A Model for Integration and Interlinking of Idea Management Systems

This paper introduces the use of Semantic Web technologies for the Idea Management Systems as a gap closer between heterogeneous software and achieving interoperability. We present a model that proposes how and what kind of rich metadata annotations to apply in the domain of Idea Management Systems. In addition, as a part of our model, we present a Generic Idea and Innovation Management Ontology (GI2MO). The described model is backed by a set of use cases followed by evaluations that prove how Semantic Web can work as tool to create new opportunities and leverage the contemporary Idea Management legacy systems into the next level

OntoMathPROOntoMath^{PRO} Ontology: A Linked Data Hub for Mathematics

In this paper, we present an ontology of mathematical knowledge concepts that covers a wide range of the fields of mathematics and introduces a balanced representation between comprehensive and sensible models. We demonstrate the applications of this representation in information extraction, semantic search, and education. We argue that the ontology can be a core of future integration of math-aware data sets in the Web of Data and, therefore, provide mappings onto relevant datasets, such as DBpedia and ScienceWISE.Comment: 15 pages, 6 images, 1 table, Knowledge Engineering and the Semantic Web - 5th International Conferenc

2100 AI: Reflections on the mechanisation of scientific discovery

The pace of research is nowadays extremely intensive, with datasets and publications being published at an unprecedented rate. In this context data science, artificial intelligence, machine learning and big data analytics are providing researchers with new automatic techniques which not only help them to manage this flow of information but are also able to identify automatically interesting patterns and insights in this vast sea of information. However, the emergence of mechanised scientific discovery is likely to dramatically change the way we do science, thus introducing and amplifying serious societal implications on the role of researchers themselves, which need to be analysed thoroughly

Semantic data mining and linked data for a recommender system in the AEC industry

Even though it can provide design teams with valuable performance insights and enhance decision-making, monitored building data is rarely reused in an effective feedback loop from operation to design. Data mining allows users to obtain such insights from the large datasets generated throughout the building life cycle. Furthermore, semantic web technologies allow to formally represent the built environment and retrieve knowledge in response to domain-specific requirements. Both approaches have independently established themselves as powerful aids in decision-making. Combining them can enrich data mining processes with domain knowledge and facilitate knowledge discovery, representation and reuse. In this article, we look into the available data mining techniques and investigate to what extent they can be fused with semantic web technologies to provide recommendations to the end user in performance-oriented design. We demonstrate an initial implementation of a linked data-based system for generation of recommendations

Linked Data - the story so far

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

The road from community ideas to organisational innovation: A life cycle survey of idea management systems

This paper introduces a new emerging software component, the idea management system, which helps to gather, organise, select and manage the innovative ideas provided by the communities gathered around organisations or enterprises. We define the notion of the idea life cycle, which provides a framework for characterising tools and techniques that drive the evolution of community submitted data inside idea management systems. Furthermore, we show the dependencies between the community-created information and the enterprise processes that are a result of using idea management systems and point out the possible benefits

Cloudbus Toolkit for Market-Oriented Cloud Computing

This keynote paper: (1) presents the 21st century vision of computing and identifies various IT paradigms promising to deliver computing as a utility; (2) defines the architecture for creating market-oriented Clouds and computing atmosphere by leveraging technologies such as virtual machines; (3) provides thoughts on market-based resource management strategies that encompass both customer-driven service management and computational risk management to sustain SLA-oriented resource allocation; (4) presents the work carried out as part of our new Cloud Computing initiative, called Cloudbus: (i) Aneka, a Platform as a Service software system containing SDK (Software Development Kit) for construction of Cloud applications and deployment on private or public Clouds, in addition to supporting market-oriented resource management; (ii) internetworking of Clouds for dynamic creation of federated computing environments for scaling of elastic applications; (iii) creation of 3rd party Cloud brokering services for building content delivery networks and e-Science applications and their deployment on capabilities of IaaS providers such as Amazon along with Grid mashups; (iv) CloudSim supporting modelling and simulation of Clouds for performance studies; (v) Energy Efficient Resource Allocation Mechanisms and Techniques for creation and management of Green Clouds; and (vi) pathways for future research.Comment: 21 pages, 6 figures, 2 tables, Conference pape

Trustworthiness in Social Big Data Incorporating Semantic Analysis, Machine Learning and Distributed Data Processing

This thesis presents several state-of-the-art approaches constructed for the purpose of (i) studying the trustworthiness of users in Online Social Network platforms, (ii) deriving concealed knowledge from their textual content, and (iii) classifying and predicting the domain knowledge of users and their content. The developed approaches are refined through proof-of-concept experiments, several benchmark comparisons, and appropriate and rigorous evaluation metrics to verify and validate their effectiveness and efficiency, and hence, those of the applied frameworks

Collective IT artifacts: Toward Inclusive Crisis Infrastructures

This paper investigates a previously overlooked phenomenon in crisis response information systems, namely inclusive crisis infrastructure. By expanding the well-acknowledged infrastructure concept with alternatives to understand the nature and scope of inclusive crisis infrastructures, this paper contributes to closing the gap between theory and practice by raising some research questions critical to the study of inclusive crisis infrastructures. The emerging literature on crisis response information systems suggests that external sourcing of information increasingly influences crisis response operations. To contribute to this discourse, the paper draws on Pipek and Wulf’s (2009) definition of work infrastructures and Palen and Liu’s (2007) conceptualization of peer-to-peer communications to develop a better understanding of the crisis response arena as a whole. In doing so, this paper goes beyond the emphasis on event-based technologies that currently dominate the crisis response information systems literature and instead argues why crisis infrastructures need to be both inward-looking and accommodating to technological and social outcomes parallel to formal response contexts. The novel conceptualization captures the fact that the crisis context contains collections of collective IT artifacts that are not aligned or related but that are, for autonomy reasons, interlinked to crisis organizations’ current IT infrastructure and may be of great value to such organizations if infrastructure capability options are considered