The Health-e-Waterways Project - Data Integration for Smarter, Collaborative, Whole-of-Water Cycle Management

Alabri, A.; Hunter, Jane; Ingen, Catharine van; Abal, Eva

doi:10.1109/cisis.2009.114

Cited by 2 publications

(3 citation statements)

References 1 publication

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“…Sensor networks have already proven to be useful in many areas such as environmental monitoring [ 44 , 45 ], agriculture and water monitoring [ 46 , 47 ], ecosystem monitoring [ 31 , 48 ] and coastal monitoring [ 21 , 49 ].…”

Section: Discussionmentioning

confidence: 99%

“…For example, the Hydro Dynamic model data [ 30 ] shown in Figure 5 are stored in NetCDF format and the real measurement data from a marine sensor network are stored in relational databases. Data from different sensor networks or domains [ 31 ] such as Hydrology and Weather also need to be integrated for smart query processing [ 32 ].…”

Section: Research Challenges For Smart Query Answering In Marine Sensmentioning

confidence: 99%

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Smart Query Answering for Marine Sensor Data

Shahriar

Souza

Timms

2011

Sensors

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We review existing query answering systems for sensor data. We then propose an extended query answering approach termed smart query, specifically for marine sensor data. The smart query answering system integrates pattern queries and continuous queries. The proposed smart query system considers both streaming data and historical data from marine sensor networks. The smart query also uses query relaxation technique and semantics from domain knowledge as a recommender system. The proposed smart query benefits in building data and information systems for marine sensor networks.

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Section: Discussionmentioning

confidence: 99%

Section: Research Challenges For Smart Query Answering In Marine Sensmentioning

confidence: 99%

Smart Query Answering for Marine Sensor Data

Shahriar

Souza

Timms

2011

Sensors

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“…The studies that develop and improve ontologies integrated into these systems in the water resources management domain are as follows. Alabri et al (2009) build The Ecosystem Health Monitoring Program (EHMP) ontology, the underlying water information management system, and a web portal. They create annual ecosystem report cards and generate WaterWiki.…”

Section: Water Resources Management Domain Summarymentioning

confidence: 99%

A Comprehensive Review of Ontologies in the Hydrology Towards Guiding Next Generation Artificial Intelligence Applications

Baydaroğlu¹,

Yeșilköy²,

Sermet³

et al. 2022

Preprint

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Open science presents a new approach for knowledge discovery, dissemination, and integrity. The idea behind open science is to reinforce research activities and create open knowledge networks by exploring, organizing, and sharing scientific data, as well as making research results transparent, open and integrated. Big data derived from remote sensing, ground-based measurements, models and simulations, social media and crowdsourcing, and wide variety of structured and unstructured sources requires significant efforts for data and knowledge management. Innovations and developments in information technology for the last couple of decades have made data and knowledge management possible for insurmountable amount of data collected and generated over the last decades. This enabled open knowledge networks to be built that lead to new ideas in scientific research and business world. To design and develop open knowledge networks, ontologies are essential since they form the backbone of conceptualization of a given knowledge domain. In this article, a systematic literature review is conducted to examine research involving ontologies related to hydrological processes and water resources management. The hydrologic cycle (water cycle) is a multi-component and multi-process system that is shaped by various dynamic factors. Because all components of the hydrologic cycle interact with one another and water distribution on Earth is not uniform in time and space, modeling the hydrologic cycle and management of hydrologic cycle components are complex and difficult endeavors. Ontologies in the hydrology domain support the comprehension, monitoring, and representation of the hydrologic cycle’s complex structure, as well as the predictions of its processes. They contribute to the development of necessary ontology-based information and decision support systems, the comprehension of environmental and atmospheric phenomena, the development of climate and water resiliency concepts, the creation of educational tools with artificial intelligence, and the strengthening of related cyberinfrastructures. This review provides an explanation of key issues and challenges in ontology development based on hydrologic processes to guide development of next generation artificial intelligence applications. The authors discuss future research prospects in combination with the artificial intelligence and hydroscience.

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The Health-e-Waterways Project - Data Integration for Smarter, Collaborative, Whole-of-Water Cycle Management

Cited by 2 publications

References 1 publication

Smart Query Answering for Marine Sensor Data

Smart Query Answering for Marine Sensor Data

A Comprehensive Review of Ontologies in the Hydrology Towards Guiding Next Generation Artificial Intelligence Applications

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