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Current Events

Ontology Engineering Fall 2018
Description:
This course provides an introduction to ontologies, their uses, and an overview of their application in semantically enabled systems. Ontologies encode term meanings. Ontologies with their declarative encodings of meaning can be used to improve communications between people and can enable computer programs to function more effectively. They provide the foundation for clear and unambiguous interaction. Ontologies have become increasingly common on the web, and class participants will not only learn about the use of ontologies in web-based applications but how to evaluate ontologies for reuse in such applications. Participants will read relevant papers, learn how to critically review ontology papers as well as ontologies themselves, and will participate in at least one group project designing, using, and evaluating ontologies.
To learn how to build computer understandable definitions of terms for usage in automated systems.

Dates: August 1, 2018 - December 31, 2018
Concepts: Semantic Reasoning, Taxonomy, Schema, Linked Data, Semantic Foundation, Controlled Vocabulary, Rule Modeling, Ontology, Semantic Web, Semantic Web Services, Information Model, Provenance, Inference, Vocabulary
Data Analytics 2018 Fall
Description:
Introduce students to relevant methods to recognize and apply quantitative algorithms, techniques and interpretation To develop students' strategic thinking skills, combined with a solid technical foundation in data and model-driven decision-making. Develop ability to apply critical and analytical methods to formulate and solve science, engineering, medical, and business problems Students will examine real-world examples using modern cyberinfrastructure to place statistical and data-mining techniques in context, to develop data-analytic thinking, and to illustrate that proper application is as much an art as it is a science. By the end of the course, students can effectively communicate analytic findings to non-specialists
Introduce students to relevant methods to recognize and apply quantitative algorithms, techniques and interpretation To develop students' strategic thinking skills, combined with a solid technical foundation in data and model-driven decision-making. Develop ability to apply critical and analytical methods to formulate and solve science, engineering, medical, and business problems Students will examine real-world examples using modern cyberinfrastructure to place statistical and data-mining techniques in context, to develop data-analytic thinking, and to illustrate that proper application is as much an art as it is a science. By the end of the course, students can effectively communicate analytic findings to non-specialists Data and Information analytics extends analysis (descriptive and predictive models to obtain knowledge from data) by using insight from analyses to recommend action or to guide and communicate decision-making. Thus, analytics is not so much concerned with individual analyses or analysis steps, but with an entire methodology. The world at-large is confronted with increasingly larger and complex sets of structured/unstructured information; from sensors, instruments, and generated by computer simulations; data is "hidden" in websites, application servers, social networks and on mobile devices. As a nation, assimilating information across disparate domains (e.g., intelligence, economics, science) has the potential to provide improved capabilities for decision makers. In commerce and industry, analytics-driven enterprises are becoming mainstream. Yet, there is a shortfall in the key education skills needed to meet the growing needs. Traditional enterprises are moving toward analytics-driven approaches for core business functions. In the government and corporations, cybersecurity problems are prevalent. The investment in advanced analytics capabilities could potentially be more broadly leveraged today and greater than any prior government investments in computing. Emphasis is now placed on disruptive data and information sources on the Web and Internet: using Web Science and informatics to explore social networks, platform competition, the "long tail" and economic or resource impacts of the search for new findings. Key topics include: advanced statistical computing theory, multivariate analysis, and application of computer science courses such as data mining and machine learning and change detection by uncovering unexpected patterns in data. Introduce students to relevant methods to recognize and apply quantitative algorithms, techniques and interpretation To develop students' strategic thinking skills, combined with a solid technical foundation in data and model-driven decision-making. Develop ability to apply critical and analytical methods to formulate and solve science, engineering, medical, and business problems Students will examine real-world examples using modern cyberinfrastructure to place statistical and data-mining techniques in context, to develop data-analytic thinking, and to illustrate that proper application is as much an art as it is a science. By the end of the course, students can effectively communicate analytic findings to non-specialists

Dates: August 31, 2018 - December 14, 2018
Concepts: Analytics, Machine Learning
Data Science 2018
Description:
To instruct future scientists how to sustainably generate/ collect and use data for their research as well as for others: data science. To instruct future technologists how to understand and support essential data and information needs of a wide variety of producers and consumers For both to know tools, and requirements to properly handle data and information Will learn and be evaluated on the full life-cycle of data and relevant methods, technologies and best practices.

Data science is advancing the inductive conduct of science and is driven by the greater volumes, complexity and heterogeneity of data being made available over the Internet. Data science combines aspects of data management, library science, computer science, and physical science using supporting cyberinfrastructure and information technology. It is changing the way all of these disciplines do both their individual and collaborative work. Key methodologies in application areas based on real research experience are taught to build a skill-set. To instruct future scientists how to sustainably generate/ collect and use data for their research as well as for others: data science. To instruct future technologists how to understand and support essential data and information needs of a wide variety of producers and consumers For both to know tools, and requirements to properly handle data and information Will learn and be evaluated on the full life-cycle of data and relevant methods, technologies and best practices.

To instruct future scientists how to sustainably generate/ collect and use data for their research as well as for others: data science. To instruct future technologists how to understand and support essential data and information needs of a wide variety of producers and consumers For both to know tools, and requirements to properly handle data and information Will learn and be evaluated on the full life-cycle of data and relevant methods, technologies and best practices.


Dates: September 10, 2018 - December 10, 2018
Concepts:


Recent Events

AMIA 2018 Annual Symposium
Description:

Dates: November 3, 2018 - November 7, 2018
Concepts:
International Semantic Web Conference (ISWC) 2018
Description:
ISWC 2018 is the premier international forum, for the Semantic Web / Linked Data Community. Here, scientists, industry specialists, and practitioners meet to discuss the future of practical, scalable, user-friendly, and game changing solutions.

Dates: October 8, 2018 - October 12, 2018
Concepts:
International Semantic Web Conference (ISWC) 2018
Description:
The premier international forum for the Semantic Web and Linked Data Community.

Dates: October 8, 2018 - October 12, 2018
Concepts: