Dieter Gawlick
Abstract
John Boyd recognized in the 1960's the importance of situation awareness for military operations and introduced the notion of the OODA loop (Observe, Orient, Decide, and Act). Today we realize that many applications have to deal with situation awareness: Customer Relationship Management, Human Capital Management, Supply Chain Management, patient care, power grid management, and cloud services management, as well as any IoT (Internet of Things) related application; the list seems to be endless. Situation awareness requires applications to support the management of data, knowledge, processes, and other services such as social networking in an integrated way. These applications additionally require high personalization as well as rapid and continuous evolution. They must provide a wide variety of operational and functional requirements, including real time processing.
Handcrafting these applications is an almost impossible task requiring exhaustive resources for development and maintenance. Due to the resources and time involved in their development, these applications typically fall way short of the desired functionality, operational characteristics, and ease and speed of evolution. We - the authors - have developed a model enabling the development and maintenance of situation-aware applications in a declarative and therefore economical manner; we call this model KIDS - Knowledge Intensive Data-processing System.
- Boser, B.E., Guyon, I.M., Vapnik, V.N., 1992, A training algorithm for optimal margin classifiers. Proceedings of the 5th Annual ACM Workshop on Computational Learning Theory, ACM Press. Google Scholar
Digital Library
- Boyd, J.R., 1976. Destruction and Creation. U.S. Army Command and General Staff College.Google Scholar
- Chan, E.S., Behrend, A., Gawlick, D., Ghoneimy, A., Liu, Z.H., 2012, Towards a Synergistic Model for Managing Data, Knowledge, Processes, and Social Interaction, SDPS-2012, Society for Design and Process Science.Google Scholar
- Chan E.S., Gawlick D., Ghoneimy A., and Liu Z.H., "Situation Aware Computing for Big Data," SemBIoT 2014.Google Scholar
- Cheng, S., Pecht, M., 2007, Multivariate State Estimation Technique for Remaining Useful Life Prediction of Electronic Products, Association for the Advancement of Artificial Intelligence.Google Scholar
- Crankshaw, D., Bailis, P., Gonzalez, J., Li, H., Zhang, Z., Franklin, M., Ghodsi, A., Jordan, Mi: The Missing Piece in Complex Analysis: Low Latency, Scalable Model Management and Serving with VELOX, CIDR 2015.Google Scholar
- Dempster, A.P., 1968, A generalization of Bayesian Inference. Journal of the Royal Statistical Society.Google Scholar
- D.I. Spivak: "Category Theory for the Scientists," ISBN-13: 978-0262028134 Google ScholarDigital Library
- Fletcher, R., 1970, Generalized Inverses for Nonlinear Equations and Optimization. Numerical Methods for Non-Linear Algebraic Equations. Gordon and Breach, London.Google Scholar
- Gawlick, D., Ghoneimy, A., Liu, Z.H., 2011, How to Build a Modern Patient Care Application. HEALTHINF.Google Scholar
- Gilmour D.L, et al. 2003, Automatic Management of Terms in a User Profile in a Knowledge Management System. United States Patent 6,640,229.Google Scholar
- Guerra, D., Gawlick, U., Bizarro, P., Gawlick, D., 2011, An Integrated Data Management Approach to Manage Health Care Data. BTW 2011.Google Scholar
- Horvitz, E., Mitchell, T., 2010. From Data to knowledge to Action: A Global Enabler for the 21st Century. Data Analytic Series, Computing Community Consortium.Google Scholar
- Howard, R.A., Matheson, J.E., 1984, Influence Diagrams. Readings on the Principles and Applications of Decision Analysis, v.2. Strategic Decisions Group, Menlo Park, CA. Google ScholarDigital Library
- http://en.wikipedia.org/wiki/OODA_loopGoogle Scholar
- http://en.wikipedia.org/wiki/Situation_awarenessGoogle Scholar
- http://mjolnir.cse.buffalo.edu/Google Scholar
- https://www3.uni-bonn.de/idb/research/statesGoogle Scholar
- http://www.cs.iit.edu/~dbgroup/research/gprom.phpGoogle Scholar
- http://www.cs.iit.edu/~dbgroup/research/oracletprov.phpGoogle Scholar
- Kokar, M.M., Matheus, C.J., Baclawski, K., (2009), Ontology-based situation awareness, Journal Information Fusion, Vol 10, Issue 1. Google ScholarDigital Library
- Koller, D., Friedman, N., 2009, Probabilistic Graphical Models: Principles and Techniques, The MIT Press, Cambridge, Massachusetts. Google ScholarDigital Library
- Liu, Z.H., Behrend, A., Chan, E., Gawlick, D., Ghoneimy A., KIDS - A Model for Developing Evolutionary Database Applications. DATA 2012: 129--134.Google Scholar
- Liu Z.H., Gawlick, D., Management of Flexible Schema Data in RDBMSs, CIDR 2015Google Scholar
- Shafer, G., 1976, A Mathematical Theory of Evidence. Princeton University Press, Princeton, NJ.Google Scholar
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