Big Data Publications of Kenneth Paul Baclawski

1. D. Kerr, K. Braithwaite, N. Metropolis, D. Sharp and G.-C. Rota. Science, Computers and the Information Onslaught. Academic Press. (1984)

2. K. Baclawski, S. Contractor and R. Wilmot. File access patterns: self-similarity and time evolution. NU-CCS-89-19. Northeastern University, College of Computer Science. (1989)

3. K. Baclawski. Materials & Methods Monitor. Northeastern University. (1992)

4. K. Baclawski, R. Futrelle, C. Hafner, M. Pescitelli, N. Fridman, B. Li and C. Zou. Data/knowledge bases for biological papers and techniques. In Proc. Sympos. Adv. Data Management for the Scientist and Engineer 23-28. (1993) [pdf]

5. K. Baclawski, R. Futrelle, N. Fridman and M. Pescitelli. Database techniques for biological materials & methods. In First Int. Conf. Intell. Sys. Molecular Biology 21-28. (1993) [pdf]

6. K. Baclawski, R. Futrelle, C. Hafner, M. Pescitelli, N. Fridman, B. Li and C. Zou. M&M-Query: Materials & Methods Knowledge Base and Query System. NU-CCS-93-06. Northeastern University, College of Computer Science. (1993)

7. K. Baclawski and J.E. Smith. KEYNET: Fast indexing for semantically rich information retrieval. NU-CCS-94-06. Northeastern University, College of Computer Science. (1994) [pdf]

8. K. Baclawski, R. Futrelle, C. Hafner, M. Pescitelli, N. Fridman, B. Li and C. Zou. Data/knowledge bases for biological papers and techniques. Northeastern University. (1993)

9. K. Baclawski, R. Futrelle, C. Hafner, M. Pescitelli, N. Fridman, B. Li and C. Zou. M&M-Query: Materials & Methods Knowledge Base and Query System. Northeastern University. (1993)

10. K. Baclawski. Materials & Methods Monitor. Northeastern University. (1993)

11. C. Hafner, K. Baclawski, R. Futrelle, N. Fridman and S. Sampath. Creating a Knowledge Base of Biological Research Papers. In Proc. Second Int. Conf. Intell. Sys. Molecular Biology 147-155. (1994) [pdf]

12. K. Baclawski and D. Simovici. An abstract model for semantically rich information retrieval. NU-CCS-94. Northestern University, Boston. (March 1994)

13. K. Baclawski and N. Fridman. M&M-Query: Database support for the annotation and retrieval of biological research articles. NU-CCS-94-07. Northeastern University, College of Computer Science. (1994) [pdf]

14. K. Baclawski and J.E. Smith. High-performance, distributed information retrieval. NU-CCS-94-05. Northeastern University, College of Computer Science. (1994) [pdf]

15. K. Baclawski and J.E. Smith. A unified approach to high-performance, vector-based information retrieval. Northeastern University, College of Computer Science. (1994) [pdf]

16. K. Baclawski and J.E. Smith. A distributed approach to high-performance information retrieval. Northeastern University, College of Computer Science. (1994) [pdf]

17. K. Baclawski and J.E. Smith. KEYNET: An architecture and protocol for high-performance semantically rich information retrieval. Northeastern University, College of Computer Science. (1994) [pdf]

18. K. Baclawski. Semantic knowledge management and retrieval engine. Software Amplification. (1994)

19. K. Baclawski. Materials & Methods Monitor. Northeastern University. (1994)

20. K. Baclawski. Distributed Computer Database System And Method. United States Patent and Trademark Office. (December 2, 1997) [pdf]

21. K. Baclawski. Long time, no see: categorization in information science. In Essays on the Future. In Honor of the 80th Birthday of Nick Metropolis, S. Hecker and G.-C. Rota (Ed), 11-26. Birkhauser, Cambridge, MA. (1997) [pdf]

22. K. Baclawski. Scientific Databases Project Final Report. Northeastern University. (1997) [pdf]

23. K. Baclawski. Semantic knowledge management and retrieval engine. Jarg Corporation. (1998)

24. K. Baclawski, J. Cigna, M.M. Kokar, P. Mager and B. Indurkhya. Knowledge Representation and Indexing Using the Unified Medical Language System. In Pacific Symposium on Biocomputing 5:490-501. (2000) [pdf][ppt]

25. K. Baclawski. Distributed Computer Database System And Method Employing Intelligent Agents. United States Patent and Trademark Office. (February 20, 2001) [pdf]

26. K. Baclawski. Search System And Method Based On Multiple Ontologies-B1. United States Patent and Trademark Office. (July 23, 2002) [pdf]

27. K. Baclawski. Distributed Computer Database System And Method For Performing Object Search. United States Patent and Trademark Office. (October 8, 2002) [pdf]

