Cursos da Prof. Jian Qin, Syracuse University, US
Terça feira dia 28/10/14 das 17:30 às 20:45 hs
Auditório Azul, 1o andar da Escola de Ciência da Informação da UFMG
(sujeito a alterações, consulte o apoio local)
eScience librarianship, Data science program and curriculum, Research data management, Research projects
Inscrições e custo:
Não há necessidade de inscrições ou pagamentos. Qualquer um inscrito no XV ENANCIB pode assistir ao mini-curso, até a lotação máxima do auditório.
Língua do curso:
Inglês, tradução simultânea para portugues será fornecida pelo evento
PART 1. Research Data Management Services in Data-Driven Science
E-Science is the new paradigm of science that is characterized as data-driven, highly distributed and collaborative, and computing dependent. This paradigm shift has raised new challenges in a largely-untested territory for librarians and information professionals: eScience is generating more data than scientists can manage and the lagging in data management and curation is hurting science research productivity. Research librarians in many countries have initiated services in support of eScience. One of such services is helping researchers manage and curate their research data. Data management for research in science and social sciences involves policy, technological, social, legal, and administrative issues at various levels (research team, administrative, institutional, national, and international).
- An overview of eScience: what it means and why it matters to research librarians
- Key concepts
- Datasets: formats and status in research workflows
- Data repositories and collections: inter-relations between data collections at research group level, institutional level, and community level
- Data policies: data access, sharing, and curation
- Practices of data management and curation in support of eScience
- Approaches to eScience initiatives: virtual campus-wide group, new organizational unit, and others
- Services: consulting, self-archiving, outreaching, and others
PART 2. Educating a New Breed of Data Scientists for Research Data Management
Data scientists play active roles in the design and implementation work of four related areas: data architecture, data acquisition, data analysis, and data archiving. While any data and computing related academic unit could offer a data science program or curriculum, each of them has their own flavors: statistics would weigh heavily toward data analytics and computer science on computational algorithms. The information schools are taking a more holistic approach in educating data scientists. This presentation reports the data science curriculum development and implementation at Syracuse iSchool, which has shaped by the fast changing data-intensive environment not only for science but also for business and research at large. Research projects that we conducted on scientific data management with participation from the e-science student fellows demonstrates the need and significance of educating the new breed of data scientists who have the knowledge and skills to take on the work in the four related areas mentioned above.