DILS: Data Integration in the Life Sciences



Past:   Proceedings on DBLP

Future:  Post a CFP for 2018 or later   |   Invite the Organizers Email


All CFPs on WikiCFP

Event When Where Deadline
DILS 2017 12th International Conference on Data Integration in Life Science
Nov 14, 2017 - Nov 15, 2017 Luxembourg Jun 20, 2017
DILS 2015 11th International Conference on Data Integration in Life Sciences
Jul 9, 2015 - Jul 10, 2015 Los Angeles, CA, USA Mar 1, 2015
DILS 2014 10th International Conference on Data Integration in the Life Sciences
Jul 17, 2014 - Jul 18, 2014 Lisbon, Portugal Feb 14, 2014 (Feb 7, 2014)
DILS 2013 The Ninth International Conference on Data Integration in the Life Sciences 2013
Jul 11, 2013 - Jul 12, 2013 Montreal, Quebec, Canada Feb 15, 2013
DILS 2012 Eighth International Conference on Data Integration in the Life Sciences
Jun 28, 2012 - Jun 29, 2012 University of Maryland, College Park, MD Feb 20, 2012 (Feb 13, 2012)
DILS 2010 Seventh International Conference on Data Integration in the Life Sciences
Aug 25, 2010 - Aug 27, 2010 Gothenburg, Sweden Apr 18, 2010 (Apr 11, 2010)
DILS 2009 6th International Workshop on Data Integration in the Life Sciences
Jul 20, 2009 - Jul 22, 2009 Manchester, UK Feb 20, 2009 (Feb 13, 2009)
DILS 2008 Data Integration in the Life Sciences 2008
Jun 25, 2008 - Jun 27, 2008 Evry, France Feb 20, 2008

Present CFP : 2017

November 14-15, Hotel Parc Belle-Vue, Luxembourg, LU

The Twelfth International Conference on Data Integration in the Life Sciences (DILS2017) will be held at the Hotel Parc Belle-Vue, on Nobember 14-15, 2017. The conference aim is to foster discussion, exchange, and innovation in research and development in the areas of data integration and knowledge management for the life sciences. Researchers and professionals from biology, medicine, computer science and engineering are invited to share their knowledge and experience.

eSanté Agency, Luxembourg
Luxembourg National Research Fund

Robert Stevens (https://www.research.manchester.ac.uk/portal/robert.stevens.html)
Alex Bateman (https://publons.com/author/259342/alex-bateman#profile)

Publisher: Springer


June 20th , 2017: Paper submission deadline for research,

June 30th, 2017: Industry, demonstration, and application/experience papers

August 25th , 2017: Notification of acceptance

September 10th , 2017: Camera-ready copy due

November 14-15, 2017: Conference days


* Life Science Data Modelling
- "Big Data" infrastructure
- Data integration systems
- Data models and standards
- Ontology and its evolution
- Architectures and data management techniques
* Analysing, Indexing, and Querying Life Sciences Datasets
- Linked Open Data
- Machine Learning
- Query formulation, processing and optimization
* Annotating, Matching, and Sharing Life Sciences Datasets
- Data annotation and maintenance
- Ontology and Schema Matching
* Privacy and Provenance of Life Sciences Datasets
- Ethical, legal and social issues
- Data owner sensitive data sharing
- Privacy-preserving data integration and management
- Sharing, updating and propagating data

Industry papers, demos and application/experiences are also welcome to DILS'17. They will be selected according to industry-compliant assessment criteria.
In all cases please refer to the submission procedure:



Authors are invited to submit original contributions of technical rigor and practical relevance to DILS 2017. Three types of papers will be selected:
Full research papers (up to 15 pages)
Short research papers (8 pages)
Industry/application/experience papers (8 pages)
Demos (4 pages)
Papers are to be prepared using LNCS templates and submitted using the EasyChair site:

The proceedings of DILS will be published by Springer in the LNCS/LNAI/LNBI (Lecture Notes in Bioinformatics).



Best Paper awards will be conferred at the conference on the authors of (1) the best research paper, (2) the best student paper.
Authors of the best accepted papers that address some interesting data quality challenges will be invited to submit an extended version of their paper to the ACM Journal of Data and Information Quality.

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