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

  • 10/29/2022 Sanaz and Amruta both received the NSF EarthCube Early-Career Travel Grant for the AGU 2022 Fall Meeting. Congrats!
  • 10/14/2022 Nature published Marshall's correspondence on scientific unions' efforts on data standards. (full text preprint)
  • 09/30/2022 Marshall was selected as the Univeristy of Idaho College of Engineering Dean's Distinguished Fellow (2022-2024)!

Sponsors

People

Faculty Members:

Xiaogang (Marshall) Ma
Director of IDEA Lab
Assistant Professor
Email: max@uidaho.edu

Postdoctoral Researchers:


Postdoctoral Research Associate
(05/2021 - )
Sanaz Salati
Postdoctoral Research Associate
(12/2021 - )
Xiang Que
Postdoctoral Research Associate
(05/2022 - )
Jingyi Huang
Postdoctoral Research Associate
(09/2022 - )

Graduate Students:

  • Rayan Alshamrani, PhD student
  • Fatimah Alkomah, PhD student
  • Amruta Kale, PhD student
  • Chenhao Li, PhD student
  • Jiyin Zhang, PhD student
  • Weilin Chen, PhD student

Undergraduate Students:

  • Meghan Nulf, NSF REU intern in Fall 2022
  • Contact Dr. Ma if you are interested to be a research intern

Former Members:

  • Chengbin Wang, Visiting PhD Student (2016-2017), Now: Assoc. Prof. at CUG, Wuhan
  • Olivier Bizimana, Research Assistant for SP17, First Job: System Validation Engineer at Intel
  • Tim Sonnen, MURI Undergraduate Intern (2018), First Job: Software Testing Engineer at Chief Architect
  • Xin Mou, Collaborating PhD student (2016-2019), First Job: Senior Software Engineer at Lucid
  • Dr. Li Sun, Visiting Scholar (2017), Now: Assoc. Prof. at CAGS, Beijing
  • Bhuwan Madhikarmi, MSc 2018, First Job: Data Scientist at WSU, Pullman
  • Fatemh Almeman, MSc 2018, Enrolled at Cardiff University for PhD study
  • Chama Salil Reddy, MSc 2018, First Job: Machine Learning Engineer at Quadgen Wireless Solutions
  • Rohit Kumar Yadav, MSc 2019
  • Adhar Partap Singh, MSc 2019
  • Homaja Marisetty, Teaching Assistant for SP18 and Research Assistant for SU18
  • Seema Kamod, Teaching Assistant for F18
  • Xiang Que, Visiting Scholar (2018-2019), Now: Assistant Professor at FAFU, China
  • Haifeng Lian, Visiting Scholar (2019-2020), Now: Professor at FAFU, China
  • Cai Can, Visiting Undergraduate Student (2019-2020), Enrolled as PhD student at CUG, Beijing
  • Lamyaa Alharbi, MSc 2020
  • Abhinav Adarapuram, MSc 2020
  • Samarth Subramanya, MSc 2020
  • Bhargav Rao, MSc 2020
  • Rongbin Tang, Visiting PhD student (2019-2020)
  • Manjunath Mulinti, MSc 2020
  • Ronald Crump III, NSF REU Intern 2020
  • Tyler Clemens, NSF REU Intern 2020
  • Chao Ma, Postdoctoral Research Associate (2019-2021), Now: Full Professor at CDUT, China
  • Abdullah Al-Owairdhi, PhD 2020
  • Ashrf Althbiti, PhD 2021, Now: Assistant Professor at Taif University, Saudi Arabia
  • Raed Alsini, PhD 2021, Now: Assistant Professor at King Abdulaziz University, Saudi Arabia
  • Omar Alghushairy, PhD 2021, Now: Assistant Professor at University of Jeddah, Saudi Arabia
  • Chunnan Zhang, MSc 2021
  • Ashwag Sharea, MSc 2021
  • Shrooq Algarni, MSc 2021
  • Chris McVickar, NSF REU intern 2021

Research

  1. 2021-2024: EarthCube Capabilities: OpenMindat - Open Access and Interoperable Mineralogy Data to Broaden Community Access and Advance Geoscience Research, funded by National Science Foundation (NSF)
  2. 2020-2023: GeoWeaver: Building an Open-Source Platform for Enabling Ad Hoc Management, Open Sharing, and Robust Reuse of NASA Earth Data-driven Hybrid AI Workflows, funded by National Aeronautics and Space Administration (NASA)
  3. 2020-2024: RII Track-2 FEC: Leveraging Big Data to Improve Prediction of Tick-Borne Disease Patterns and Dynamics, funded by National Science Foundation (NSF)
  4. 2018-2022: 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)
  5. 2017-2018: Leveraging data science to explore co-relationships between elements and minerals, funded by UI ORED Seed Grant
  6. 2016-2018: MILES: Managing Idaho's Landscapes for Ecosystem Services, funded by National Science Foundation (NSF) through Idaho EPSCoR
  7. 2015-2017: DTDI: Deep Time Data Infrastructure, funded by W.M. Keck Foundation
  8. 2015: Research Data Alliance Adoption Initiatives, funded by National Science Foundation (NSF)
  9. 2012-2016: DCO-DS: Deep Carbon Observatory – Data Science, funded by Alfred P. Sloan Foundation

Recent Publications

  1. Kale, A., Nguyen, T., Harris Jr., F.C., Li, C., Zhang, J., Ma, X., 2022. Provenance documentation to enable explainable and trustworthy AI: A literature review. Data Intelligence. In Press.
  2. Ma, X., 2022. Knowledge graph construction and application in geosciences: A review. Computers & Geosciences, 161, 105082.
  3. Muscente, A.D., Martindale, R.C., Prabhu, A., Ma, X., Fox, P., Hazen, R.M., Knoll, A.H., 2022. Appearance and disappearance rates of Phanerozoic marine animal paleocommunities. Geology, 50(3), 341-345.
  4. Sun, Z., Sandoval, L., Crystal-Ornelas, R., Mousavi, S.M., Wang, J., Lin, C., Cristea, N., Tong, D., Carande, W.H., Ma, X., Rao, Y., Bednar, J.A., Tan, A., Wang, J., Purushotham, S., Gill, T.E., Chastang, J., Howard, D., Holt, B., Gangodagamage, C., Zhao, P., Rivas, P., Chester, Z., Orduz, J., John, A., 2022. A Review of Earth Artificial Intelligence. Computers & Geosciences, 159, 105034.
  5. He, Z., Zhang, C., Ma, X., Liu, G., 2021. Hexadecimal aggregate approximation representation and classification of time series data. Algorithms, 14(12), 353.
  6. Brantley, S., Wen, T., Agarwal, D., Catalano, J., Schroeder, P.A., Lehnert, K., Varadharajan, C., Pett-Ridge, J., Engle, M., Castronova, A.M., Hopper, R., Ma, X., Jin, L., McHenry, K., Aronson, E., Shaughnessy, A.R., Derry, L.A., Richardson, J., Bales, J., Pierce, E.M. 2021. A Vision for the Future Low-Temperature Geochemical Data-scape. Computers & Geosciences, 157, 104933.
  7. Kong, C., Tian, Y., Ma, X., Weng, Z., Zhang, Z., Xu, K., Landslide susceptibility assessment based on different machine learning methods in Zhaoping county of eastern Guangxi. Remote Sensing, 13(18), 3573.
  8. Cui, Z., Chen, Q., Liu, G., Mariethoz, G., Ma, X., 2021. Hybrid Parallel Framework for Multiple-point Geostatistics on Tianhe-2: A Robust Solution for Large-scale Simulation. Computers & Geosciences, 157, 104923.
  9. Wang, C., Hazen, R.M., Cheng, Q., Stephenson, M.H., Zhou, C., Fox, P., Shen, S., Oberhansli, R., Hou, Z., Ma, X., Feng, Z., Fan, J., Ma, C., Hu, X., Luo, B., Wang, J., 2021. The Deep-time Digital Earth Program: Data-driven Discovery in the Geosciences. National Science Review, 8(9), nwab027.
  10. Cui, Z., Chen, Q., Liu, G., Ma, X., Que, X., 2021. Multiple-point geostatistical simulation based on conditional conduction probability. Stochastic Environmental Research and Risk Assessment, 35, 1355–1368.
  11. Que, X., Ma, C., Ma, X., Chen, Q., 2021. Parallel Computing for Fast Spatiotemporal Weighted Regression. Computers & Geosciences, 150, 104723.
  12. Alghushairy, O., Alsini, R., Soule, T., Ma, X., 2021. A review of local outlier factor algorithms for outlier detection in big data streams. Big Data and Cognitive Computing, 5(1), 1.
  13. Que, X., Ma, C., Ma, X., Chen, Q., 2020. A Spatiotemporal Weighted Regression Model (STWR v1.0) for Analyzing Local Non-stationarity in Space and Time. Geoscience Model Development, 13, 6149-6164.
  14. Alsini, R., Almakrab, A., Ibrahim, A., Ma, X., 2020. Improving the Outlier Detection Method in Concrete Mix Design by Combining Isolation Forest and Local Outlier Factor. Construction and Building Materials, 270, 121396.
  15. Alshamrani, R., Althbiti, A., Alshamrani, Y., Ma, X., 2020. Model-Driven Decision-Making in Multiple Sclerosis Research: Existing Works and Latest Trends. Patterns, 1(8), 100121.
  16. He, Z., Long, S., Ma, X., Zhao, H., 2020. A boundary distance-based symbolic aggregate approximation method for time series data. Algorithm. 13(11), 284.
  17. Ma, X., Ma, C., Wang, C., 2020. A new structure for representing and tracking version information in a deep time knowledge graph. Computers & Geosciences, 145(12), 104620.
  18. Alowairdhi, A., Ma., X., 2020. Utilizing fuzzy logic for assessing “FAIRness” of a digital resource. The 2020 International Conference on Computational Science and Computational Intelligence, Las Vegas, NV, USA. In press.
  19. Alghushairy, O., Alsini, R., Ma, X., 2020. An Efficient Local Outlier Factor for Data Stream Processing: A Case Study. The 2020 International Conference on Computational Science and Computational Intelligence, Las Vegas, NV, USA. In press.
  20. Alsini, R., Alghushairy, O., Ma, X., Soule, T., 2020. A Grid Partition-based Local Outlier Factor by Reachability Distance for Data Stream Processing. The 2020 International Conference on Computational Science and Computational Intelligence, Las Vegas, NV, USA. In press.
  21. Alghushairy, O., Alsini, R., Ma, X., Soule, T., 2020. Improving the Efficiency of Genetic-based Incremental Local Outlier Factor Algorithm for Network Intrusion Detection. The 4th International Conference on Applied Cognitive Computing. Las Vegas, NV, USA. In press.
