Graph Management to Improve Querying of Health and Social Data

Maria Constanza Pabón, Claudia Roncancio, Martha Millán

Abstract

Large amount of data related to health care are stored in heterogeneous data sources. Independently, social media provides information about people's environment and activities, such as family relationships or patient's habits and social interaction. This information could be used to complement patients medical profiles to improve patient's care. Providing expert users with mechanisms to integrate and query such sources becomes crucial to retrieve information allowing to improve the analysis of patient's situations. This work contributes to facilitating visualization and querying of data coming from such sources. We adopt a graph data model at the conceptual level as it facilitates the integration of structured and semi-structured data. Our purpose is to go a step forward by providing a conceptual query language intended to allow end users, medical domain experts, to retrieve data from heterogeneous data sources by ad hoc queries. In this paper we introduce a set of operators to query data by transforming a graph and we analyze how they fulfill some design features of the conceptual language. These operators allow successive graph transformation to generate subgraphs with filtered data and to derive new relations representing information that is implicit or that is sparse in the data.

References

  1. Bhowmick, S. S., Choi, B., and Zhou, S. (2013). VOGUE: Towards A Visual Interaction-aware Graph Query Processing Framework. In CIDR. www.cidrdb.org.
  2. Blau, H., Immerman, N., and Jensen, D. (2002). A Visual Language for Querying and Updating Graphs. Technical report, University of Massachusetts, Amherst.
  3. Catarci, T., Di Mascio, T., Franconi, E., Santucci, G., and Tessaris, S. (2003). An Ontology Based Visual Tool for Query Formulation Support. In LNCS, volume 2889, pages 32-33. Springer.
  4. Chau, D. H., Faloutsos, C., Tong, H., Hong, J. I., Gallagher, B., and Eliassi-Rad, T. (2008). GRAPHITE: A Visual Query System for Large Graphs. In Intl. Conf. on Data Mining Workshops, pages 963-966. IEEE.
  5. Consens, M. P. and Mendelzon, A. O. (1990). GraphLog: A Visual Formalism for Real Life Recursion. In Proc. of the 9th Symposium on Principles of Database Systems, pages 404-416, New York, USA. ACM.
  6. Groppe, J., Groppe, S., and Schleifer, A. (2011). Visual Query System or Analyzing Social Semantic Web. In Proc. of the 20th Intl. Conf. Companion on World Wide Web, pages 217-220, New York,USA. ACM.
  7. Gyssens, M., Paredaens, J., and Gucht, D. V. (1990). A Graph-oriented Object Model for Database End-user Interfaces. SIGMOD Record, 19(2):24-33.
  8. Harris, S. and Seaborne, A. (2013). SPARQL 1.1 Query Language. W3C Recommendation.
  9. Hidders, J. (2002). Typing Graph-Manipulation Operations. In Proc. of the 9th Intl. Conf. on Database Theory, ICDT, pages 394-409, London, UK. Springer-Verlag.
  10. Hidders, J. and Paredaens, J. (1993). GOAL, A Graphbased Object and Association Language. CISM - Advances in Database Systems, pages 247-265.
  11. López, F., Ceballos, O., and Díaz, N. (2012). SMITAG: Red Social para la Anotación Semántica de Imágenes Médicas. In XXXVIII Latin American Conf. on Informatics CLEI, Colombia.
  12. Quilitz, B. and Leser, U. (2008). Querying Distributed RDF Data Sources with SPARQL. In ESWC'08, pages 524-538. Springer-Verlag.
  13. San Martín, M., Gutierrez, C., and Wood, P. T. (2011). SNQL: Social Networks Query Language. Technical report, Universidad de Chile.
  14. Schwarte, A., Haase, P., Hose, K., Schenkel, R., and Schmidt, M. (2011). FedX: A Federation Layer for Distributed Query Processing on Linked Open Data. In Extended Semantic Web Conf. ESWC.
  15. Smart, P. R., Russell, A., Braines, D., Kalfoglou, Y., Bao, J., and Shadbolt, N. R. (2008). A Visual Approach to Semantic Query Design Using a Web-Based Graphical Query Designer. In Proc. of the 16th Intl. Conf. on Knowledge Engineering: Practice and Patterns, volume 5268 of LNCS, pages 275-291. Springer.
Download


Paper Citation


in Harvard Style

Pabón M., Roncancio C. and Millán M. (2014). Graph Management to Improve Querying of Health and Social Data . In Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2014) ISBN 978-989-758-010-9, pages 343-350. DOI: 10.5220/0004805403430350


in Bibtex Style

@conference{healthinf14,
author={Maria Constanza Pabón and Claudia Roncancio and Martha Millán},
title={Graph Management to Improve Querying of Health and Social Data},
booktitle={Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2014)},
year={2014},
pages={343-350},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004805403430350},
isbn={978-989-758-010-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2014)
TI - Graph Management to Improve Querying of Health and Social Data
SN - 978-989-758-010-9
AU - Pabón M.
AU - Roncancio C.
AU - Millán M.
PY - 2014
SP - 343
EP - 350
DO - 10.5220/0004805403430350