A model of knowledge management system for facilitating knowledge as a service (KaaS) in cloud computing environment

Knowledge as a service (KaaS) is an emerging concept that integrates knowledge management (KM), a knowledge organization, and knowledge markets. KaaS are programs that provide content-based (data, information, knowledge) as organizational outputs (e.g., advice, answers, facilitation), to meet person or external user wants or needs. KaaS are delivered through the knowledge markets as a cloud computing (CC) environment. In ensuring the services will be delivered to the right community of practice (CoP) at the right time in a proper manner, therefore there is a need of a system called knowledge management system (KMS), so that the KaaS can be well managed in a proper form by using the KM life cycle processes. These life cycle processes are including the knowledge acquisition, knowledge storage, knowledge dissemination and knowledge application. This paper presents the concept and its model for facilitating knowledge as a service (KaaS) in a KM system so that CoP can make used the knowledge from service provider as organizational output for their referencing in the context of current best practice and lesson learnt especially related to the CC environment. By using this KMS model, the community who are engaged or connected to the cloud can be easily getting the KaaS as they are wanted or to be considered for the potential purposes in achieving their goal or mission statement

Collaborative knowledge as a service applied to the disaster management domain

Cloud computing offers services which promise to meet continuously increasing computing demands by using a large number of networked resources. However, data heterogeneity remains a major hurdle for data interoperability and data integration. In this context, a Knowledge as a Service (KaaS) approach has been proposed with the aim of generating knowledge from heterogeneous data and making it available as a service. In this paper, a Collaborative Knowledge as a Service (CKaaS) architecture is proposed, with the objective of satisfying consumer knowledge needs by integrating disparate cloud knowledge through collaboration among distributed KaaS entities. The NIST cloud computing reference architecture is extended by adding a KaaS layer that integrates diverse sources of data stored in a cloud environment. CKaaS implementation is domain-specific; therefore, this paper presents its application to the disaster management domain. A use case demonstrates collaboration of knowledge providers and shows how CKaaS operates with simulation models

Data as a Service (DaaS) for sharing and processing of large data collections in the cloud

Data as a Service (DaaS) is among the latest kind of services being investigated in the Cloud computing community. The main aim of DaaS is to overcome limitations of state-of-the-art approaches in data technologies, according to which data is stored and accessed from repositories whose location is known and is relevant for sharing and processing. Besides limitations for the data sharing, current approaches also do not achieve to fully separate/decouple software services from data and thus impose limitations in inter-operability. In this paper we propose a DaaS approach for intelligent sharing and processing of large data collections with the aim of abstracting the data location (by making it relevant to the needs of sharing and accessing) and to fully decouple the data and its processing. The aim of our approach is to build a Cloud computing platform, offering DaaS to support large communities of users that need to share, access, and process the data for collectively building knowledge from data. We exemplify the approach from large data collections from health and biology domains.Peer ReviewedPostprint (author's final draft

Knowledge as a Service Framework for Disaster Data Management

Each year, a number of natural disasters strike across the globe, killing hundreds and causing billions of dollars in property and infrastructure damage. Minimizing the impact of disasters is imperative in today’s society. As the capabilities of software and hardware evolve, so does the role of information and communication technology in disaster mitigation, preparation, response, and recovery. A large quantity of disaster-related data is available, including response plans, records of previous incidents, simulation data, social media data, and Web sites. However, current data management solutions offer few or no integration capabilities. Moreover, recent advances in cloud computing, big data, and NoSQL open the door for new solutions in disaster data management. In this paper, a Knowledge as a Service (KaaS) framework is proposed for disaster cloud data management (Disaster-CDM), with the objectives of 1) storing large amounts of disaster-related data from diverse sources, 2) facilitating search, and 3) supporting their interoperability and integration. Data are stored in a cloud environment using a combination of relational and NoSQL databases. The case study presented in this paper illustrates the use of Disaster-CDM on an example of simulation models

Disaster Data Management in Cloud Environments

Facilitating decision-making in a vital discipline such as disaster management requires information gathering, sharing, and integration on a global scale and across governments, industries, communities, and academia. A large quantity of immensely heterogeneous disaster-related data is available; however, current data management solutions offer few or no integration capabilities and limited potential for collaboration. Moreover, recent advances in cloud computing, Big Data, and NoSQL have opened the door for new solutions in disaster data management. In this thesis, a Knowledge as a Service (KaaS) framework is proposed for disaster cloud data management (Disaster-CDM) with the objectives of 1) facilitating information gathering and sharing, 2) storing large amounts of disaster-related data from diverse sources, and 3) facilitating search and supporting interoperability and integration. Data are stored in a cloud environment taking advantage of NoSQL data stores. The proposed framework is generic, but this thesis focuses on the disaster management domain and data formats commonly present in that domain, i.e., file-style formats such as PDF, text, MS Office files, and images. The framework component responsible for addressing simulation models is SimOnto. SimOnto, as proposed in this work, transforms domain simulation models into an ontology-based representation with the goal of facilitating integration with other data sources, supporting simulation model querying, and enabling rule and constraint validation. Two case studies presented in this thesis illustrate the use of Disaster-CDM on the data collected during the Disaster Response Network Enabled Platform (DR-NEP) project. The first case study demonstrates Disaster-CDM integration capabilities by full-text search and querying services. In contrast to direct full-text search, Disaster-CDM full-text search also includes simulation model files as well as text contained in image files. Moreover, Disaster-CDM provides querying capabilities and this case study demonstrates how file-style data can be queried by taking advantage of a NoSQL document data store. The second case study focuses on simulation models and uses SimOnto to transform proprietary simulation models into ontology-based models which are then stored in a graph database. This case study demonstrates Disaster-CDM benefits by showing how simulation models can be queried and how model compliance with rules and constraints can be validated

Cloud-based personal knowledge management as a service (PKMaaS)

2010-2011 > Academic research: refereed > Refereed conference paperAccepted ManuscriptPublishe

Towards a methodological framework for designing a KaaS system

The paper proposes a KaaS conceptual model by using the well-known definitions of knowledge vis - vis information. Based on this KaaS model, using the principles of business model and service science, the paper proposes a representative classification KaaS business model types as well as a preliminary macro-methodological framework for designing commercially viable KaaS. The design emphasis is on distinctive KaaS value proposition for a chosen market segment, simple revenue mechanism, low cost structure, and agile value network that positions the focal firm strategically on the choke-point in the value net which locks in its customers and value partners while locking-out potential or real competitors. © 2011 IEEE

Cloud-Based Personal Knowledge Management as a service (PKMaaS)

This study tries to give a different perspective of the cloud application through a personal knowledge management perspective and its structure in the cloud computing environment. In recent years, there has been a great hype about cloud computing and different books and literature reviews have classified different types of cloud with various definitions and criteria focusing on mainly three different layers of services being infrastructure, platform and software. Instead, this paper provides a meta-observation over an integrated cloud ecosystem through the knowledge window through which a deeper insight into how the cloud, as an ecosystem, provides services that are not feasible in many conventional knowledge management approaches. Adopting a top-down approach, this study tries to illustrate the implications of the cloud at the personal levels from a knowledge-oriented perspective.Department of Industrial and Systems EngineeringRefereed conference pape