Mark Roantree

Data transformation and query management in personal health sensor networks

Sensor technology has been exploited in many application areas ranging from climate monitoring, to traffic management, and healthcare. The role of these sensors is to monitor human beings, the environment or instrumentation and provide continuous streams of information regarding their status or well being. In the case study presented in this work, the network is provided by football teams with sensors generating continuous heart rate values during a number of different sporting activities. In wireless networks such as these, the requirement is for methods of data management and transformation in order to present data in a format suited to high level queries. In effect, what is required is a traditional database-style query interface where domain experts can continue to probe for the answers required in more specialised environments. The challenge arises from the gap that emerges between the low level sensor output and the high level user requirements of the domain experts. This paper describes a process to close this gap by automatically harvesting the raw sensor data and providing semantic enrichment through the addition of context data.

Querying Distributed Data in a Super-Peer Based Architecture

Data integration is a significant challenge: relevant data objects are split across multiple information sources, and often owned by different organizations. The sources represent, maintain, and export the information using a variety of formats, interfaces and semantics. This paper addresses the issue of querying distributed data in a large scale context. We present a p2p information mediation framework based on the notion of super-peers, providing a super-peer network. This makes it possible for a super-peer to reach every other peer (data source) in the system, thus realizing the concept of a integrated schema formed from all possible information sources. This is achieved by classifying data sources into domains and creating user profiles for query optimization purposes.

The OASIS multidatabase prototype

The OASIS Prototype is under development at Dublin City University in Ireland. We describe a multi-database architecture which uses the ODMG model as a canonical model and describe an extention for construction of virtual schemas within the multidatabase system. The OMG model is used to provide a standard distribution layer for data from local databases. This takes the form of CORBA objects representing export schemas from separate data sources.

Using a Metadata Software Layer in Information Systems Integration

A Federated Information System requires that multiple (often heterogenous) information systems are integrated to an extent that they can share data. This shared data often takes the form of a federated schema, which is a global view of data taken from distributed sources. One of the issues faced in the engineering of a federated schema is the continuous need to extract metadata from cooperating systems. Where cooperating systems employ an object-oriented common model to interact with each other, this requirement can become a problem due to the type and complexity of metadata queries. In this research, we specified and implemented a metadata software layer in the form of a high-level query interface for the ODMG schema repository, in order to simplify the task of integration system engineers. Two clears benefits have emerged: the reduced complexity of metadata queries during system integration (and federated schema construction) and a reduced learning curve for programmers who need to use the ODMG schema repository.

Desirable properties for XML update mechanisms

The adoption of XML as the default data interchange format and the standardisation of the XPath and XQuery languages has resulted in significant research in the development and implementation of XML databases capable of processing queries efficiently. The ever-increasing deployment of XML in industry and the real-world requirement to support efficient updates to XML documents has more recently prompted research in dynamic XML labelling schemes. In this paper, we provide an overview of the recent research in dynamic XML labelling schemes. Our motivation is to define a set of properties that represent a more holistic dynamic labelling scheme and present our findings through an evaluation matrix for most of the existing schemes that provide update functionality.

Capturing Personal Health Data from Wearable Sensors

Recently, there has been a significant growth in pervasive computing and ubiquitous sensing which strives to develop and deploy sensing technology all around us. We are also seeing the emergence of applications such as environmental and personal health monitoring to leverage data from a physical world. Most of the developments in this area have been concerned with either developing the sensing technologies, or the infrastructure (middleware) to gather this data and the issues which have been addressed include power consumption on the devices, security of data transmission, networking challenges in gathering and storing the data and fault tolerance in the event of network and/or device failure. Research is focusing on harvesting and managing data and providing query capabilities.

Wireless temperature logging technology for the fishing industry

A system for autonomous temperature logging of fish catches is described. The system is completely wireless and is comprised of a number of loggers, in individual fish boxes, and a base station, assigned to a particular trawler. The temperature of the fish is monitored by the loggers, which contain a thermistor and RF transmitter circuitry. The data is sent at fixed intervals (usually 5 minutes) to the base station. Through a GSM modem, the base station communicates the collected data to the shore where a server uploads the temperature-time information to a database. The database and controlling software are completely Web-based and can be accessed by an Internet-enabled PC, laptop or PDA. This allows remote initiation and control of the system, in addition to querying of the database. To date, successful trials have been conducted for salmon, mackerel and whelk fishing off the Irish coast.

Integrating Sensor Streams in pHealth Networks

Personal Health (pHealth) sensor networks are generally used to monitor the well being of both athletes and the general public to inform health specialists of future and often serious ailments. The problem facing these domain experts is the scale and quality of data they must search in order to extract meaningful results. By using peer-to-peer sensor architectures and a mechanism for reducing the search space, we can, to some extent, address the scalability issue. However, synchronisation and normalisation of distributed sensor streams remains a problem in many networks. In the case of pHealth sensor networks, it is crucial for experts to align multiple sensor readings before query or data mining activities can take place. This paper presents a system for clustering and synchronising sensor streams in preparation for user queries.

Metadata Modelling for Healthcare Applications in a Federated Database System

One of the problems facing federated database management systems is how to handle change among entities in the federation. Change can occur when a new site is added to the federation, a new set of security privileges is introduced, or one of the schemas has been modified. One powerful mechanism for constructing an adaptive federated architecture is metadata. Mowbray [MZ95] describes metadata as self-descriptive definition of services and information. In this article we present our ideas for modelling federation metadata in the LIOM project.

A path-oriented RDF index for keyword search query processing

Most of the recent approaches to keyword search employ graph structured representation of data. Answers to queries are generally sub-structures of the graph, containing one or more keywords. While finding the nodes matching keywords is relatively easy, determining the connections between such nodes is a complex problem requiring on-the-fly time consuming graph exploration. Current techniques suffer from poorly performing worst case scenario or from indexing schemes that provide little support to the discovery of connections between nodes. In this paper, we present an indexing scheme for RDF that exposes the structural characteristics of the graph, its paths and the information on the reachability of nodes. This knowledge is exploited to expedite the retrieval of the substructures representing the query results. In addition, the index is organized to facilitate maintenance operations as the dataset evolves. Experimental results demonstrates the feasibility of our index that significantly improves the query execution performance.