# _Ex Machina_: Analytical platforms, Law and the Challenges of Computational Legal Science
## 1 Introduction  
The history of science has always been marked by a close connection between the development of new research tools and the understanding of reality. Our ability to advance scientific knowledge is strongly affected by the capacity to conceive and develop new tools, new ways to explore the world: instruments enable science and, at once, advances in science lead to the creation of new tools in a sort of neverending cycle.  
Even if in peculiar ways, this process involves law as well. The design of new scientific tools for various reasons is looming on the horizon within today's debate about the aims and methods of legal studies. Two emerging research fields, Empirical legal studies (ELS) [1; 2; 3; 4] and Computational legal science (CLS) [5; 6; 7; 8; 9], are indeed pushing forward discussions involving not only scientific issues such as the definition of scope and object of legal science, but also methodological questions concerning how and with which instruments law can be studied. The call for a closer integration of empirical analyses into legal scholarship and practice characterising ELS--the latest in a series of empirically flavouredschools of thought going from Law and Economics, to Sociology of law and Legal Realism--inevitably results into the quest for tools enabling a deeper understanding of the factual dimension of the legal universe [1; 10; 11; 12]. Even more so, computational legal scholars are trying to figure out how to exploit the impact that digitisation, Big Data and findings from the area of computational social science can have on the legal science and practice.  
This paper lies at the intersection between the topics and the research fields above mentioned dwelling on how computational tools and methods can favour the emergence of new perspectives in legal research and practice. We focus, in particular, on the role played by analytical platforms here defined as integrated hardware and software infrastructures design to manage data and support scientific analyses. To do that, we draw on the experience and results of a research project exploring innovative and cross-methodological computational approaches to the academic and investigative study of crime.  
Our goal is twofold. A first objective is to present the more recent developments of an ongoing research in which different studies at the borders between law and computational social science--from network analysis [13; 14], to visualisation [15; 16] and social simulation [17]--converge and interact. On the other hand, we aim at raising the debate about the new frontier of computational legal studies, a still poorly explored research field that will probably make important contributions to legal theory and practice in coming years.  
The work is structured as follows: Section 2 sketches the background of our analysis by means of a brief overview of the computational and data-driven turn of science. Sections 3 and 4 focus on the spread of analytical platforms in science and then, more specifically, in the legal field. Section 5 presents the concept, the features and the development prospects of _CrimeMiner_, an analytical platform for the computational analysis of criminal networks. Section 6, finally, is reserved to some brief considerations about the implications that our experience has suggested with reference to the future of legal scholarship and the emerging field of Computational Legal Science.