28. K. Baclawski. Knowledge Extraction System And Method. United States Patent and Trademark Office. (October 22, 2002) [pdf]

29. K. Baclawski. Distributed Computer Database System And Method Employing Hypertext Linkage Analysis. United States Patent and Trademark Office. (January 7, 2003) [pdf]

30. K. Baclawski. Distributed Computer Database System And Method Employing Intelligent Agents. United States Patent and Trademark Office. (March 18, 2003) [pdf]

31. K. Baclawski. Web Technologies for Bioinformatics. Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School. (October 2003) [pdf][ppt]

32. K. Baclawski. Mining the Biomedical Research Literature. Department of Statistics, Harvard University. (November 2003) [pdf][ppt]

33. K. Baclawski. Knowledge Extraction System and Method. The United Kingdom Patent Office. (September 7, 2004) [pdf]

34. K. Baclawski. Information Retrieval Apparatus for Processing a Query for Retrieval of Information from a Database. The United Kingdom Patent Office. (November 2, 2004) [pdf]

35. K. Baclawski. Search System and Method Based on Multiple Ontologies. European Patent Office. (February 14, 2007)

36. P. Yim, M. Dean, L. Obrst and K. Baclawski. Leveraging OOR. Implementing 'Big Open Data' in government through Open Collaboration - case examples and possibilities . (May 17, 2012) [pdf]

37. K. Baclawski, Y. Yin and H. Yu. Biomedical Terminology in the ICU. (October 29, 2012)

38. K. Baclawski. Warehousing-Verfahren und verteiltes Computer-Datenbanksystem für das Warehousing. The German Patent Office. (October 4, 2012)

39. K. Baclawski. Knowledge Extraction Method for Distributed Computer Databank System Processes Received Question for Retrieval of Information Corresponding to Answer. The German Patent Office. (September 27, 2001)

40. K. Baclawski and A. Thessen. Tackling the Variety Problem in Big Data. In Ontology Summit 2014 Big Data and Semantic Web Meet Applied Ontology . http://bit.ly/2xefFQT (February 13, 2014) [talk][links]

41. K. Baclawski and A. Thessen. Tackling the Variety Problem in Big Data. In Ontology Summit 2014 Big Data and Semantic Web Meet Applied Ontology. (February 20, 2014) [pdf][talk]

42. K. Baclawski and A. Thessen. Tackling the Variety Problem in Big Data. In Ontology Summit 2014 Big Data and Semantic Web Meet Applied Ontology. (March 27, 2014) [pdf][talk]

43. K. Baclawski and A. Thessen. Tackling the Variety Problem in Big Data. In Ontology Summit 2014 Big Data and Semantic Web Meet Applied Ontology. (April 3, 2014) [pdf][talk]

44. K. Baclawski and A. Thessen. Tackling the Variety Problem in Big Data. In Ontology Summit 2014 Symposium: Big Data and Semantic Web Meet Applied Ontology. (April 28, 2014) [pdf][talk]

45. K. Baclawski. Semantic Interoperability for Big Data. In Federal Meetup. (August 11, 2014) [pdf]

46. K. Baclawski. Situation Awareness and Decision Making. (February 12, 2015) [pdf]

47. X. Zhang and K. Baclawski. A Scalable Data, Knowledge and Processes Management System (SKPMS). Northeastern University. (2015)

48. K. Baclawski, E.S. Chan, D. Gawlick, A. Ghoneimy, K. Gross, Z.H. Liu and X. Zhang. Framework for Ontology-Driven Decision Making. Applied Ontology 12(3-4):245-273. IOS Press, The Netherlands. https://bit.ly/2LYPszt (2017) [pdf]

49. G. Berg-Cross and K. Baclawski. Semantic Interoperability in the GeoSciences. In Ontology Summit 2016: Framing the Conversation: Ontologies within Semantic Interoperability Ecosystems. http://bit.ly/2fOGmsO (February 25, 2015) [links]

50. G. Berg-Cross and K. Baclawski. Semantic Integration for Geographically Distributed Sensor and Control Systems. In Ontology Summit 2016: Framing the Conversation: Ontologies within Semantic Interoperability Ecosystems. Ontolog Forum. Slide Presentation (March 31, 2016) [links]

51. K. Baclawski. The KIDS Ontology Version 2.0. https://bit.ly/3EJbzG2 (2016) [KIDS Ontology Version 2.0]

52. K. Baclawski. Toward Combining Ontologies and Machine Learning for Improving Decision Making. In Ontology Summit 2017: AI, Learning, Reasoning, and Ontologies. http://bit.ly/2DVUS9D (March 15, 2017) [pdf][links]

