[Download PDF version of CFP]

Call for Papers

The conference is preceded by one day of free tutorials for participants who wish to learn state of the art of research relating to the topics of KMO and LTEC. The tutorials will be held on 24thJuly, 2016. The conference itself commences on the 25th July, 2016.
Knowledge Management is in the midst of a revolution. Traditional KM approaches have failed to meet the challenges posed by Big Data, mobility, social media, and customer demands. That’s because the knowledge critical for customer service is everywhere, and new approaches are required to tap into its value.

The way knowledge management of an organization, is handled, has undergone significant changes. New kinds of data, new techniques, new demands, and the plethora of data is forcing organizations to reformulate their strategies to achieve an interactive, distributed and collaborative environment. Technology has had a tremendous impact on knowledge management (KM), inspiring the development of robust software platforms to leverage KM strategies. Many new trends and technologies have emerged, such as Enterprise 2.0; Semantic Web (Web 3.0); Ubiquitous Technologies; big data, social networking, cloud computing, mobile technologies, and internet of things.

There is a strong relationship between innovation, technology and knowledge management. ICTs have great influence on KM, and therefore any innovation in ICTs directly linked to creativity in knowledge management. Collaboration is essential in an economy based on highly specialised knowledge. There is a need to focus on fostering collaboration between individuals, teams, divisions, and organisations. It is important that we develop the skills and culture that enable high-value collaboration. Implementing a whole new set of businesses processes is also required to unlock the full potential of collaboration for knowledge management.

Knowledge management is not only limited to technology, but it is the integration of business strategy and process, organizational community and culture, expertise and technology. The knowledge society is helping us to produce better products and services that provide values to society. How do we develop products and services that will meet the values of the users? To do this requires that we look into the new emerging discipline of service science especially   service dominant logic. Co-creation of value is essential to provide services and products that will provide vales to users.

Research contributions from the above different aspects will enlighten industry on how to handle the various organizational and technical opportunities and challenges in knowledge management. KMO 2016 aims to encourage research into the various aspects of knowledge management especially in new research and manuscripts involving emerging issues, challenges and trends. These and other related topics will be discussed and explored at the 11th KMO conference. The intent is to create a better understanding of knowledge management practices, research and practical applications.

Continuing the success of the KMO conference series since 2005, KMO 2016 conference will provide an international communication forum bringing together academia and industry for discussing the progress made and addressing the challenges faced by knowledge management. The conference committee welcomes contributions on a wide range of topics from a range of scholarly approaches including theoretical, technical, practical and empirical papers as well as by innovative ideas and experiences. We are also interested in case studies that demonstrate how KM research strategies have been applied and the lessons learned. Case studies and work-in-progress/posters are welcomed. PhD Research, proposals for roundtable discussions, non-academic contributions and product demonstrations based on the main themes are also invited.

Topics in KMO include, but are not limited to:

Knowledge management in general

  • Dynamic Knowledge Integration and Visualization
  • Enterprise 2.0 Knowledge Management Development
  • Knowledge resource – intellectual capital
  • Knowledge Management Paradigm
  • Knowledge visualization for knowledge management and business modelling
  • KM for Healthcare
  • KM for Smart cities
  • Knowledge Representation and Reasoning
  • Knowledge discovery in databases
  • Knowledge engineering and management
  • Security and intrusion detection in KM
  • Ontology and knowledge representation
  • Tacit knowledge capture and dissemination
  • Knowledge creation and sharing mechanisms
  • Knowledge management strategies, resources and competencies
  • Methodology and best practices to implement big data driven KM
  • Application of knowledge representation techniques to semantic modelling
  • Measurement and evaluation of KM effectiveness
  • Knowledge Management in Practice
  • Change management, KM in business transformation
  • Case studies and best practices
  • KM in SME’s

Internet of Things

  • Formal verification and model-checking for Internet of Things applications
  • Knowledge representation models in the Internet of Things
  • Business information processing and business models in the Internet of Things
  • Management information systems of the Internet of Things
  • Knowledge retrieving and sharing mechanisms in the Internet of Things
  • Integration of heterogeneous information for the Internet of Things
  • Reasoning algorithms for the knowledge systems in the Internet of Things
  • Knowledge representation models in the Internet of Things
  • Governance, Ethics and Trust in IoT and Big Data in KM
  • Software engineering in the Internet of Things
  • Service oriented computing in the Internet of Things
  • Mobile tracking services in the Internet of Things
  • Context Awareness in the Internet of Things
  • Enterprise knowledge management in the Internet of Things
  • Service oriented computing in the Internet of Things
  • Privacy protection and security issues of the Internet of Things
  • Intelligent applications of the Internet of Things
  • Technologies of data management and integration in the Internet of Things
  • Data Mining in the Internet of Things
  • Interoperability including Semantic interoperability in the Internet of Things
  • Business models for the Internet of Things
  • Development methodologies for IoT-based applications
  • IoT for health
  • Organizational semiotics
  • Testing, debugging, validation, and QoS modelling of Internet of Things applications

Big Data and Cloud Computing

  • Big Data Computing for Knowledge Management
  • Mobile Data Communications
  • Business models on Big Data applications
  • Supply chain of big data and data products
  • Real-time data mining in mobile internet
  • Web 2.0 and Data Mining
  • Data and Knowledge Interoperability and Exchange
  • Semantic web data management
  • Large-scale network data analysis
  • Large data stream processing on cloud
  • Large incremental datasets on cloud
  • Open source real-time computing system for data mining
  • Security and privacy in Big Data
  • Knowledge Acquisition and Discovery (AI, Data Mining, Text and Web Mining
  • Knowledge Organization (Meta Data, Taxonomies and Ontology)
  • Theoretical development of Big Data
  • Volume, velocity and variety of Big Data on cloud
  • Cloud computing, peer-to-peer, parallel and distributed databases
  • Big data and innovation
  • Data and Knowledge Modeling
  • Use Cases and Applications in Knowledge and Big Data analytics
  • Data mining theory, methods, and applications
  • Data warehousing and business intelligence
  • Big Data theory
  • Big data analytics
  • Big Data applications
  • Big Data processing tools
  • Big Data visualization
  • Big Data management
  • Big data and smart city
  • KM and Data Security
  • Case studies of big data mining applications for providing online customer support
  • Big data for knowledge management
  • Capture of big data for knowledge management
  • Big data and knowledge extraction
  • New algorithmic approaches to Big Data
  • Big data and knowledge sharing
  • Privacy Preserving Big Data Collection / Analytics
  • Big data on cloud
  • Big Data Computing for Knowledge Management
  • KM in the Cloud
  • Privacy preserving on cloud

Social and Organizational aspects

  • Social networks analysis
  • Algorithms for developing user profiles
  • Knowledge Management and supply chains
  • Benefits and Challenges in Adopting KM in the Public Sector
  • KM in Education
  • The role of KM in Tourism
  • KM and Sustainable Competitive Advantage
  • Social Networks Analysis
  • KM, HR and Organizational Culture
  • Social Networks Extraction and Construction
  • KM and Organizational Structures
  • Knowledge Management and Knowledge Networks
  • Value Creation through Knowledge
  • Transferring Critical Knowledge to Maintain Competitiveness
  • Best practices and communities of practice
  • Intellectual capital
  • Business Process Management
  • Requirements Engineering
  • Competitive and Business Intelligence
  • Social Media and Social Network Technologies
  • Social media analytics
  • Business forecasting
  • Knowledge management in innovative applications, such as healthcare information and network
  • Security intelligence
  • Knowledge Creation
  • Organizational Memory
  • Big Data sharing Knowledge Analytics Framework and Architecture
  • Customer Knowledge in Innovation
  • Customer Knowledge Management
  • Managing Knowledge for Global and Collaborative Innovations
  • Co-production of Knowledge
  • Knowledge Management for Social Change and Innovation
  • The Impacts of Knowledge Management in the Organization
  • E-government
  • Intelligent and Multi-agent Control Systems

Innovation, Evaluation and Services 

  • Innovative business models
  • Innovation and Knowledge
  • Innovation Management in the Public Sector Through KM
  • Re-thinking Knowledge Management
  • Innovative Processes and Models
  • Innovation in Education and Training
  • Practical examples of services innovation
  • Mobile Data Communications
  • KM Implementation Challenges and Opportunities
  • Knowledge Assets
  • Knowledge Measurement and Evaluation
  • Knowledge Sharing
  • Dynamic Knowledge Integration and Visualization
  • Knowledge Creation through Crowdsourcing
  • Social computing and knowledge management
  • Service Science
  • Management and Business Intelligence
  • Information security and knowledge protection
  • Web Services, Grid Services and Service-Oriented Computing
  • Knowledge Representation
  • Knowledge Evaluation
  • KM Tools and Techniques
  • Knowledge Quality Estimation and Uncertainty Handling
  • The Role of Semantic Web in Software and Service Development
  • Intelligent information systems
  • Modeling of service, industrial, and environmental processes
  • Predictive analytics
  • Semantic and Entity-Based Information Retrieval
  • Machine Learning for IR