Themes The conference Themes, as selected by the Scientific Committee, highlight some important areas for the future of Forensic Science. The Themes have served as a compass in the development of the scientific program. It is our ambition that EAFS 2022 will contribute to further develop these areas. We have offered the authors of abstracts for EAFS 2022 to, if they so wish, indicate one or more themes that they consider to be linked to their contribution. As many of our authors have chosen to exercise this opportunity we encourage everyone to explore areas outside of their field of expertise with help of the theme symbols displayed for each abstract.
Digital Transformation of the Forensic Process New digitalized products and services are entering our society in many ways as new technologies and innovations become available at an increasing rate. The digital transformation itself is not new, but the effects and impact of the transformation are continuously finding themselves into new areas. It is not only about technology, the transformation also involves people, workflow, judicial and ethical considerations etc. In the field of Forensic Science, we now have the opportunity to improve our way of working by harvesting the benefits from the digital transformation. The question is, how do we accomplish this in a way that will fit the forensic processes and workflows? How do we bring all colleagues on board? And, how do we make sure that we maintain quality and a scientific approach within our forensic processes?
Forensic Data Science Data Science is an interdisciplinary field that combines the use of mathematical methods, data and expert knowledge. It is a fundamental part of Forensic Science as a tool for the evaluation of evidence and to communicate the findings. The increased capabilities to capture, store, share and process data, propelled by the development of Artificial Intelligence and Big Data, are enabling Forensic Scientists to automate and address more complex problems. There is no field within Forensic Science that will not experience the impact of this development. What are the future opportunities in Forensic Data Science? How do we share data and knowledge in order to benefit from these opportunities?
2