53. K. Baclawski, M. Bennett, G. Berg-Cross, D. Fritzsche, T. Schneider, R. Sharma, R.D. Sriram and A. Westerinen. Ontology Summit 2017 Communiqué: AI, Learning, Reasoning and Ontologies. Applied Ontology 13(1):3-18. IOS Press, The Netherlands. https://bit.ly/2PWRTrO (2018) [pdf][links]

54. K. Baclawski, M. Bennett, G. Berg-Cross, D. Fritzsche, R. Sharma, J. Singer, J. Sowa, R.D. Sriram, M. Underwood and D. Whitten. Ontology Summit 2019 Communiqué: Explanation. Applied Ontology 15(1):91-107. IOS Press, The Netherlands. http://bit.ly/2TDdyTG (2020) [pdf][Communiqué]

55. E. Wetherbee, K. Baclawski, G. Wang, K. Gross, A. Chystiakova, D. Gawlick, Z. Liu and P. Sonderegger. System and Method for Ensuring that the Results of Machine Learning Models can be Audited. United States Patent and Trademark Office. (April 2, 2024) [pdf]

56. K. Baclawski, M. Bennett, G. Berg-Cross, D. Fritzsche, R. Sharma, J. Singer, J. Sowa, R.D. Sriram, M. Underwood and D. Whitten. Ontology Summit 2020 Communiqué: Knowledge Graphs. Applied Ontology 16(2):229-247. IOS Press, The Netherlands. (2021) [links]

57. K. Baclawski, G. Berg-Cross, C. Miles, D. Miles, T. Schneider and R. Sharma. Modeling with Knowledge Graphs. J. Wash. Acad. Sci. 107(3):1-10. (2021) [Journal]

58. K. Baclawski, G. Berg-Cross, M. Bennett, L. Dickerson, T. Schneider, S. Seppälä, R. Sharma, R. Sriram and A. Westerinen. Ontology Summit 2021 Communiqué: Ontology Generation and Harmonization. Applied Ontology 17(2):233-248. IOS Press, The Netherlands. (2022) [Web page]

59. M. Liu, P. Sonderegger, K. Baclawski, D. Gawlick, A. Chystiakova, G. Wang, Z.H. Liu, H. Balasubramanian and K.C. Gross. Optimizing a Prognostic-Surveillance System to Achieve a User-Selectable Functional Objective. United States Patent and Trademark Office. (February 2, 2023) [pdf]

60. J. Courtney, K. Baclawski, D. Gawlick, K.C. Gross, G. Wang, A. Chystiakova, P. Sonderegger and Z.H. Liu. Machine Learning Traceback-Enabled Decision Rationales as Models for Explainability. United States Patent and Trademark Office. (July 28, 2022) [pdf]

61. J. Rohrkemper, P. Sonderegger, A. Chystiakova, K. Baclawski, D. Gawlick, K.C. Gross, Z. Liu and G. Wang. Root Cause Analysis for Deterministic Machine Learning Model. United States Patent and Trademark Office. (March 2, 2023) [pdf]

62. J. Rohrkemper, K. Baclawski, D. Gawlick, K.C. Gross, G. Wang, A. Chystiakova, P. Sonderegger and Z. Liu. Recommendation Generation Using Machine Learning Data Validation. United States Patent and Trademark Office. (May 18, 2023) [pdf]

63. K. Baclawski, G. Berg-Cross, M. Bennett, R. Rovetto, R. Sharma and R. Sriram. Ontology Summit 2022 Communiqué: Dealing with Disasters. J. Wash. Acad. Sci. 108(3):17-48. (2022) [Dealing with Disasters]

64. K. Baclawski. Principles of Data Management and Stewardship. Ontolog Forum. (2022) [pdf]

65. P. Sonderegger, K. Baclawski, G. Wang, A. Chystiakova, D. Gawlick, Z.H. Liu and K.C. Gross. Automatically adapting a prognostic-surveillance system to account for age-related changes in monitored assets. United States Patent and Trademark Office. (October 10, 2023) [pdf]

66. K. Baclawski, D. Gawlick, K.C. Gross and Z.H. Liu. Prognostic-Surveillance Technique that Dynamically Adapts to Evolving Characteristics of a Monitored Asset. United States Patent and Trademark Office. (October 24, 2023) [pdf]

67. M. Gerdes, K. Baclawski, D. Gawlick, K.C. Gross, G. Wang, A. Chystiakova, P. Sonderegger and Z.H. Liu. Dependency Checking for Machine Learning Models. United States Patent and Trademark Office. (November 23, 2023) [pdf]

68. K. Ru, K. Baclawski, P. Sonderegger, D. Gawlick, A. Chystiakova, G. Wang, M. Gerdes and K.C. Gross. Bias Detection in Machine Learning Tools. United States Patent and Trademark Office. (August 1, 2024) [pdf]