Medical Informatics Europe Conference

Kerstin Forsberg presenting at MIE 2014

Kerstin presenting at MIE 2014

The MIE conference is in full swing this week in Istanbul I thought it time to share our paper on mapping medical terminologies [1].

The paper was collaborative effort combining input from EU IMI funded projects EHR4CR, SALUS and Open PHACTS as well as the W3C Health Care and Life Sciences Interest Group (HCLS).

Below are Kerstin’s slides.
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[1] [doi] S. Hussain, H. Sun, A. Sinaci, G. B. L. Erturkmen, C. Mead, A. J. G. Gray, D. Mcguinness, E. Prud’hommeaux, C. Daniel, and K. Forsberg, “A framework for evaluating and utilizing medical terminology mappings,” in 25th Eur. Med. Informatics Conf. – MIE2014, Istanbul, Turkey, 2014, pp. 594-598.
[Bibtex]
@inproceedings{Hussain2014,
abstract = {Use of medical terminologies and mappings across them are considered to be crucial pre-requisites for achieving interoperable eHealth applications. Built upon the outcomes of several research projects, we introduce a framework for evaluating and utilizing terminology mappings that offers a platform for i) performing various mappings strategies, ii) representing terminology mappings together with their provenance information, and iii) enabling terminology reasoning for inferring both new and erroneous mappings. We present the results of the introduced framework from SALUS project where we evaluated the quality of both existing and inferred terminology mappings among standard terminologies.},
address = {Istanbul, Turkey},
author = {Hussain, Sajjad and Sun, Hong and Sinaci, Anil and Erturkmen, Gokce Banu Laleci and Mead, Charles and Gray, Alasdair J G and Mcguinness, Deborah and Prud'hommeaux, Eric and Daniel, Christel and Forsberg, Kerstin},
booktitle = {25th Eur. Med. Informatics Conf. - MIE2014},
doi = {10.3233/978-1-61499-432-9-594},
month = aug,
pages = {594--598},
title = {{A framework for evaluating and utilizing medical terminology mappings}},
url = {http://ebooks.iospress.nl/volumearticle/37557},
year = {2014}
}

SensorBench SICSA Presentation

SensorBench [1] is a benchmark suite for wireless sensor networks. The design of wireless sensor network systems sits within a multi-dimensional design space, where it can be difficult to understand the implications of specific decisions and to identify optimal solutions. SensorBench enables the systematic analysis and comparison of different techniques and platforms, enabling both development and user communities to make well informed choices. The benchmark identifies key variables and performance metrics, and specifies experiments that explore how different types of task perform under different metrics for the controlled variables. The benchmark is demonstrated by its application on representative platforms.

[1] [pdf] [doi] I. Galpin, A. B. Stokes, G. Valkanas, A. J. G. Gray, N. W. Paton, A. A. A. Fernandes, K. Sattler, and D. Gunopulos, “SensorBench: benchmarking approaches to processing wireless sensor network data,” in Proceedings of the 26th International Conference on Scientific and Statistical Database Management (SSDBM2014), 2014, p. 21.
[Bibtex]
@inproceedings{SensorBenchSSDBM2014,
abstract = {Wireless sensor networks enable cost-effective data collection for tasks such as precision agriculture and environment monitoring. However, the resource-constrained nature of sensor nodes, which often have both limited computational capabilities and battery lifetimes, means that applications that use them must make judicious use of these resources. Research that seeks to support data intensive sensor applications has explored a range of approaches and developed many different techniques, including bespoke algorithms for specific analyses and generic sensor network query processors. However, all such proposals sit within a multi-dimensional design space, where it can be difficult to understand the implications of specific decisions and to identify optimal solutions. This paper presents a benchmark that seeks to support the systematic analysis and comparison of different techniques and platforms, enabling both development and user communities to make well informed choices. The contributions of the paper include: (i) the identification of key variables and performance metrics; (ii) the specification of experiments that explore how different types of task perform under different metrics for the controlled variables; and (iii) an application of the benchmark to investigate the behavior of several representative platforms and techniques.},
author = {Ixent Galpin and
Alan B. Stokes and
George Valkanas and
Alasdair J. G. Gray and
Norman W. Paton and
Alvaro A. A. Fernandes and
Kai-Uwe Sattler and
Dimitrios Gunopulos},
title = {SensorBench: benchmarking approaches to processing wireless
sensor network data},
booktitle = {Proceedings of the 26th International Conference on Scientific and Statistical Database Management ({SSDBM2014})},
doi = {10.1145/2618243.2618252},
year = {2014},
pages = {21},
web = {http://doi.acm.org/10.1145/2618243.2618252},
}

SensorBench SSDBM Paper

The SensorBench paper [1] will be presented this week at the 26th International Conference on Scientific and Statistical Database Management (SSDBM).

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[1] [pdf] [doi] I. Galpin, A. B. Stokes, G. Valkanas, A. J. G. Gray, N. W. Paton, A. A. A. Fernandes, K. Sattler, and D. Gunopulos, “SensorBench: benchmarking approaches to processing wireless sensor network data,” in Proceedings of the 26th International Conference on Scientific and Statistical Database Management (SSDBM2014), 2014, p. 21.
[Bibtex]
@inproceedings{SensorBenchSSDBM2014,
abstract = {Wireless sensor networks enable cost-effective data collection for tasks such as precision agriculture and environment monitoring. However, the resource-constrained nature of sensor nodes, which often have both limited computational capabilities and battery lifetimes, means that applications that use them must make judicious use of these resources. Research that seeks to support data intensive sensor applications has explored a range of approaches and developed many different techniques, including bespoke algorithms for specific analyses and generic sensor network query processors. However, all such proposals sit within a multi-dimensional design space, where it can be difficult to understand the implications of specific decisions and to identify optimal solutions. This paper presents a benchmark that seeks to support the systematic analysis and comparison of different techniques and platforms, enabling both development and user communities to make well informed choices. The contributions of the paper include: (i) the identification of key variables and performance metrics; (ii) the specification of experiments that explore how different types of task perform under different metrics for the controlled variables; and (iii) an application of the benchmark to investigate the behavior of several representative platforms and techniques.},
author = {Ixent Galpin and
Alan B. Stokes and
George Valkanas and
Alasdair J. G. Gray and
Norman W. Paton and
Alvaro A. A. Fernandes and
Kai-Uwe Sattler and
Dimitrios Gunopulos},
title = {SensorBench: benchmarking approaches to processing wireless
sensor network data},
booktitle = {Proceedings of the 26th International Conference on Scientific and Statistical Database Management ({SSDBM2014})},
doi = {10.1145/2618243.2618252},
year = {2014},
pages = {21},
web = {http://doi.acm.org/10.1145/2618243.2618252},
}

Scientific Lenses over Linked Chemistry Data using BridgeDb and the Open PHACTS Chemical Registration System

New paper on Scientific Lenses at 10th International Conference on Chemical Structures (ICCS) [1].

[1] C. R. Batchelor, C. Brenninkmeijer, C. Evelo, C. Goble, A. J. G. Gray, K. Karapetyan, V. Tkachenko, and E. Willighagen, “Scientific Lenses over Linked Chemistry Data using BridgeDb and the Open PHACTS Chemical Registration System,” in 10th Int. Conf. Chem. Struct., Noordwijkerhout, The Netherlands, 2014, p. 76.
[Bibtex]
@inproceedings{Batchelor2014,
address = {Noordwijkerhout, The Netherlands},
author = {Batchelor, Colin R and Brenninkmeijer, Christian and Evelo, Chris and Goble, Carole and Gray, Alasdair J G and Karapetyan, Kenneth and Tkachenko, Valery and Willighagen, Egon},
booktitle = {10th Int. Conf. Chem. Struct.},
month = jun,
pages = {76},
title = {{Scientific Lenses over Linked Chemistry Data using BridgeDb and the Open PHACTS Chemical Registration System}},
url = {http://www.int-conf-chem-structures.org/fileadmin/user\_upload/program/Book.of.Abstracts.pdf},
year = {2014}
}

PAV Paper Highly Accessed

The PAV ontology paper [1] is “highly accessed” at Journal of Biomedical Semantics within 6 months of publication.

The paper presents the Provenance, Authoring and Versioning ontology. It details the use cases it was designed to meet together with its alignment to PROV-O. The paper also discusses the applications that are already using the PAV ontology, which includes the <a href=”http://www.openphacts.org”>Open PHACTS</a> project <a href=”www.openphacts.org/specs/datadesc/”>Dataset Descriptions</a>.

[1] [doi] P. Ciccarese, S. Soiland-Reyes, K. Belhajjame, A. J. G. Gray, C. Goble, and T. Clark, “PAV ontology: Provenance, Authoring and Versioning,” Journal of Biomedical Semantics, vol. 4, iss. 37, 2013.
[Bibtex]
@Article{PAV:JBS2013,
author = {Paolo Ciccarese and Stian Soiland-Reyes and Khalid Belhajjame and Alasdair J. G. Gray and Carole Goble and Tim Clark},
title = {PAV ontology: Provenance, Authoring and Versioning},
journal = {Journal of Biomedical Semantics},
year = {2013},
OPTkey = {},
volume = {4},
number = {37},
OPTpages = {},
month = nov,
OPTnote = {},
OPTannote = {},
doi = {10.1186/2041-1480-4-37},
url = {http://www.jbiomedsem.com/content/4/1/37/abstract}
}