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

  • 05/31/2019 The first Deep Time Data Science Mini-Workshop at Moscow, ID was a big success. Thanks to all attendees and organizers for your time!
  • 04/30/2019 PhD student Rayan Alshamrani awarded Best Poster at the 2019 UI Computer Science Industrial Advisory Board Meeting.
  • 04/22/2019 Dr. Kathy Fontaine from Rensselaer Polytechnic Institute visited us and gave a talk at the CS seminar series.



Faculty Members:

Xiaogang (Marshall) Ma
Director of IDEA Lab
Assistant Professor
Email: max@uidaho.edu
Xiang Que
Visiting Scholar
Assistant Professor at FAFU, China

Postdoctoral Researchers:

Chao Ma
Postdoctoral Research Associate

Graduate Students:

Abdullah Al-Owairdhi
PhD student
Ashrf Althbiti
PhD student
Rayan Alshamrani
PhD student
Raed Alsini
PhD student
Omar Alghushairy
PhD student
Fatimah Alkomah
PhD student
Lamyaa Alharbi
MSc student
Abhinav Adarapuram
MSc student
Amruta Kale
MSc student
Chunnan Zhang
MSc student

Former Members:

Chengbin Wang
Visiting PhD Student (2016-2017)
Now: Assoc. Prof. at CUG, Wuhan
Olivier Bizimana
Research Assistant for SP17
Now: System Validation Engineer at Intel
Tim Sonnen
MURI Undergraduate Intern (2018)
Now: Software Testing Engineer at Chief Architect
Xin Mou
Collaborating PhD student
Now: Senior Software Engineer at Lucid
Dr. Li Sun
Visiting Scholar (2017)
Now: Assoc. Prof. at CAGS, Beijing
Bhuwan Madhikarmi
MSc student (2016-2018)
Now: Data Scientist at WSU, Pullman
Fatemh Almeman
MSc student (2016-2018)
Now pursuing a PhD program
Chama Salil Reddy
MSc student (2016-2018)
Now Machine Learning Engineer at Quadgen Wireless Solutions
Rohit Kumar Yadav
MSc student (2017-2019)
Adhar Partap Singh
MSc student (2017-2019)
Homaja Marisetty
Teaching Assistant for SP18
Research Assistant for SU18
Seema Kamod
Teaching Assistant for F18


  1. 2018-2021: Elements: Software: HDR: A knowledge base of deep time to facilitate automated workflows in studying the co-evolution of the geosphere and biosphere, funded by National Science Foundation (NSF)
  2. 2017-Present: Leveraging data science to explore co-relationships between elements and minerals, funded by UI ORED Seed Grant
  3. 2016-Present: MILES: Managing Idaho's Landscapes for Ecosystem Services, funded by National Science Foundation (NSF) through Idaho EPSCoR
  4. 2015-Present: DTDI: Deep Time Data Infrastructure, funded by W.M. Keck Foundation
  5. 2015: Research Data Alliance Adoption Initiatives, funded by National Science Foundation (NSF)
  6. 2012-2016: DCO-DS: Deep Carbon Observatory – Data Science, funded by Alfred P. Sloan Foundation

Recent Publications

  1. Wang, C., Ma, X., 2019. Text Mining to Facilitate Domain Knowledge Discovery. In: Mouatasim, A.E., (ed.) Text Mining - Analysis, Programming and Application. IntechOpen, London. In Press. (Open Access)
  2. He, Z., Liu, G., Ma, X., Chen, C., 2019. GeoBeam: A Distributed Computing Framework for Spatial Data. Computers & Geosciences. In Press.
  3. Zeng, Y., Su, Z., Barmpadimos, I., Perrels, A., Poli, P., Boersma, K.f., Frey, A., Ma, X., de Bruin, K., Gossen, H., Timmermans, W., 2019. Towards a Traceable Climate Service: Assessment of Quality and Usability of Essential Climate Variables. Remote Sensing. In Press. (Open Access)
  4. Chen, Q., Liu, G., Ma, X., Zhang, J., Zhang, X., 2019. Conditional multiple-point geostatistical simulation for unevenly distributed sample data. Stochastic Environmental Research and Risk Assessment. In Press.
  5. Hazen, R.M., Downs, R.T., Eleish, A., Fox, P., Gagne, O., Golden, J.J., Grew, E.S., Hummer, D.R., Hystad, G., Krivovichev, S.V., Li, C., Liu, C., Ma, X., Morrison, S.M., Pan, F., Pires, A.J., Prabhu, A., Ralph, J., Rumyon, S.E., Zhong, H., 2019. Data-driven discovery in mineralogy: Recent advances in data resources, analysis, and visualization. Engineering. In Press.
  6. Ma, X., 2019. Geo-Data Science: Leveraging Geoscience Research with Geoinformatics, Semantics and Open Data. Acta Geologica Sinica (English Edition), 93(s1), 44-47. (Open Access)
  7. Morrison, S.M., Prabhu, A., Eleish, A., Pan, F., Zhong, H., Huang, F., Fox, P., Ma, X., Ralph, J., Golden, J.J., Downs, R., Liu, C., Runyon, S.E., Hazen, R.M., 2019. Application of Advanced Analytics and Visualization in Mineral Systems. Acta Geologica Sinica (English Edition), 93(s1), 55-55. (Open Access)
  8. Chen, Q., Mariethoz, G., Liu, G., Comunian, A., Ma, X., 2018. Locality-based 3-D multiple-point statistics reconstruction using 2-D geological cross-sections. Hydrology and Earth System Sciences, 22, 6547-6566.
  9. Chen, Q., Liu, G., Ma, X., Yao, Z., Tian, Y., 2018. A virtual globe-based integration and visualization framework for aboveground and underground 3D spatial objects. Earth Science Informatics, 11 (4), 591-603.
  10. Ma, X., Fu, L., West, P., Fox, P., 2018. Ontology Usability Scale: Context-aware metrics for the effectiveness, efficiency and satisfaction of ontology uses. Data Science Journal, 17, 10. (Open Access)
  11. He, Z., Ma, X., 2018. A distributed indexing method for timeline similarity query, Algorithms, 11 (4), 41. (Open Access)
  12. Wang, C., Ma, X., Chen, J., 2018. Ontology-driven data integration and visualization for exploring regional geologic time and paleontological information, Computers & Geosciences, 115, 12-19. (Open Access)
  13. Wang, C., Ma, X., Chen, J., 2018. The application of data pre-processing technology in the geoscience big data. Acta Petrologica Sinica, 34 (2), 303-313. (In Chinese with English Abstract)
  14. Chen, Q., Liu, G., Ma, X., Mariethoz, G., He, Z., Tian, Y., Weng, Z., 2018. Local curvature entropy-based 3D terrain representation using a comprehensive Quadtree. ISPRS Journal of Photogrammetry and Remote Sensing, 139, 30-45.
  15. Wang, C., Ma, X., Chen, J., Chen, J., 2018. Information extraction and knowledge graph construction from geoscience literature. Computers & Geosciences, 112, 112-120.
  16. Ma, X., Hummer, D., Golden, J.J., Fox, P.A., Hazen, R.M., Morrison, S.M., Downs, R.T., Madhikarmi, B.L., Wang, C., Meyer, M.B., 2017. Using Visual Exploratory Data Analysis to Facilitate Collaboration and Hypothesis Generation in Cross-Disciplinary Research. International Journal of Geo-Information 6 (11), 368. (Open Access)
  17. Ma, X., 2019. Data-Information-Knowledge-Action Model. In: Schintler, L.A., McNeely, C.L. (eds.) Encyclopedia of Big Data. Springer, Cham, Switzerland. In Press.
  18. Ma, X., 2019. Data Repository. In: Schintler, L.A., McNeely, C.L. (eds.) Encyclopedia of Big Data. Springer, Cham, Switzerland. In Press.
  19. Ma, X., 2019. Metadata. In: Schintler, L.A., McNeely, C.L. (eds.) Encyclopedia of Big Data. Springer, Cham, Switzerland. In Press.
  20. Ma, X., 2019. Spatial Data. In: Schintler, L.A., McNeely, C.L. (eds.) Encyclopedia of Big Data. Springer, Cham, Switzerland. In Press.
  21. Ma, X., 2019. Visualization. In: Schintler, L.A., McNeely, C.L. (eds.) Encyclopedia of Big Data. Springer, Cham, Switzerland. In Press.
  22. Ma, X., 2017. Linked Geoscience Data in practice: where W3C standards meet domain knowledge, data visualization and OGC standards. Earth Science Informatics, 10(4), 429-441.
  23. 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.
  24. 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)
  25. 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]
  26. 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.
  27. 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)
  28. 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.
  29. 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.
  30. Ma, X., Fox, P., Narock, T., Wilson, B., 2015. Semantic e-Science. Earth Science Informatics 8 (1), 1-3.
  31. 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]
  32. 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]
  33. 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.
  34. 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.
  35. Ma, X., Fox, P., 2014. A jigsaw puzzle layer cake of spatial data. EOS, Transactions American Geophysical Union 95 (19), 161–161.
  36. 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.


Prof. Xiaogang Ma can be reached at:
Office: Janssen Engineering Building, Room 230
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.