La Serena School for Data Science is a multidisciplinary program with six editions so far and a constant format: during 10-14 days, a group of ∼30 students (15 from the US, 15 from Chile and 1-3 from Caribbean countries) and ∼9 faculty gather in La Serena (Chile) to complete an intensive program in Data Science with emphasis in applications to astronomy and bio-sciences.

The students attend theoretical and hands-on sessions, and, since early on, they work in multidisciplinary groups with their “mentors” (from the faculty) on real data science problems. The SOC and LOC of the school have developed student selection guidelines to maximize diversity.

The program is very successful as proven by the high over-subscription rate (factor 5-8) and the plethora of positive testimony, not only from alumni, but also from current and former faculty that keep in contact with them.

We review Big Data in Astronomy and its role in Astronomy Education. At present all-sky and large-area astronomical surveys and their catalogued data span over the whole range of electromagnetic spectrum, from gamma-ray to radio, as well as most important surveys giving optical images, proper motions, variability and spectroscopic data. Most important astronomical databases and archives are presented as well. They are powerful sources for many-sided efficient research using the Virtual Observatory (VO) environment. It is shown that using and analysis of Big Data accumulated in astronomy lead to many new discoveries. Using these data gives a significant advantage for Astronomy Education due to its attractiveness and due to big interest of young generation to computer science and technologies. The Computer Science itself benefits from data coming from the Universe and a new interdisciplinary science Astroinformatics has been created to manage these data.

In this contribution we report the current stage of the MOLecular Dissociation (MOL-D) database which is a web service within the Serbian virtual observatory (SerVO) and node within Virtual Atomic and Molecular Data Center (VAMDC). MOL-D is an atomic and molecular (A&M) database devoted to the modelling of stellar atmospheres, laboratory plasmas, industrial plasmas etc. The initial stage of development was done at the end of 2014, when the service for data connected with hydrogen and helium molecular ions was done. In the next stage of the development of MOL-D, we include new cross-sections and rate coefficients for processes which involve species such as XH+, where X is atom of some metal. Data are important for the exploring of the interstellar medium as well as for the early Universe chemistry and for the modeling of stellar and solar atmospheres. In this poster, we present our ongoing work and plans for the future.