Curry, Edward and Derguech, Wassim and Hasan, Souleiman and Kouroupetroglou, Christos and ul Hassan, Umair
(2019)
A Real-time Linked Dataspace for the Internet of Things: Enabling
"Pay-As-You-Go" Data Management in Smart Environments.
Future Generation Computer Systems, 90.
pp. 405-422.
ISSN 0167-739X
Abstract
As smart environments move from a research vision to concrete manifestations in real-world enabled by
the Internet of Things, they are encountering a number of very practical challenges in data management
in terms of the flexibility needed to bring together contextual and real-time data, the interface between
new digital infrastructures and existing information systems, and how to easily share data between
stakeholders in the environment. Therefore, data management approaches for smart environments need
to support flexibility, dynamicity, incremental change, while keeping costs to a minimum. A Dataspace is
an emerging approach to data management that has proved fruitful for personal information and scientific
data management. However, their use within smart environments and for real-time data remains largely
unexplored.
This paper introduces a Real-time Linked Dataspace (RLD) as an enabling platform for data management
within smart environments. This paper identifies common data management requirements
for smart energy and water environments, details the RLD architecture and the key support services
and their tiered support levels, and a principled approach to ‘‘Pay-As-You-Go’’ data management. The
paper presents a dataspace query service for real-time data streams and entities to enable unified
entity-centric queries across live and historical stream data. The RLD was validated in 5 real-world
pilot smart environments following the OODA (Observe, Orient, Decide, and Act) Loop to build real-time
analytics, decisions support, and smart apps for energy and water management. The pilots demonstrate
that the RLD enables incremental pay-as-you-go data management with support services that simplify
the development of applications and analytics for smart environments. Finally, the paper discusses
experiences, lessons learnt, and future directions.
| Item Type: |
Article
|
| Keywords: |
Smart environments;
Data management;
Internet of Things;
Water management;
Energy management;
Dataspace;
Linked data;
Semantic web;
Event processing;
Distributed systems; |
| Academic Unit: |
Faculty of Social Sciences > School of Business |
| Item ID: |
11330 |
| Identification Number: |
https://doi.org/10.1016/j.future.2018.07.019 |
| Depositing User: |
Souleiman Hasan
|
| Date Deposited: |
17 Oct 2019 13:15 |
| Journal or Publication Title: |
Future Generation Computer Systems |
| Publisher: |
Elsevier |
| Refereed: |
Yes |
| URI: |
|
| Use Licence: |
This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available
here |
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