FRC Collaboration Hub

The FRC Collaboration Hub connects academic researchers with forensic practitioners to combine the strengths of real-world forensic experience with large-scale research and project management expertise. These collaborations will result in comprehensive, high-impact research projects that will transition into the laboratory as new and enhanced forensic capabilities.

  • If you are a researcher looking for practitioner support (as a subject matter expert, as a collaborator, as a beta-tester, as a participant in a study, etc.), please submit information about your project to the FRC Collaboration Hub.
  • If you are a practitioner looking to contribute to the advancement of forensic science through research or are interested in providing forensic support for the professional development opportunities that research enables, please review the directory and select projects that you can support.

SEEKING FORENSIC RESEARCH SUPPORT OR COLLABORATION?

Complete the project form to advertise your project to practitioners looking for research opportunities.

Search Collaboration Hub

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FIGG and UHR Survey of Publicly Funded Crime Laboratories

Research Organization:  The National Technology Validation and Implementation Collaborative (NTVIC)
Principal Investigator:  Dr. Garry Bombard (Retired Illinois State Police and Loyola University Chicago), Public Policy Analyst

Funding Source:  None
Other Collaborators Involved:  Deputy Administrator Jennifer Naugle, State of Wisconsin Department of Justice, Division of Forensic Sciences.
Email Address:  gjb4n6@att.net
Phone Number:  773-892-6483
Website/URL:  https://sites.google.com/view/ntvic
Discipline:  Management
Instrumentation Involved:  None

Abstract: 

The National Technology Validation and Implementation Collaborative (NTVIC) is creating a cost/benefit analysis (CBA) for Forensic Investigative Genetic Genealogy (FIGG) and Unidentified Human Remains (UHR). The questionnaire is designed to capture information on the current and future uses of FIGG and UHR within your system or laboratory. The information provided will be utilized as a data starting point, since little data is currently available for the FIGG UHR CBA. The FIGG Working Group (WG) and Subcommittee #1 thanks you for your participation.

Before completing the survey, we highly suggest utilizing the pdf file for the hard data responses, in order to organize your Agency or Laboratory responses. Contact Dr. Bombard, gjb4n6@att.net, for the pdf file. Note: only one response is needed for Agencies.

If you would like more information about the NTVIC and the current WGs, please utilize the link: https://sites.google.com/view/ntvic

The link to the survey is: https://forms.office.com/Pages/ResponsePage.aspx?id=DQSIkWdsW0yxEjajBLZtrQAAAAAAAAAAAAMAANDKRQZUNlRXRTVWVFRKV05VSDdXWUxGTUIxSTFUQi4u

Thank you!
NTVIC FIGG Working Group, Subcommittee #1: Public Entity FIGG Policy & Procedure

Study Dates:  February 1, 2024 – March 29, 2024
Support Requested:  Survey Completion to include various numerical and fiscal data; and current and future uses of FIGG and UHR for your System/Laboratory.
Estimated Participant Time Involved:  30 minutes or less
Deliverable Anticipated:  Peer-reviewed article, Oral Presentation, Poster Presentation, Report on NTVIC Website


 

Development of a standardized classification system for quality issues in forensic science

Research Organization:  Curtin University, Western Australia
Principal Investigator:  Anna Heavey, Manager-Quality, Safety, Training & Risk – Forensic Biology Department, PathWest Laboratory Medicine WA, PhD Candidate – Curtin University

Funding Source:  Curtin University
Other Collaborators Involved:  Professor Simon Lewis (Curtin University), Dr Max Houck (Florida International University), Dr Gavin Turbett (PathWest Laboratory Medicine WA)
Email Address:  anna.heavey@postgrad.curtin.edu.au
Phone Number: 
Website/URL: 
Discipline:  Quality management
Instrumentation Involved:  Online survey tool

Abstract: 

For decades, accredited forensic laboratories world-wide have collected and retained records of non-conforming work and issues detected within the analytical and management system process as routine practice. These “quality issues” represent an invaluable source of data on critical issues affecting forensic science – data which could be used to identify emerging areas of risk, as well as opportunities for improvement, research and innovation, both at the individual agency level and for the field of forensic science as a whole.
Whilst other high-risk fields, such as aviation and medicine, have successfully developed standardized systems for the categorization of critical issues, forensic science has not. Due to the variable, agency-specific nature and classification schemes by which quality issues are recorded, utilizing this vital data for the purposes of interjurisdictional comparison, benchmarking and analysis is extremely challenging.
Utilizing a variety of data sources, this research project aims to develop an evidence-based standardized classification system for quality issues, suitable for use across disciplines within the field of forensic science. Data from forensic agencies on current systems for the management and classification of quality issues is an essential component of the study to ensure that the resulting classification system is practicable and fit-for-purpose.
An online survey for forensic industry experts with experience in the management of quality issues has been developed to capture data on the types of issues that are logged and categorized, along with how information on quality issues is disclosed and communicated. Further information on the project and the survey is provided below.

Study Dates:  February 1, 2024 – May 3, 2024
Support Requested:  Forensic experts involved in the management of quality issues are invited to take part in an online survey, accessible through the following link: https://curtin.au1.qualtrics.com/jfe/form/SV_6MdBv04tZes1hyu The survey should take no more than 30 minutes to complete. The link above includes a Participant Information Form which outlines the project, how the data will be used and what is being requested of participants. The survey can be completed anonymously if preferred.
Estimated Participant Time Involved:  30 minutes for survey completion
Deliverable Anticipated:  Peer-reviewed article, Oral Presentation, PhD thesis


 

Interlaboratory study on 2022-S-0001 Standard Guide for Image Comparison Opinions

Research Organization:  North Carolina State University
Principal Investigator:  Dr. Kelly Meiklejohn

Funding Source:  National Institute of Standards and Technology
Other Collaborators Involved: 
Email Address:  kameikle@ncsu.edu
Phone Number: 
Website/URL: 
Discipline:  Digital Evidence
Instrumentation Involved:  Computer with internet access

Abstract: 

Forensic image comparison is an assessment of the correspondence between features in questioned
items depicted in images and either questioned or known objects or images, for the purpose of
rendering an expert opinion regarding identification or elimination. Images that are sent to forensic laboratories for comparison include but are not limited to faces (and other body parts/areas), vehicles, weapons, clothing, luggage, furniture, landscapes, and buildings. Trained forensic practitioners are tasked with determining whether there is sufficient support to conclude either common source or different source. To harmonize the opinion categories used across the digital multimedia forensic disciplines for image comparisons, a task group consisting of individuals from the Digital/Multimedia Scientific Area Committee (DMSAC) of the Organization of Scientific Area Committees (OSAC) for Forensic Science developed OSAC Proposed Standard 2022-S-0001, Standard Guide for Image Comparison Opinions. Whilst this proposed standard has been extensively developed
with input from a broad range of U.S. based forensic practitioners, the practical utility of
practitioners to reproducibly apply the opinion categories in 2022-S-0001 has not been assessed.
To ensure this standard meets the OSAC program goal of developing technically sound standards
and promoting their adoption through the forensic community, an interlaboratory study focused
on 2022-S-0001 is needed using images that could be routinely encountered in casework.

Study Dates:  October 1, 2023 – March 31, 2024
Support Requested:  We are actively two cohorts of participants: 1) forensic practitioners who have been determined to be competent by their respective agency, organization, or other entity, and currently conduct forensic casework on face, hands, or clothing image comparisons; and 2) laypersons composed of individuals trained in forensic science but not image comparisons, undergraduate/graduate forensic science students, and the general public. Please fill out this Google Form by end of Feb 2024 to register your interest: go.ncsu.edu/osac-img
Estimated Participant Time Involved:  1-2 hours
Deliverable Anticipated:  Peer-reviewed article, Oral Presentation, Poster Presentation


 

Rapid Characterization of Cellular Material in Trace DNA Samples

Research Organization:  Rapid Forensic Cell Typing Inc. & Virginia Commonwealth University
Principal Investigator:  Christopher Ehrhardt

Funding Source:  National Institute of Justice, Virginia Center for Innovative Technology
Other Collaborators Involved:  Virginia Department of Forensic Science, Ontario Centre for Forensic Science, San Francisco Police Department
Email Address:  cehrhardt@vcu.edu
Phone Number: 
Website/URL: 
Discipline:  Biology/Serology
Instrumentation Involved:  Flow cytometry, qPCR assays, STR profiling (flexible on specific instrument platforms)

Abstract: 

We have developed a new method for estimating the time-since-deposition (TSD) for trace DNA samples. TSD signatures are based on morphological and autofluorescence properties of individual epithelial cells that change over time as the sample degrades. These are measured in a rapid and non-destructive fashion using flow cytometry. Previous studies (‘proof-of-concept’) have shown that TSD estimates can establish probative time-intervals for an evidentiary sample, e.g., sample is less than a week old, between one week and one month old, more than six months old. Importantly, this method has been demonstrated for epithelial cells derived from ‘touch’ DNA samples with deposition times ranging between one day and two years.

We are currently looking for collaborators to evaluate and test this method under the operational constraints of DNA casework. Possible areas of collaboration could include (1) resolving TSD signatures from mixture samples, (2) correlating ratio of cells at different TSDs to contributor ratio determined from DNA profiling, (3) optimizing methods for collecting both DNA and TSD from the same sample, (4) examining reliability of TSD for samples collected from different substrates.

Study Dates:  May 1, 2023 – May 1, 2024
Support Requested:  Practitioner feedback and evaluation, collaborative laboratory activities when possible
Estimated Participant Time Involved:  10-20 hrs month (but flexible depending on scope of collaborator interest/involvement)
Deliverable Anticipated:  Peer-reviewed article, Oral Presentation, Poster Presentation


 

Solving the DNA Mixture Conundrum with Single-Cell analysis

Research Organization:  Rutgers University Camden
Principal Investigator:  Catherine Grgicak

Funding Source:  National Institute of Justice
Other Collaborators Involved:  Desmond S. Lun; Ken R. Duffy
Email Address:  c.grgicak@rutgers.edu
Phone Number:  617-913-9728
Website/URL:  http://www.lftdi.com
Discipline:  Biology/Serology
Instrumentation Involved:  Bespoke Software

Abstract: 

We are interested in collaborating with a crime laboratory partner interested in exploring single-cell analysis for forensic purposes. We have a bespoke algorithm capable of interpreting single-cell EPGs from diploid cells across multiple clusters and are now working on expanding the model to be able to address haploid results. This work is of forensic relevance since the single cell likelihood ratio (LR) simplifies to it most informative form — i.e., the number of contributors being one and only one — which means that multiple contributors would not have jointly contributed to the group of cells. Recently, we developed an extension to the bespoke algorithm that allows us to report the weight of evidence (WoE) across all clusters of an admixture of cells, and these WoE were ca. [25-30) regardless of the TrueNOCs. We seek laboratories willing to alpha-test the software using their own samples, or samples we can provide.

Study Dates:  January 1, 2023 – December 31, 2024
Support Requested: 
Estimated Participant Time Involved:  2 hours per month
Deliverable Anticipated:  Peer-reviewed article, Oral Presentation


 

Forensic geology and soil evidence: Current status and needs in Forensic Community

Research Organization:  Arizona State University
Principal Investigator:  Gwyneth Gordon

Funding Source:  none
Other Collaborators Involved:  none
Email Address:  gwyneth.gordon@asu.edu
Phone Number:  4809936600
Website/URL:  https://forms.gle/N6c2qdBWxPPgh2pd7
Discipline:  Trace Chemistry
Instrumentation Involved:  none

Abstract: 

There has been no published survey of law enforcement and forensic practitioners to determine how frequently soil and geolgoical evidence is collected and used. AIM 1) Determine the current frequency of soil collection and forensic analysis AIM 2) Determine what the unmet needs of the forensic and law enforcement communities are for soil and geological evidence. The de-identified information collected will be relayed to the Organization of Scientific Area Committee of the National Institute of Standards and Technology. The PI is a member of the Geological Materials Task Group within the Trace Evidence section of OSAC (https://www.nist.gov/topics/organization-scientific-area-committees-forensic-science/geological-materials-subcommittee), although they are not funding nor are they responsible for this study. This study is approved by the Arizona State University Institutional Research Board as IRB study #00016934.If you have any questions about your rights as a subject/participant in this research, or if you feel you have been placed at risk, you can contact the Chair of the Human Subjects Institutional Review Board, through the ASU Office of Research Integrity and Assurance, at (480) 965-6788.

Study Dates:  December 1, 2022 – May 30, 2023
Support Requested:  distribution and response to survey
Estimated Participant Time Involved:  15 minutes
Deliverable Anticipated:  Peer-reviewed article, Oral Presentation, Poster Presentation


 

Assessment of Forensic Footwear Impression Quality by Human Raters

Research Organization:  West Virginia University
Principal Investigator:  Dr. Jacqueline Speir (with co-investigator Ms. Lily Lin)

Funding Source:  N/A
Other Collaborators Involved: 
Email Address:  el0049@mix.wvu.edu
Phone Number: 
Website/URL:  https://wvu-speir-research-group.shinyapps.io/shiny_shoe/
Discipline:  Footwear
Instrumentation Involved:  Computer

Abstract: 

Shoeprints deposited during the commission of a crime vary in quality as a function of numerous factors, including substrates, media, and the physical activities carried out by perpetrators. This variability impacts the value and quantity of information available in questioned crime scene impressions, and therefore the strength of an examiner’s opinion concerning source attribution. To date, limited research has been conducted to quantify footwear image quality. In response, this study aims to develop a footwear quality assessment model to define footwear impression quality using human assessments as a guide, combined with image factors such as totality, noise, contrast, etc. To collect human ratings, participants will review 55 pairs of impressions via a web browser and using an R-shiny application interface. For each pair of impressions, participants will evaluate the type and reliability of information available in the impressions, as well as the highest level of source-attribution that can be reached based on the totality of information present. Experts’ responses will be used to calculate intra- and inter-rater-reliability, and median/mean/predicted ratings will be used to inform an ordinal logistic regression model designed to predict image quality based on impression features. This study has an IRB (Institutional Review Board) approved protocol on file with WVU (West Virginia University) and can be accessed via the following URL: https://wvu-speir-research-group.shinyapps.io/shiny_shoe/

Study Dates:  November 1, 2022 – May 31, 2023
Support Requested:  Willingness to review and rate images of footwear impressions.
Estimated Participant Time Involved:  1 to 1.5 hours
Deliverable Anticipated:  Peer-reviewed article


 

Latent Print Expert Professional Objectivity Study

Research Organization:  Arizona State University
Principal Investigator:  Tess Neal

Funding Source:  National Science Foundation
Other Collaborators Involved:  Emily Pronin, Princeton University
Email Address:  tess.neal@asu.edu
Phone Number:  602-543-5680
Website/URL:  https://asu.co1.qualtrics.com/jfe/form/SV_3PjsN5D5wwkZU6a
Discipline:  Latent Prints
Instrumentation Involved: 

Abstract: 

Dear Colleague:

Greetings from Arizona State University! We hope you will join us in learning more about the profession. We are conducting a brief survey to help us understand professional objectivity.

We are conducting a brief study (takes up to 10 minutes) of latent print analysis. You are invited to participate if you are a latent print analyst.

If you’d like to know what we find in order to inform your work, please email me (tess.neal@asu.edu) with a request for the findings and I’ll respond with a summary of the results as soon as data collection is complete. We will share the findings in the aggregate – and we ask no individually-identifying questions.

Study Dates:  September 26, 2022 – November 1, 2022
Support Requested: 
Estimated Participant Time Involved:  10 minutes
Deliverable Anticipated:  Peer-reviewed article, Oral Presentation, Poster Presentation


 

Characterization of Footwear in Local Populations

Research Organization:  University of Nebraska, Lincoln
Principal Investigator:  Dr. Susan Vanderplas

Funding Source:  National Institute of Justice, National Institute of Standards and Technology
Other Collaborators Involved:  Dr. Richard Stone (Iowa State), Steve Lund (NIST), Marty Herman (NIST)
Email Address:  susan.vanderplas@unl.edu
Phone Number: 
Website/URL:  https://forensicstats.org/footwear/
Discipline:  Footwear
Instrumentation Involved:  Footwear scanner developed as part of NIJ funded effort

Abstract: 

This project will develop scanning equipment which will be used to capture population footwear class characteristics. In concert, we will develop statistical software which will automatically identify class characteristics and other comparison features. We will collect data from several different populations and compare the prevalence of class characteristics in those populations, using these results to develop guidelines for future data collection projects.

Study Dates:  June 1, 2022 – May 31, 2024
Support Requested:  We are looking for practitioners and law enforcement partners to collect data from local populations
Estimated Participant Time Involved:  Ongoing and dependent on agency
Deliverable Anticipated:  Peer-reviewed article


 

Handwriting Evaluation

Research Organization:  Iowa State University
Principal Investigator:  Dr. