On behalf of the editorial board of the
The traditional approach of performing research, namely, reading, formulating hypotheses, and testing, is rapidly evolving and changing in a world in which several millions of articles are published each year. Scientists are nowadays confronted with large numbers of relationships between more and more diverse actors. No person can read the complete literature of their own field. Although this may be considered a threat to science, it may also be considered a unique opportunity to change the way science is carried out. The massive amount of accumulated publications produced over the years probably contains a treasure of minable information. Hence for many young scientists applying theories, methodologies, techniques, and services to support knowledge discovery has become a key competency. “Big data” is not just a buzz-word but a daily concern. It is no surprise to see that the science to develop, test, improve, and apply new methods and facilities has become a fast developing and far-reaching endeavor. This new science integrates research and practice from data mining, knowledge discovery, knowledge infrastructure, predictive analytics, competitive intelligence, informetrics, (semantic) webmetrics, social network analysis, altmetrics, information science, evidence-based policy making, domain informatics, intelligent knowledge production, etc., into a new and coherent knowledge-based discipline.
A major component of this discipline is known as data analytics, the multidimensional approach of examining raw data with the purpose of discovering meaningful patterns, analyzing and communicating the obtained information to specific target groups. Data analytics relies on the simultaneous application of mathematics, statistics, computer programming, and operations research. It makes use of techniques for explanatory research, seeks to identify underlying factors, and performs conceptual modeling, often leading to data visualization to communicate insights. As a consequence we hope that this journal will play an important role in the scholarly development and communication of these new techniques. Yet, the journal, off-spring of the
It is important now to reshape scientific practice by imposing stringent research publishing protocols leading to strict accountability, precision, and verifiability of data and algorithms. This must allow readers to assess the reliability and validity of the work that has been published. The journal
In accordance with the latest developments in journal publishing this journal is an Open Access journal and intends to stay this way.
Let’s think big and welcome the new opportunities, some would say the paradigm shift, in the field of information science to embrace the new role that data and data science are playing.
The JDIS Editors