[apologies for the cross-posting]
*Special Issue on Exploration of IoT generated Big Data using Semantics
<http://www.journals.elsevier.com/future-generation-computer-systems/call-for-papers/scalab-special-issue-on-exploration-of-internet-of-things/>*
*Journal: *Elsevier journal on**Future Generation Computer Systems
*Impact Factor*:2.786
*Guest-Editors: *Dr Rajiv Ranjan (Newcastle University, UK), Dr
Dhaval Thakker (University of Bradford, UK), Dr Armin Haller
(Australian National University, Australia), Prof Rajkumar Buyya
(University of Melbourne, Australia)
*Schedule*
Submission due date: March 15, 2016
Notification of acceptance: July 15, 2016
Submission of final manuscript: September 15, 2016
Publication date: End of 2016 (Tentative)
*Scope and Objective*
Recent studies have shown that we generate 2.5 quintillion (2.5.1018)
bytes of data per day (Cisco and IBM) and this is set to explode to 40
yotta (40.1024) bytes by 2020 – this is 5,200 gigabytes for every person
on earth. Much of these data is and will be generated from the Internet
of Things (IoT) devices such as sensors, RFIDs, social media,
clickstreams, remote sensing satellites, business transactions,
actuators (such as machines/equipment fitted with sensors and deployed
for mining, oil exploration, or manufacturing operations), lab
instruments (e.g., high energy physics synchrotron), and smart consumer
appliances (TV, phone, etc.). This vision has recently given rise to the
notion of IoT Big Data Applications (IoTBDAs) in domains such as
Healthcare, Smart Cities, Smart Manufacturing, and Smart Energy Grids.
These IoTBDAS are required to have novel capability (currently
non-existent) of analyzing large number of dynamic data streams, tens
of years of historical data, and static knowledge about the physical
world (i.e. city map, road network map, utility network map, etc.) to
support real-time and/or near real-time decision making. The decision
making process involving such big data applications often involve
exploration for meaningful
patterns and connections. Despite the rapid evolution of IoTBDAs;;
current generation of Cloud Computing and Big Data Processing
techniques/frameworks (e.g., batch processing, stream processing, and
NoSQL) lack following very important abilities to support effective
exploration:
* Handling trajectory data
* Scalable discovery and indexing
* Automatic Integration of distributed data across different data sources
* Visualisation and navigation
* Discovering connections in data
* Summarising complex data
* Modelling and utilising context in big data
* Graph exploration
Several novel interfaces and interaction means for exploration of big
data are being proposed, for example, exploratory search systems, data
browsers, visualisation environments and knowledge graph based search
engines. Although on the rise, the current solutions are still maturing
and can benefit from computational models that aid intuitiveness and
improve the effectiveness of exploration tasks. The Semantic web and its
derivatives in the form of Linked data and Web of data can play a
crucial role in addressing various big data exploration challenges.
The main goal of this Special Issue is to explore new directions and
approaches about key research topics needed to leverage innovative
research aimed at tackling big data exploration challenges in IoTBDAs,
based on semantic technologies. We encourage the submission of work with
important theoretical and practical results, as well as case studies on
existing use of semantic technologies for big data exploration.
*Topics*
This special issue calls for original papers describing the latest
research on Semantic Technologies for Big data exploration. The
following is the proposed, non-exhaustive, list of topics addressed by
this special issue:
* Scalable knowledge driven indexing of big data
* Semantic middleware support for big data processing frameworks
* Knowledge representation techniques for aiding exploration of big data
* Methods and techniques for integration of large datasets
* Computational models using semantic technologies to discover
connections (e.g. relatedness,
* similarity, complementarity, contradictions, and causality)
* Entity and ontology summarisation methods
* Exploratory search using semantics
* Graph exploration techniques
* Visualisation and navigation techniques
* Human factors in data exploration
* User/context modelling to support personalised exploration
* Supporting learning/knowledge expansion through exploration
*Submission & Major Guidelines*
The special issue invites original research papers that make significant
contributions to the state-of-the-art in "Scalable Exploration of
Internet of Things Generated Big Data using Semantics". The papers must
not have been previously published or submitted for journal or
conference publications. However, the papers that have been previously
published with reputed conferences could be considered for publication
in the special issue if they are substantially revised from their
earlier versions with at least 30% new contents or results that comply
with the copyright regulations, if any.
Authors should prepare their manuscript according to the Guide for
Authors available from the online submission page of the Future Generate
Computer Systems at http://ees.elsevier.com/fgcs/. Authors must select
"SI: IoTBigDataExploration" when they reach the "Article Type" step in
the submission process. All papers will be peer-reviewed following the
FGCS reviewing procedures.
Every submitted paper will receive at least three reviews. The editorial
review committee will include well known experts in the area of Internet
of Things, Big Data, Semantic Web, and Cloud Databases Selection and
Evaluation Criteria:
* Significance to the readership of the journal
* Relevance to the special issue
* Originality of idea, technical contribution, and significance of the
presented results
* Quality, clarity, and readability of the written text
* Quality of references and related work
* Quality of research hypothesis, assertions, and conclusion
*Guest Editors*
Dr. Rajiv Ranjan, PhD SMIEEECS
Reader (Associate Professor) in Computing Science,
Newcastle University, United Kingdom
Visiting Scientist, Data61, CSIRO, Australia
[email protected] <mailto:[email protected]>Whttp://rajivranjan.net/
Dr. Dhaval Thakker PhD MBCS (contact person)
Lecturer in Computing,
University of Bradford, United Kingdom
Visiting Research Fellow, University of Leeds, United Kingdom
[email protected]
<mailto:[email protected]>Whttp://scim.brad.ac.uk/~dthakker/
Dr. Armin Haller
Lecturer, Research School of Accounting and Business Information Systems
Building 21, Australian National University
Canberra ACT 2601, Australia
[email protected]
<mailto:[email protected]>Whttp://www.armin-haller.com/
<http://www.armin-haller.com/>
Prof. Rajkumar Buyya
CEO, Manjrasoft Pty Ltd, Melbourne, Australia
Director, Cloud Computing and Distributed Systems Laboratory
Department of Computing and Information Systems
The University of Melbourne, Australia
[email protected] <mailto:[email protected]>Whttp://www.buyya.com/
===========================================
*Dr Dhaval Thakker*
/Lecturer in Computing/
Faculty of Engineering & Informatics
University of Bradford
Bradford, West Yorkshire, BD7 1DP, UK
Ph: +44(0)1274 23 4578
email: [email protected] <mailto:[email protected]>
web: http://scim.brad.ac.uk/~dthakker/
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