Informatics as a key methodology for sustainable and repeatable data science and analytics.

Printer-friendly version

Authors:Peter Fox

Abstract:

Many data-savvy researchers and practitioners are now able to utter the phrase "I am a data scientist", or even have new job titles to reflect the Fourth Paradigm of science. As these people come out, educators are pondering how to be deliberate in producing graduates that are data scientists on Day-1 -- versus after years of work experience. Based on 25+ years of data science experience and 8 years of degree program, curricula and course development for data scientists, the need for a strong conceptual and theoretical basis for data science is apparent. Thus, based on the long look back into career paths and choices related to data science this presentation will place Informatics as one of the key integration methodologies to ensure data science is sustainable and repeatable. As a basis, the Drew Conway simplification of three key skills: Math/Stats, Hacking, and Domain expertise will be used as the basis for examples of Informatics-based approaches deemed to be successful, i.e. the "anatomy". Informatics provides the essential "physiology" of a data scientist. The conclusion is that data science must become embedded in all degree and continuing programs, lest it be misconstrued as a separate discipline.

History

DateCreated ByLink
September 13, 2016
19:06:38
Peter FoxDownload

Related Research Areas:

Data Science
Lead Professor: Peter Fox
Description: Science has fully entered a new mode of operation. Data science is advancing inductive conduct of science driven by the greater volumes, complexity and heterogeneity of data being made available over the Internet. Data science combines of aspects of data management, library science, computer science, and physical science using supporting cyberinfrastructure and information technology. As such it is changing the way all of these disciplines do both their individual and collaborative work.

Data science is helping scienists face new global problems of a magnitude, complexity and interdisciplinary nature whose progress is presently limited by lack of available tools and a fully trained and agile workforce.

At present, there is a lack formal training in the key cognitive and skill areas that would enable graduates to become key participants in escience collaborations. The need is to teach key methodologies in application areas based on real research experience and build a skill-set.

At the heart of this new way of doing science, especially experimental and observational science but also increasingly computational science, is the generation of data.

Concepts: eScience
X-informatics
Lead Professor: Peter Fox
Description: In the last 2-3 years, Informatics has attained greater visibility across a broad range of disciplines, especially in light of great successes in bio- and biomedical-informatics and significant challenges in the explosion of data and information resources. Xinformatics is intended to provide both the common informatics knowledge as well as how it is implemented in specific disciplines, e.g. X=astro, geo, chem, etc. Informatics' theoretical basis arises from information science, cognitive science, social science, library science as well as computer science. As such, it aggregates these studies and adds both the practice of information processing, and the engineering of information systems.
Concepts: , eScience