  22. Alsini, R., Alghushairy, O., Ma, X., Soule, T., 2020. A Grid Partition-based Local Outlier Factor for Data Stream Processing. The 4th International Conference on Applied Cognitive Computing. Las Vegas, NV, USA. In press.
  23. Alghushairy, O., Alsini, R., Ma, X., Soule, T., 2020. A Genetic-Based Incremental Local Outlier Factor Algorithm for Efficient Data Stream Processing. Proceedings of the ICCDA 2020 Conference, San Jose, CA. pp. 38-49.
  24. Chen, Q., Liu, G., Ma, X., Li, X., He Z., 2020. 3D stochastic modeling framework for Quaternary sediments using multiple-point statistics: a case study in Minjiang Estuary area, Southeast China. Computers & Geosciences. 136, 104404.
  25. Althbiti, A., Ma, X., 2019. Collaborative Filtering. In: Schintler, L.A., McNeely, C.L. (eds.) Encyclopedia of Big Data. Springer, Cham, Switzerland. 5pp. In Press.
  26. Alowairdhi, A., Ma, X., 2019. Data Brokers and Data Services. In: Schintler, L.A., McNeely, C.L. (eds.) Encyclopedia of Big Data. Springer, Cham, Switzerland. 5pp. In Press.
  27. Alghushairy, O., Ma, X., 2019. Data Storage. In: Schintler, L.A., McNeely, C.L. (eds.) Encyclopedia of Big Data. Springer, Cham, Switzerland. 5pp. In Press.
  28. Alsini, R., Ma, X., 2019. Data Streaming. In: Schintler, L.A., McNeely, C.L. (eds.) Encyclopedia of Big Data. Springer, Cham, Switzerland. 5pp. In Press.
  29. Alshamrani, R., Ma, X., 2019. Deep Learning. In: Schintler, L.A., McNeely, C.L. (eds.) Encyclopedia of Big Data. Springer, Cham, Switzerland. 5pp. In Press.
  30. 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)
  31. He, Z., Liu, G., Ma, X., Chen, C., 2019. GeoBeam: A Distributed Computing Framework for Spatial Data. Computers & Geosciences. 131(10), 15-22.
  32. 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. 11(10), 1186. (Open Access)
  33. 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. 33, 973-987.
  34. 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. 5(3), 397-405.
  35. 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)
  36. 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)
  37. 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.
  38. 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.
  39. 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)
  40. He, Z., Ma, X., 2018. A distributed indexing method for timeline similarity query, Algorithms, 11 (4), 41. (Open Access)
  41. 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)
  42. 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)
  43. 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.
  44. Wang, C., Ma, X., Chen, J., Chen, J., 2018. Information extraction and knowledge graph construction from geoscience literature. Computers & Geosciences, 112, 112-120.
  45. 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)
  46. 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.
  47. Ma, X., 2019. Data Repository. In: Schintler, L.A., McNeely, C.L. (eds.) Encyclopedia of Big Data. Springer, Cham, Switzerland. In Press.
  48. Ma, X., 2019. Metadata. In: Schintler, L.A., McNeely, C.L. (eds.) Encyclopedia of Big Data. Springer, Cham, Switzerland. In Press.
  49. Ma, X., 2019. Spatial Data. In: Schintler, L.A., McNeely, C.L. (eds.) Encyclopedia of Big Data. Springer, Cham, Switzerland. In Press.
  50. Ma, X., 2019. Visualization. In: Schintler, L.A., McNeely, C.L. (eds.) Encyclopedia of Big Data. Springer, Cham, Switzerland. In Press.
  51. 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.
  52. 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.
  53. 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)
  54. 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]
  55. 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.
  56. 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)
  57. 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.
  58. 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.
  59. Ma, X., Fox, P., Narock, T., Wilson, B., 2015. Semantic e-Science. Earth Science Informatics 8 (1), 1-3.
  60. 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]
  61. 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]
  62. 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.
  63. 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.
  64. Ma, X., Fox, P., 2014. A jigsaw puzzle layer cake of spatial data. EOS, Transactions American Geophysical Union 95 (19), 161–161.
  65. 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 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.