About

The Laboratory for Interdisciplinary Data Exploration and Analytics (IDEA Lab) addresses the growing demand of data science in multi- and interdisciplinary research. Building on our previous experience of deploying data science in the Semantic Web to support cross-disciplinary collaboration and scientific discovery, we aim at exploring the cutting-edge methodologies and technologies for participatory knowledge engineering, qualitative and quantitative modeling of complex systems, data interoperability and provenance, data curation and stewardship, visualized analysis of Big and Small Data, and the integrated application of them to tackle real world issues.

Apply to the Computer Science Graduate Program - We are looking for new PhD students with a background and interest in topics related to data science and geoinformatics - Contact Us to Discuss the Opportunities.

Research Areas

  • Design and implementation of models and knowledge graphs for complex systems in science
  • Data interoperability and provenance enablement with participatory approaches and semantic technologies
  • Exploratory analytics and visualization of spatio-temporal patterns in Big and Small Data

News & Announcements | More

  • 09/14/2017 Congrats to Chengbin Wang for receiving the 2017 Computers&Geosciences Research Scholarship.
  • 08/01/2017 Marshall's manuscript on data science and geoscience was accepted for publication in "Handbook of Mathematical Geosciences: Fifty Years of IAMG" by Springer.
  • 06/22/2017 Marshall will co-chair the Hackathon session 'Social Network Analysis of Non-social Data' at ACM Web Science Conference 2017, Tory, NY.

Sponsors

People

Xiaogang (Marshall) Ma
Head of IDEA Lab
Assistant Professor
Email: max@uidaho.edu
Abdullah Al-Owairdhi
PhD student
Chengbin Wang
Visiting scholar
Bhuwan Madhikarmi
MSc student
Olivier Bizimana
Research Assistant for SP17
Xin Mou
Collaborating PhD student
Tim Sonnen
MURI Undergraduate Intern

Research

  1. 2017-Present: Leveraging data science to explore co-relationships between elements and minerals, funded by UI ORED Seed Grant
  2. 2016-Present: MILES: Managing Idaho's Landscapes for Ecosystem Services, funded by National Science Foundation (NSF) through Idaho EPSCoR
  3. 2015-Present: DTDI: Deep Time Data Infrastructure, funded by W.M. Keck Foundation
  4. 2015: Research Data Alliance Adoption Initiatives, funded by National Science Foundation (NSF)
  5. 2012-2016: DCO-DS: Deep Carbon Observatory – Data Science, funded by Alfred P. Sloan Foundation

Recent Publications

  1. Ma, X., 2017. Metadata. In: Schintler, L.A., McNeely, C.L. (eds.) Encyclopedia of Big Data. Springer, Cham, Switzerland. In Press.
  2. Ma, X., 2017. Spatial Data. In: Schintler, L.A., McNeely, C.L. (eds.) Encyclopedia of Big Data. Springer, Cham, Switzerland. In Press.
  3. Ma, X., 2017. Visualization. In: Schintler, L.A., McNeely, C.L. (eds.) Encyclopedia of Big Data. Springer, Cham, Switzerland. In Press.
  4. Ma, X., 2017. Linked Geoscience Data in practice: where W3C standards meet domain knowledge, data visualization and OGC standards. Earth Science Informatics, In press.
  5. Chen, Q., Liu, G., Ma, X., Li, X., He, Z., 2017. Fractal generator for efficient production of random planar patterns and symbols in digital mapping. Computers & Geosciences, 105, 91-102.
  6. Ma, X., West, P., Zednik, S., Erickson, J., Eleish, A., Chen, Y., Wang, H., Zhong, H., Fox, P., 2017. Weaving a knowledge network for Deep Carbon Science. Frontiers in Earth Science, 5, 36. (Open Access)
  7. Mou, X., Jamil, H., Ma, X., 2017. VisFlow: A visual database integration and workflow querying system. Proceedings of the 33rd IEEE International Conference on Data Engineering (ICDE 2017). San Diego, CA, USA. 2pp. [Finalist of Demo Paper Track]
  8. Ma, X., Beaulieu, S.E., Fu, L., Fox, P., Di Stefano, M., West, P., 2017. Documenting Provenance for Reproducible Marine Ecosystem Assessment in Open Science. In: Diviacoo, P., Glaves, H.M., Leadbetter, A. (eds.) Oceanographic and Marine Cross-Domain Data Management for Sustainable Development. IGI Global, Hershey, PA, USA. pp.100-126.
  9. Ma, X., Erickson, J.S., Zednik, S., West, P., Fox, P., 2016. Semantic specification of data types for a world of Open Data. ISPRS International Journal of Geo-Information 5 (3), 38. (Open Access)
  10. Ma, X., Chen, Y., Wang, H., Zheng J.G., Fu, L., West, P., Erickson, J.S., Fox, P., 2015. Data visualization in the Semantic Web. In: Narock, T., Fox, P., (eds.) The Semantic Web in Earth and Space Science: Current Status and Future Directions. IOS Press, Berlin. pp. 149-167.
  11. Zheng, J., Fu, L., Ma, X., Fox, P., 2015. SEM+: tool for discovering concept mapping in Earth science related domain. Earth Science Informatics 8 (1), 95-102.
  12. Ma, X., Fox, P., Narock, T., Wilson, B., 2015. Semantic e-Science. Earth Science Informatics 8 (1), 1-3.
  13. Ma, X., 2015. Geoinformatics in the Semantic Web. In: Schaeben, H., Delgado, R.T., van den Boogaart, K.G., van den Boogaart, R. (eds.) Proceedings of IAMG 2015, Freiberg, Germany, pp 18-26. [Andrei B. Vistelius Award Invited Article]
  14. Wang, H., Zheng, J.G., Ma, X., Fox P., Ji, H., 2015. Language and Domain Independent Entity Linking with Quantified Collective Validation. Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP2015). 10 pp. [Best Paper Nomination]
  15. Ma, X., Zheng, J.G., Goldstein, J., Zednik, S., Fu, L., Duggan, B., Aulenbach, S., West, P., Tilmes, C., Fox, P., 2014. Ontology engineering in provenance enablement for the National Climate Assessment. Environmental Modelling & Software 61, 191-205.
  16. Ma, X., Fox, P., Tilmes, C., Jacobs, K., Waple, A., 2014. Capturing and presenting provenance of global change information. Nature Climate Change 4 (6), 409-413.
  17. Ma, X., Fox, P., 2014. A jigsaw puzzle layer cake of spatial data. EOS, Transactions American Geophysical Union 95 (19), 161–161.
  18. Ma, X., Fox, P., Rozell, E., West, P., Zednik, S., 2014. Ontology dynamics in a data life cycle: challenges and recommendations from a geoscience perspective. Journal of Earth Science 25 (2), 407–412.

Contact

Prof. Xiaogang Ma can be reached at:
Office: Janssen Engineering Building, Room 337
Tel: +1 208-885-1547
Email: max@uidaho.edu

Mailing address:
Department of Computer Science
University of Idaho
875 Perimeter Drive MS 1010
Moscow, ID 83844-1010, USA

We are looking for new PhD students with a background and interest in topics related to data science and geoinformatics, such as knowledge graph, data interoperability, data mining, big data analytics, data visualization, semantic similarity, natural languange processing, spatial data infrastructure, and more. Please email us to discuss the opportunities. Refer to the Computer Science Graduate Program webpage for information about the prelimary requirements for enrollment.