16,830 research outputs found
Referent tracking for corporate memories
For corporate memory and enterprise ontology systems to be maximally useful,
they must be freed from certain barriers placed around them by traditional
knowledge management paradigms. This means, above all, that they must mirror
more faithfully those portions of reality which are salient to the workings of the
enterprise, including the changes that occur with the passage of time. The purpose
of this chapter is to demonstrate how theories based on philosophical realism can
contribute to this objective. We discuss how realism-based ontologies (capturing
what is generic) combined with referent tracking (capturing what is specific) can
play a key role in building the robust and useful corporate memories of the future
An Ontology-centered Approach for Designing an Interactive Competence Management System for IT Companies
The paper presents a generic framework for an intelligent information system of competence management based on ontologies for information technology companies. In a first step it will be applied in an information technology (IT) small enterprise and then its applicability will be verified for other organizations of the same type. The work presented in the paper is performed under the project "CONTO â Ontology-based Competencies Management in Information Technology" funded by the Romanian Ministry of Education and Research, involving two universities, a research institute and an IT private company. A competence management system (CMS), in our vision has to achieve three functions: (a) to support the complete and systematic acquisition of knowledge about the competence of the members of an enterprise; (b) to provide the knowledge about competences and their owners; (c) to apply the available knowledge to serve a purpose. The core of the competence management information system is an ontology that plays the role of the declarative knowledge repository containing the basic concepts (such as: company-job, competence, domain, group, person etc.) and their relationships with other concepts, instances and properties. The ProtĂ©gĂ© environment was used for the development of this ontology. The structure of the ontology is conceived so that description logics can be used to represent the concept definitions of the application domain in a structured and formally well-understood way. Knowledge acquisition is performed in our approach by enriching the ontology, according to the requirements of the IT company. An advantage of using an ontology-based system is the possibility of the identification of new relations among concepts based on inferences starting from the existing knowledge. The user can choose to query instances of one type of concept. The paper also presents some use-cases
Ontology-based employer demand management
Skills shortages globally pose a real and urgent need for proper investigation and workforce development planning into the future. Analysing workforce development and employer demand needs through electronic job market allows much deeper and wider research into skill shortages. Current methods do not provide the level of depth required to address such important economic implications. In this paper, we present a system aiming to gather and analyse current employer demand information from online job advertisements. It identifies current employer demand needs analysed from electronic job market
Managing corporate memory on the semantic web
Corporate memory (CM) is the total body of data, information and knowledge required to deliver the strategic aims and objectives of an organization. In the current market, the rapidly increasing volume of unstructured documents in the enterprises has brought the challenge of building an autonomic framework to acquire, represent, learn and maintain CM, and efficiently reason from it to aid in knowledge discovery and reuse. The concept of semantic web is being introduced in the enterprises to structure information in a machine readable way and enhance the understandability of the disparate information. Due to the continual popularity of the semantic web, this paper develops a framework for CM management on the semantic web. The proposed approach gleans information from the documents, converts into a semantic web resource using resource description framework (RDF) and RDF Schema and then identifies relations among them using latent semantic analysis technique. The efficacy of the proposed approach is demonstrated through empirical experiments conducted on two case studies. © 2014 Springer Science+Business Media New York
Propelling the Potential of Enterprise Linked Data in Austria. Roadmap and Report
In times of digital transformation and considering the potential of the data-driven
economy, it is crucial that data is not only made available, data sources can be trusted,
but also data integrity can be guaranteed, necessary privacy and security mechanisms
are in place, and data and access comply with policies and legislation. In many cases,
complex and interdisciplinary questions cannot be answered by a single dataset and
thus it is necessary to combine data from multiple disparate sources. However, because
most data today is locked up in isolated silos, data cannot be used to its fullest
potential.
The core challenge for most organisations and enterprises in regards to data exchange
and integration is to be able to combine data from internal and external data sources
in a manner that supports both day to day operations and innovation. Linked Data is a
promising data publishing and integration paradigm that builds upon standard web
technologies. It supports the publishing of structured data in a semantically explicit
and interlinked manner such that it can be easily connected, and consequently becomes
more interoperable and useful.
The PROPEL project - Propelling the Potential of Enterprise Linked Data in Austria - surveyed technological challenges, entrepreneurial opportunities, and open research
questions on the use of Linked Data in a business context and developed a roadmap and a set of recommendations for policy makers, industry, and the research community.
Shifting away from a predominantly academic perspective and an exclusive focus on open data, the project looked at Linked Data as an emerging disruptive technology
that enables efficient enterprise data management in the rising data economy. Current market forces provide many opportunities, but also present several data and
information management challenges. Given that Linked Data enables advanced analytics and decision-making, it is particularly suitable for addressing today's data and
information management challenges. In our research, we identified a variety of highly promising use cases for Linked Data in an enterprise context. Examples of promising
application domains include "customization and customer relationship management", "automatic and dynamic content production, adaption and display", "data search, information
retrieval and knowledge discovery", as well as "data and information exchange and integration". The analysis also revealed broad potential across a large spectrum of
industries whose structural and technological characteristics align well with Linked
Data characteristics and principles: energy, retail, finance and insurance, government, health, transport and logistics, telecommunications, media, tourism, engineering, and research and development rank among the most promising industries for the adoption of Linked Data principles.
In addition to approaching the subject from an industry perspective, we also examined the topics and trends emerging from the research community in the field of Linked Data and the Semantic Web. Although our analysis revolved around a vibrant and active community composed of academia and leading companies involved in semantic technologies, we found that industry needs and research discussions are
somewhat misaligned. Whereas some foundation technologies such as knowledge representation and data creation/publishing/sharing, data management and system
engineering are highly represented in scientific papers, specific topics such as recommendations, or cross-topics such as machine learning or privacy and security are marginally
present. Topics such as big/large data and the internet of things are (still) on an
upward trajectory in terms of attention. In contrast, topics that are very relevant for
industry such as application oriented topics or those that relate to security, privacy
and robustness are not attracting much attention. When it comes to standardisation
efforts, we identified a clear need for a more in-depth analysis into the effectiveness of
existing standards, the degree of coverage they provide with respect the foundations
they belong to, and the suitability of alternative standards that do not fall under the
core Semantic Web umbrella.
Taking into consideration market forces, sector analysis of Linked Data potential, demand
side analysis and the current technological status it is clear that Linked Data
has a lot of potential for enterprises and can act as a key driver of technological, organizational,
and economic change. However, in order to ensure a solid foundation
for Enterprise Linked Data include there is a need for: greater awareness surrounding
the potential of Linked Data in enterprises, lowering of entrance barriers via education
and training, better alignment between industry demands and research activities,
greater support for technology transfer from universities to companies.
The PROPEL roadmap recommends concrete measures in order to propel the adoption
of Linked Data in Austrian enterprises. These measures are structured around five
fields of activities: "awareness and education", "technological innovation, research gaps,
standardisation", "policy and legal", and "funding". Key short-term recommendations include the clustering of existing activities in order to raise visibility on an international level, the funding of key topics that are under represented by the community, and the setup of joint projects. In the medium term, we recommend the strengthening
of existing academic and private education efforts via certification and to establish flagship projects that are based on national use cases that can serve as blueprints for transnational initiatives. This requires not only financial support, but also infrastructure support, such as data and services to build solutions on top. In the long term, we
recommend cooperation with international funding schemes to establish and foster a European level agenda, and the setup of centres of excellence
Co-creation in service assemblages for service innovation : an empirical investigation
Co-creation could enhance service innovation (Perks, Gruber, and Edvardsson, 2012). Despite the research conducted on co-creation, the issue concerning how actors could form service system with high density still needs to be addressed (Michel, Vargo and Lusch, 2008). We conceptualized service system as an assemblage and investigated emergence and dynamic process of assemble and dissemble of service assemblages by drawing on theories of co-creation, affordance, task network and modularity and the notion of assemblage (Delanda, 2006). We developed a framework and empirically examined how to map the competences required for actors in a task network and how capacities could be optimally (re)configured as assemblages (clusters) for value co-creation. We demonstrated that the framework developed could be applied to formation, reformation of service assemblages for design of service offerings enabling optimal value co-creation
Application of an Enterprise Modelling approach to deploy Systems Engineering processes in large organizations
Enterprise Modelling (EM) enables the representation of companies' activities, of their resources along with their roles and responsibilities in order to share the company's knowledge and support performance analysis. For this, EM promotes various concepts, techniques, frameworks, modelling languages and tools today widely used in companies. Currently, even a partial model of an enterprise constitutes a way to communicate, to share advices, to analyse and to make decisions. Therefore, EM appears to be a privileged tool to support any business change management. In a complementary way, Systems Engineering (SE) is a tried and tested methodological approach to design and test new products whatever their complexity or nature. Nowadays SE is considered in industry as a competitive and structured approach enabling a company to manage design activities and more generally to improve its capacity and ability to design complex systems efficiently. SE acts as a model-based engineering approach and promotes to this end a set of standardized collaborative processes, modelling languages and frameworks. Thus, when considering large companies designing complex systems such as a helicopter manufacturer, first it appears critical to be able to adapt processes proposed by SE standardization according to the business specific needs. This tailoring must be guided in order to consider the inherent complexity of the organization, the various human actors' profiles and skills, tools and stakeholders involved in the design of new products. As they all have to communicate and interact efficiently together their abilities and capacities to be interoperable i.e. to really work together should be analysed and improved accordingly before going further. Then, it appears necessary to prepare the company for the required changes, and to deploy in situ the adopted SE processes taking into account not only company's classical constrains and objectives but also the current level of interoperability of its elements. Finally, company managers must become able to control and adjust these processes from the cradle to the grave according to feedbacks from their stakeholders. To support all these activities, Enterprise Modelling (EM) provides several techniques, modelling languages, reference models and interoperability assessment methods which have been adapted and applied in this research work. The purpose of this article is threefold: 1) to provide a state of the art in interoperability, Systems Engineering (SE), and EM to illustrate how these disciplines are interrelated, to identify the needs they imply in the deployment, to discuss lacks in existing works considering these needs and thus to formulate how we aim to meet them, 2) to present an approach based on EM helping companies to lead changes required to apply SE principles and aiming to promote interoperability; and 3) to introduce the modelling environment proposed to support the approach including an ontology, an extension of BPMN 2.0 and software tools
Improvement of a Document Retrieval System for the Supply Chain domain
Aquest projecte s'enmarca en el context del projecte Europeu "Semantically Connected Semiconductor Supply Chains (SC3)". Es farĂ Ășs de Natural Language Processing i Semantic Web , adaptant les tĂšcniques per a poder referenciar documents de la cadena de producciĂł per un pilot en cadenes de subministrament de semiconductors. En aquest projecte s'utilitzaran conjuntament tecnologies de web semĂ ntica (fent Ășs d'ontologies) i de Deep Learning (amb BERT/SBERT en pyTorch).This project is framed in the context of the European project "Semantically Connected Semiconductor Supply Chains (SC3)". Natural Language Processing and Semantic Web will be used, adapting the techniques to be able to reference documents from the production chain by a pilot in semiconductor supply chains. This project will use semantic web technologies (using ontologies) and Deep Learning (with BERT / SBERT in pyTorch) together
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