|
ИСТИНА |
Войти в систему Регистрация |
ИПМех РАН |
||
Spatial data infrastructure for multidisciplinary geographical scientific researchesтезисы доклада
- Автор: Tatiana Khromova
- Сборник: Book of Abstracts of the International Conference "Global Challenges and Data-Driven Science"
- Серия: 5
- Тезисы
- Год издания: 2017
- Место издания: Copyright 2017 by the Geophysical Center RAS Moscow
- Первая страница: 102
- Последняя страница: 102
- Аннотация: The diversity and complexity of scientific data pose challenges in how it is managed and shared with a diverse community, visualized intuitively, and fused for answering scientific questions. Such challenges are very actual for multidisciplinary scientific researches in Institute of Geography RAS including cryosphere studies. Spatial data infrastructure is created to build a framework that will support satellite imagery, airborne data, climate-weather observations, simulations, and forecasts. Such frameworks allow us to manage data, generate science products, and develop applications that support the end users need. The concept of the data system identifies solutions aimed at assessing the completeness and qualitative characteristics of existing spatial data, exploring the territories in various ways, planning studies to collect additional data and integrating them to work with scientific hypotheses, setting up new research projects and fixing their results, engaging researchers and organizations of Russia and foreign countries. The level of metadata describing the layers of spatial data, combined GIS-projects, as well as cartographic images is allocated as the upper level. Data can be in different projections, coordinate systems, sometimes generally in the form of schemes, but nevertheless have a value for scientific work. Based on them, one can draw conclusions about the study of the territory, justify the execution of works on the collection of new data, generate and refine scientific hypotheses, work with data as evidence, see unexplored places in some respects, i.e. Work with "bad data".
- Добавил в систему: Хромова Татьяна Емельяновна