| Author | Title | Year | Journal/Proceedings | Reftype | DOI/URL |
|---|---|---|---|---|---|
| Blum, J. | Metadata, say what? | 2008 | Unpublished | unpublished | URL |
| Abstract: Social science generates and uses an enormous amount of statistical data. Many actors are involved in data collection and storage processes including governments, institutions, organisations and researchers. Assumptions are made about what the data represents and what is common knowledge. In order to improve data management and exchange, the data needs to be described, which is exactly what metadata does. In this talk we will explore the way that metadata has developed for social science and describe the uses it can be put to. We will also examine emerging social science metadata standards and tool support for those standards. Finally we will present a vision for e-social science research supported by pervasive use of metadata. | |||||
BibTeX:
@unpublished{blum2008meta_say,
author = {Blum, J.},
title = {Metadata, say what?},
year = {2008},
note = {Talk given at the 3rd ESRC Research Methods Festival as part of Session 27 - Resources for Data Management and Handling Social Science Data},
url = {http://www.cs.stir.ac.uk/~jmb/dames/presentations/Metadata_say_what.ppt}
}
|
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| Blum, J. & Magill, E. | Telecare Service Challenge: Conflict Detection | 2011 | ATTACH 2011 Workshop, Pervasive Computing Technologies for Healthcare (PervasiveHealth), 2011 5th International Conference on, | inproceedings | |
| Abstract: Telecare and telehealth system services can be dynamically configured to collect, analyse, store, and adapt to multimodal data about people as they go about their activities of daily life. These services need to be able to personalise to subjects and adapt to changes in lifestyles, environments and technology. Such dynamic adaptability may be well supported by a low-level rule programming approach; however measures may need to be taken to limit the emergence of conflicts between the distributed rulesets owing to differing programmatic assumptions and unexpected changes. | |||||
BibTeX:
@inproceedings{Blum2011TelecareS,
author = {Blum, J.M. and Magill, E.H.},
title = {Telecare Service Challenge: Conflict Detection},
booktitle = {ATTACH 2011 Workshop, Pervasive Computing Technologies for Healthcare (PervasiveHealth), 2011 5th International Conference on,},
year = {2011}
}
|
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| Blum, J. & Magill, E. | The Design and Evaluation of Personalised Ambient Mental Health Monitors | 2010 | Proceedings of the 7th Annual IEEE Consumer Communications and Networking Conference | conference | URL |
| Abstract: Mobile and environmental sensing technology can be used to assess human behaviour and mental health trajectories outside of laboratories and in ecologically-relevant settings. To achieve maximum benefit, the set of equipment and the monitoring patterns must be personalised to respect individual needs and fit into individual lifestyles. We have developed a mobile-phone-centric sensor homecare and network infrastructure using a rule-oriented programming architecture to monitor the activity signatures of people with Bipolar Disorder (BD). We believe that the use of this rule-based paradigm within the network for a mental health setting to be a contribution of this work. We are evaluating the effectiveness of the technology in an on-going technical trial with control participants as a precursor to studying the effectiveness of the system for use with people with BD. In this paper, we report the design and development of the monitoring system along with preliminary findings from the technical trial of the system, and discuss future developments. |
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BibTeX:
@conference{blumDesign2010,
author = {Jesse Blum and Evan Magill},
title = {The Design and Evaluation of Personalised Ambient Mental Health Monitors},
booktitle = {Proceedings of the 7th Annual IEEE Consumer Communications and Networking Conference},
publisher = {IEEE},
year = {2010},
url = {http://ieeexplore.ieee.org/Xplore/login.jsp?url=http%3A%2F%2Fieeexplore.ieee.org%2Fiel5%2F5419385%2F5421566%2F05421748.pdf%3Farnumber%3D5421748&authDecision=-203}
}
|
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| Blum, J. & Magill, E. | Dynamically Programmable m-Psychiatry System For Self-Management of Bipolar Disorder | 2009 | Postgraduate Conference in Biomedical Engineering & Medical Physics (PGBioMed), pp. 21 | conference | |
| Abstract: A rule-oriented approach to programming mobile psychiatric monitoring systems was designed. Initial simulations of rule processing have tested system personalisation issues and reviewed characteristics of the rule-oriented approach including the degree of task expressiveness and ease of expressing domain knowledge. A technical trial is being prepared to analyse the approach in a non-simulated environment. | |||||
BibTeX:
@conference{blum2009dynamically,
author = {Blum, JM and Magill, EH},
title = {Dynamically Programmable m-Psychiatry System For Self-Management of Bipolar Disorder},
booktitle = {Postgraduate Conference in Biomedical Engineering & Medical Physics (PGBioMed)},
year = {2009},
pages = {21}
}
|
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| Blum, J. & Magill, E. | M-Psychiatry: Sensor Networks for Psychiatric Health Monitoring | 2008 | Proceedings of The 9th Annual Postgraduate Symposium The Convergence of Telecommunications, Networking and Broadcasting (PGNET 2008), pp. 33-37 | conference | URL |
| Abstract: Long-term monitoring of patients with affective disorders has been shown to reduce certain types of episodes and improve social functioning. However, most of the research to date has been based on patient-reported data, which exhibits certain deficiencies including failure to detect depressive aspects of the illness. Questions have also been raised about the accuracy and completeness of patient-reported data. Enhancing patientreported data with environmental and physiological recordings could improve the accuracy and completeness that current solutions are missing. This paper describes procedures for the fusion of patient-reported data with remotely-sensed patientcentred data collected using small wireless devices placed on patients and in their homes. | |||||
BibTeX:
@conference{blum-m,
author = {Blum, J. and Magill, E.},
title = {M-Psychiatry: Sensor Networks for Psychiatric Health Monitoring},
booktitle = {Proceedings of The 9th Annual Postgraduate Symposium The Convergence of Telecommunications, Networking and Broadcasting (PGNET 2008)},
year = {2008},
pages = {33--37},
url = {www.cms.livjm.ac.uk/pgnet2008/Proceeedings/Papers/2008028.pdf}
}
|
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| Blum, J. & Turner, K. | The DAMES Metadata Approach | 2008 | Technical report, University of Stirling, DAMES Project (CSM-177) | techreport | URL |
| Abstract: The DAMES project will provide high quality data management activities services to the social science research community based on an e-social science infrastructure. The infrastructure is supported by the collection and use of metadata to describe datasets and other social science resources. This report reviews the metadata requirements of the DAMES services, reviews a number of metadata standards, and discusses how the selected standards can be used to supprot the DAMES services. The kinds of metadata focussed upon in this report include metadata for describing social science microdatasets and other resources such as data analysis processing instruction files, metadata for grouping and linking datasets, and metadata for describing the provenance of data as it is transformed through analytical procedures. The social science metadata standards reviewed include: • The Common Warehouse Metamodel (CWM) • The Data Documentation Initiative (DDI) versions 2 and 3 • Dublin Core • Encoded Archival Description (EAD) • e-Government Metadata Standard (e-GMS) • ELSST and HASSET • MAchine-Readable Cataloging (MARC) • Metadata Encoding and Transmission Standard (METS) • MetaDater • Open Archives Initiative (OAI) • Open Archival Information System (OAIS) • Statistical Data and Metadata Exchange (SDMX) • Text Encoding Initiative (TEI) The review concludes that the DDI standard version 3.0 is the most appropriate one to be used in the DAMES project and explains how best to integrate the standard into the project. This includes a description of how to capture metadata upon resource registration, upgrade the metadata from accessible resources available throughthe GEODE project, use the metadata for resource discovery, and generate provenance metadata during data transformation procedures. In addition, a “metadata wizard” is described to help with data management activities. |
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BibTeX:
@techreport{blum2008dames,
author = {Blum, J.M. and Turner, K.J.},
title = {The DAMES Metadata Approach},
year = {2008},
number = {CSM-177},
note = {ISSN 1460-9673},
url = {https://dspace.stir.ac.uk/dspace/handle/1893/1576}
}
|
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| Blum, J., Warner, G., Jones, S., Lambert, P., Dawson, A., Tan, K. & Turner, K. | Metadata Creation, Transformation and Discovery for Social Science Data Management: The DAMES Project Infrastructure | 2009 | IASSIST Quarterly Vol. 2009, pp. 23 |
article | URL |
| Abstract: This paper discusses the use of metadata, underpinned by DDI (Data Documentation Initiative), to support social science data management. This term refers broadly to the discovery, preparation and manipulation of social science data for the purposes of research and analysis. Typical tasks include recoding variables within a dataset, and linking data from different sources. A description is given of the DAMES project (Data Management through e-Social Science), a UK project which is building resources and services to support quantitative social science data management activities. DAMES provides generic facilities for performing (and recording) operations on data. Specific resources include support for analysis through microsimulation, and support for access to specialist data on occupations, educational qualifications, measures of ethnicity and immigration, social care, and mental health. The DAMES project tools and services can generate, use, transform and search metadata that describes social science datasets (such as micro-social survey datasets and aggregatelevel macro-data). On DAMES, this metadata is described by various standards including DDI version 2, DDI version 3, JSDL (Job Submission Definition Language), and the purposedesigned JFDL (Job Flow Definition Language). The paper describes how DAMES uses metadata with a range of resources that are integrated with a job execution infrastructure, a web portal, and a tool for data fusion. | |||||
BibTeX:
@article{blum2009meta,
author = {Blum, J.M. and Warner, G.C. and Jones, S.B. and Lambert, P.S. and Dawson, A.S.F. and Tan, K.L.L. and Turner, K.J.},
title = {Metadata Creation, Transformation and Discovery for Social Science Data Management: The DAMES Project Infrastructure},
journal = {IASSIST Quarterly},
year = {2009},
volume = {2009},
pages = {23},
url = {http://www.iassistdata.org/iq/metadata-creation-transformation-and-discovery-social-science-data-management-dames-project-infra}
}
|
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| James, C., Crowe, J., Magill, E., Brailsford, S., Amor, J., Prociow, P., Blum, J. & Mohiuddin, S. | Chapter: Personalised Ambient Monitoring (PAM) of the mentally ill | 2008 | 4th European Conference of the International Federation for Medical and Biological Engineering Vol. 22(Part 8), pp. 1010-1013 |
inbook | DOI URL |
| Abstract: One in ten of the (UK) population will suffer a disabling mental disorder at some stage in their life. Bipolar disorder is one such illness and is characterized by periods of depression or manic activity interspersed with stretches of normality. Some patients are able to manage this condition via their self-awareness that enables them to detect the onset of debilitating episodes and so take effective action. Such self management can be achieved through a paper-based process, although more recently PDAs have been used with success. This presentation will introduce the Personalised Ambient Monitoring (PAM) concept that aims to augment such processes by automatically providing and merging environmental details and information relating to personal activity. Essentially the PAM project is investigating what may be loosely referred to as ‘electronic’ monitoring to automatically record ‘activity signatures’ and subsequently use this data to issue alerts. The types of data that we are considering using includes: location and activity (e.g. via GPS and accelerometers); and environment (e.g. temperature and light levels). Other types of sensor under consideration are passive IR sensors (within the home); and sound processing to log the audio ‘environment’. The use of such monitoring will be agreed between the patient and their health care team and it is anticipated that different patients will be comfortable with different sensor packages, thus personalizing the monitoring. Although such tele-monitoring is now generally common, its use in the treatment of the mentally ill is still in its infancy. This paper will consider the specific problems faced in applying it to this community along with the aims of this project. In addition, the use of modelling to predict the effects of the possible problems of sparse data that is expected, and to predict the effect on the overall patient pathway will be considered. | |||||
BibTeX:
@inbook{james-personalised,
author = {James, CJ and Crowe, J. and Magill, E. and Brailsford, SC and Amor, J. and Prociow, P. and Blum, J. and Mohiuddin, S.},
title = {4th European Conference of the International Federation for Medical and Biological Engineering},
publisher = {Springer Berlin Heidelberg},
year = {2008},
volume = {22},
number = {Part 8},
pages = {1010-1013},
url = {http://www.springerlink.com/content/g11840r16v070529/},
doi = {http://dx.doi.org/10.1007/978-3-540-89208-3}
}
|
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| Lambert, P., Blum, J., Bowes, A., Gayle, V., Jones, S., Sinnott, R., Tan, K., Turner, K. & Warner, G. | Standards setting when standardizing categorical data | 2009 | The Proceedings of the 5th International Conference on E-Social Science | conference | URL |
| Abstract: Quantitative social survey research struggles to reconcile the widespread collection of categorical measures, and the common desire to conduct analyses which are not well suited to categorical data (involving comparing standardized, relative positions). By describing approaches taken in the DAMES NCeSS research Node, which is developing facilities to assist in the management of categorical data on occupations, educational qualifications, and ethnicity, this paper argues that tools and practices associated with e-Social Science offer an opportunity to raise standards in the analysis of categorical data. | |||||
BibTeX:
@conference{lambert-standards,
author = {Lambert, P.S. and Blum, J.M. and Bowes, A. and Gayle, V. and Jones, S.B. and Sinnott, R.O. and Tan, K.L.L. and Turner, K.J. and Warner, G.C.},
title = {Standards setting when standardizing categorical data},
booktitle = {The Proceedings of the 5th International Conference on E-Social Science},
year = {2009},
url = {http://www.dames.org.uk/docs/conf_papers/ess09/Lambert_et_al.pdf}
}
|
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| Lambert, P., Gayle, V., Tan, K., Blum, J., Bowes, A., Jones, S., Turner, K., Warner, G., Sinnott, R. & Bihagen, E. | Grid enabled specialist data environments: Forward planning for GE* DE services for specialist data on occupations, educational qualifications, and ethnicity | 2008 | Technical report, University of Stirling, DAMES Project Vol. 12(2008-1), pp. 2008 |
techreport | URL |
| Abstract: Technical Papers of the DAMES Node: Data Management through e-Social Science, http://www.dames.org.uk/publications.html. DAMES is an ESRC Research Node, Ref: RES- 149-25-1066, based at the Universities of Stirling and Glasgow (the National e-Science Centre, www.nesc.ac.uk). The DAMES Node is a component of the ESRC National Centre for e-Social Science (www.ncess.ac.uk). | |||||
BibTeX:
@techreport{lambert2008grid,
author = {Lambert, P.S. and Gayle, V. and Tan, K.L.L. and Blum, J. and Bowes, A. and Jones, S. and Turner, K.J. and Warner, G. and Sinnott, R.O. and Bihagen, E.},
title = {Grid enabled specialist data environments: Forward planning for GE* DE services for specialist data on occupations, educational qualifications, and ethnicity},
year = {2008},
volume = {12},
number = {2008-1},
pages = {2008},
url = {http://www.dames.org.uk/docs/tech_papers/DAMES_tp2008-1.pdf}
}
|
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| Prociow, P., Crowe, J.A., Brailsford, S.C., James, C.J., Magill, E., Amor, J., Blum, J. & Mohiuddin, S. | Personalised Ambient Monitoring (PAM) for People with Bipolar Disorder | 2009 | Proceedings of the International eHealth, Telemedicine and Health ICT Forum For Education, Networking and Business (MedETel), Vol. 2, pp. 176 | inbook | |
| Abstract: Preliminary Evaluations of Internet-based System for e-Psychology. | |||||
BibTeX:
@inbook{Prociow2009Personalised,
author = {Prociow, P. and Crowe, J. A. and Brailsford, S. C. and James, C. J. and Magill, E. and Amor, J. and Blum, J. and Mohiuddin, S.},
title = {Personalised Ambient Monitoring (PAM) for People with Bipolar Disorder},
booktitle = {Proceedings of the International eHealth, Telemedicine and Health ICT Forum For Education, Networking and Business (MedETel)},
publisher = {Luxexpo},
year = {2009},
volume = {2},
pages = {176},
note = {ISSN 1998-5509}
}
|
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| Tan, K., Lambert, P., Turner, K., Blum, J., Gayle, V., Jones, S., Sinnott, R. & Warner, G. | Enabling Quantitative Data Analysis Through e-Infrastructure | 2009 | Social Science Computer Review Vol. 27(4), pp. 539-552 |
article | DOI URL |
