Systematically assessing the competence level of digital evidence handling

Norway is among the most digitalized countries in the world. For ex-ample, more than 91% of the citizens use mobile phones, and even more than 98% have access to the Internet. Hence, almost all kinds of criminal cases inves-tigated by the Norwegian police include digital evidence. Within the police or-ganization, various roles and responsibilities exist, ranging from first responders arriving and securing crime scenes, to police investigators, analysts, forensic sci-entists, and prosecutors. They will all need to handle digital evidence according to their work tasks. Available skilled personnel with education in digital forensics accounted for only 2% of the available personnel in 2018. To assess the skill level of first responders in securing digital evidence at crime scenes, derive knowledge needs and recommend adequate training, we conducted a large-scale field study. This paper presents our methodology in detail, comprising i) a theoretical com-petency assessment and ii) a practical test. Our findings indicate deficiencies in the examination phase of digital evidence, and there are indications that a digital evidence verification system is missing before the evidence is presented in court. Further findings are discussed in this paper before we propose several activities for decision makers to implement and to improve digital competence and digital understanding for personnel in law enforcement agencies

Multiple Uncertainties in Time-Variant Cosmological Particle Data

Though the mediums for visualization are limited, the potential dimensions of a dataset are not. In many areas of scientific study, understanding the correlations between those dimensions and their uncertainties is pivotal to mining useful information from a dataset. Obtaining this insight can necessitate visualizing the many relationships among temporal, spatial, and other dimensionalities of data and its uncertainties. We utilize multiple views for interactive dataset exploration and selection of important features, and we apply those techniques to the unique challenges of cosmological particle datasets. We show how interactivity and incorporation of multiple visualization techniques help overcome the problem of limited visualization dimensions and allow many types of uncertainty to be seen in correlation with other variables

The Coyote Universe III: Simulation Suite and Precision Emulator for the Nonlinear Matter Power Spectrum

Many of the most exciting questions in astrophysics and cosmology, including the majority of observational probes of dark energy, rely on an understanding of the nonlinear regime of structure formation. In order to fully exploit the information available from this regime and to extract cosmological constraints, accurate theoretical predictions are needed. Currently such predictions can only be obtained from costly, precision numerical simulations. This paper is the third in a series aimed at constructing an accurate calibration of the nonlinear mass power spectrum on Mpc scales for a wide range of currently viable cosmological models, including dark energy. The first two papers addressed the numerical challenges, and the scheme by which an interpolator was built from a carefully chosen set of cosmological models. In this paper we introduce the "Coyote Univers"' simulation suite which comprises nearly 1,000 N-body simulations at different force and mass resolutions, spanning 38 wCDM cosmologies. This large simulation suite enables us to construct a prediction scheme, or emulator, for the nonlinear matter power spectrum accurate at the percent level out to k~1 h/Mpc. We describe the construction of the emulator, explain the tests performed to ensure its accuracy, and discuss how the central ideas may be extended to a wider range of cosmological models and applications. A power spectrum emulator code is released publicly as part of this paper.Comment: 10 pages, 10 figures, minor changes to address referee report, version v1.1 of the power spectrum emulator code can be downloaded at http://www.hep.anl.gov/cosmology/CosmicEmu/emu.html, includes now fortran wrapper and choice of any redshift between z=0 and z=1 (note: webpage now maintained at Argonne National Laboratory

Analyzing and Visualizing Cosmological Simulations with ParaView

The advent of large cosmological sky surveys - ushering in the era of precision cosmology - has been accompanied by ever larger cosmological simulations. The analysis of these simulations, which currently encompass tens of billions of particles and up to trillion particles in the near future, is often as daunting as carrying out the simulations in the first place. Therefore, the development of very efficient analysis tools combining qualitative and quantitative capabilities is a matter of some urgency. In this paper we introduce new analysis features implemented within ParaView, a parallel, open-source visualization toolkit, to analyze large N-body simulations. The new features include particle readers and a very efficient halo finder which identifies friends-of-friends halos and determines common halo properties. In combination with many other functionalities already existing within ParaView, such as histogram routines or interfaces to Python, this enhanced version enables fast, interactive, and convenient analyses of large cosmological simulations. In addition, development paths are available for future extensions.Comment: 9 pages, 8 figure