**2. Computer science in actual science**

Considering the direction of evolution in scientific research, in order to prepare future professionals who can successfully face the challenges of sciences, education systems must adapt at all levels of education to the interdisciplinary and transdisciplinary trends in scientific

Moreover, one of the main objectives of the educational system should be eliminating the barriers identified in interdisciplinary and transdisciplinary research, in order to accelerate the progress of sciences and technology and through them, as result, to accelerate the prog-

The removal or mitigation of cultural, methodological or knowledge barriers that occur in interdisciplinary and transdisciplinary research can be achieved only through interdisciplinary and transdisciplinary orientation in teaching-learning activities, such that current students, future professionals, will develop from early stage during the years of study those skills that will make them competitive in an interdisciplinary or transdisciplinary scientific

The report emphasizes the absolute necessity for students to be familiarized with various fields of computer science during their schooling. In order to be an effective approach in favor of students, with long-term beneficial effect on the training of future specialists, familiarizing students with various areas of computer science should be done according on their own lean-

Thus, the discipline computer science should be studied in an interdisciplinary way, correlated with other scientific field (or fields), which constitute the subject of interest for every

In the same sense, in another important document, the report of the joint Informatics Europe & ACM Europe Working Group on Informatics Education, we have identified the following

**1.** Generalization of education in computer literacy and computer science (informatics) at all

**3.** Introducing digital literacy and computer science in the curriculum for all European

**4.** Enhancement of The students training in computer science (informatics) so as to make

The two bodies have developed the following recommendations for educational systems

**1.** "All students should benefit from education in digital literacy, starting from an early age and mastering the basic concepts by age 12. Digital literacy education should emphasize not only skills, but also the principles and practices of using them effectively and ethically."

**2.** Creating a Europe based on an Informational Society and an informational economy.

objectives concerning computer science education in Europe [3]:

Europe a major player in Information Technology.

across Europe regarding computer science education [3]:

research.

ress of entire society.

140 Science Education - Research and New Technologies

research activity.

ing skills and interests.

educational levels.

countries.

student.

In the contemporary society, the role of computer science has become and is becoming more and more important in all scientific fields: medicine, pharmacy, economics, education, sociology, physics, chemistry, biochemistry, anthropology, aerospace and others.

The evolution of computer science provides to other scientific research fields powerful instruments for research: high capacity computational systems, able to manage huge databases, powerful and sophisticated calculus algorithms for data analysis and data mining and dedicated software for computer-assisted modeling and simulation. At the same time are being built increasingly sophisticated measuring devices based on highly specialized sensors and biosensors, that incorporate dedicated software packages for automatic processing of collected data. Fall into this category devices used in the study of outer space, devices for measuring biological parameters in medicine, biotechnology, marine research and other similar devices used in physics, chemistry and others.

All these specialized devices, dedicated for gathering and automatic processing of large amounts of data on the one hand, have led to spectacular developments in various scientific fields like medicine, pharmacy, physics, biophysics, chemistry, biochemistry and others, and on the other hand, they have led to the emergence of new sciences, such as exo-oceanography, exo-biology, computing sociology, computing anthropology, computing ecology, computing toxicology and others.

The huge amount of data collected in all scientific fields using specialized devices allow the possibility to use these data in order to elaborate specific prognosis (population health prognosis, population movement prognosis, meteorological and exo-meteorological prognosis, environment evolution prognosis and others). As a result, in almost all fields of research are extensively used experimental models and simulations. This relatively new approach, belonging to the past 25–30 years, has made simulation and modeling to be considered an <<emerging "third leg" of Scientific Investigation>> [4].

Computer science is an extremely abstract, intellectually challenging field, because programming technologies operate with very abstract and codified representations for the surrounding reality. For this reason, especially in the initial stages, interdisciplinary and transdisciplinary research projects involving computer science are faced with certain difficulties, especially concerning the transposition into an abstract representation specific to computer science, the experimental reality belonging to a different scientific field.

These difficulties occurring in research activities constitute another reason for teaching computer science discipline, at all levels of education, in an interdisciplinary manner. Through teaching computer science in an interdisciplinary and transdisciplinary manner, on one hand the future specialist in computer science will have early formed the necessary skills to conduct a dialogue with specialists belonging to other scientific fields, and on the other hand, for specialists from different scientific fields (physics, chemistry, biochemistry, medicine), computer science will no longer be a stranger and abstract area.

Another important issue is that in the era of Big Data, characterized by huge databases in all fields of science (medicine, genetics, sociology, anthropology) collected through most various channels, one of the most challenging scientific work is to identify patterns and consistent elements of knowledge in large databases.

Big Data technology development determined that currently some of of the most increasingly used computing applications and algorithms, used today by researchers in most fields of science, are those dedicated for Data Mining.

In the scientific literature, it is defined the activity of Knowledge Discovery in Databases (KDD) as "the process of identifying valid, novel, potentially useful and ultimately understandable patterns in data" [5]. The most powerful tool used for Knowledge Discovery in Databases, Data Mining represents "a collection of methods of data analysis coming from different fields of computer science, artificial intelligence and statistics" [5].

Taking into account that, as we noted above, computer science is deeply involved in all current sciences, it is considered that "interdisciplinary computer science is becoming the norm" [6].

They are science or scientific results, which could not exist in the absence of computer science. An example of this is the genomic sequencing, a remarkably successful genetics result, which would not be achieved in the absence of tools provided by computer science [6].

In other sciences, like the aerospace sciences or exo-meteorology, they could not exist as scientific fields itself in the absence of computer science, because both in the collection of scientific data and in the processing thereof are being used computer systems and devices coordinated by computer systems (space probes, spatial robots, artificial satellites).