| Abstract: This article discusses how quantitative data analysis in the social sciences can engage with and exploit an e-Infrastructure. We highlight how a number of activities that are central to quantitative data analysis, referred to as "data management," can benefit from e-Infrastructural support. We conclude by discussing how these issues are relevant to the Data Management through e-Social Science (DAMES) research Node, an ongoing project that aims to develop e-Infrastructural resources for quantitative data analysis in the social sciences. | |||||
BibTeX:
@article{tan2009enabling,
author = {Tan, K.L.L. and Lambert, P.S. and Turner, K.J. and Blum, J. and Gayle, V. and Jones, S.B. and Sinnott, R.O. and Warner, G.},
title = {Enabling Quantitative Data Analysis Through e-Infrastructure},
journal = {Social Science Computer Review},
publisher = {Sage Publications, Inc.},
year = {2009},
volume = {27},
number = {4},
pages = {539--552},
url = {http://ssc.sagepub.com/cgi/content/abstract/27/4/539},
doi = {http://dx.doi.org/10.1177/0894439309332647}
}
|
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| Turner, K., Tan, K., Blum, J., Warner, G., Jones, S. & Lambert, P. | Managing Data in E-Social Science | 2009 | Proceedings of the 2009 Eighth International Conference on Networks-Volume 00, pp. 214-219 | conference | DOI URL |
| Abstract: Grid computing is moving from its original focus on the physical sciences to other disciplines such as the social sciences. The orientation of these newer applications is on data management rather than processing. This paper describes how the DAMES project (Data Management through E-Social Science) is developing grid-based solutions for handling data in a distributed environment. The paper describes the approach being taken to meet key challenges: metadata for effective use of datasets, and data-oriented workflows for e-social science. | |||||
BibTeX:
@conference{turner2009managing,
author = {Turner, K.J. and Tan, K.L.L. and Blum, J.M. and Warner, G.C. and Jones, S.B. and Lambert, P.S.},
title = {Managing Data in E-Social Science},
booktitle = {Proceedings of the 2009 Eighth International Conference on Networks-Volume 00},
year = {2009},
pages = {214--219},
url = {http://portal.acm.org/citation.cfm?id=1547799},
doi = {http://dx.doi.org/10.1109/ICN.2009.15}
}
|
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| Warner, G., Blum, J., Jones, S., Lambert, P., Turner, K., Tan, L., Dawson, A. & Bell, D. | A social science data-fusion tool and the Data Management through e-Social Science (DAMES) infrastructure | 2010 | Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences Vol. 368(1925), pp. 3859 |
article | DOI URL |
| Abstract: The last two decades have seen substantially increased potential for quantitative social science research. This has been made possible by the significant expansion of publicly available social science datasets, the development of new analytical methodologies, such as microsimulation, and increases in computing power. These rich resources do, however, bring with them substantial challenges associated with organizing and using data. These processes are often referred to as ‘data management’. The Data Management through e-Social Science (DAMES) project is working to support activities of data management for social science research. This paper describes the DAMES infrastructure, focusing on the data-fusion process that is central to the project approach. It covers: the background and requirements for provision of resources by DAMES; the use of grid technologies to provide easy-to-use tools and user front-ends for several common social science data-management tasks such as data fusion; the approach taken to solve problems related to data resources and metadata relevant to social science applications; and the implementation of the architecture that has been designed to achieve this infrastructure. | |||||
BibTeX:
@article{warner2010social,
author = {Warner, G.C. and Blum, J.M. and Jones, S.B. and Lambert, P.S. and Turner, K.J. and Tan, L. and Dawson, A.S.F. and Bell, D.N.F.},
title = {A social science data-fusion tool and the Data Management through e-Social Science (DAMES) infrastructure},
journal = {Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences},
publisher = {The Royal Society},
year = {2010},
volume = {368},
number = {1925},
pages = {3859},
url = {http://rsta.royalsocietypublishing.org/content/368/1925/3859.abstract},
doi = {http://dx.doi.org/10.1098/rsta.2010.0159}
}
|
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