language (OWL). We introduce DAML+OIL syntax and usage through a set of examples, drawn from a wine knowledge base used to teach novices how to build ontologies.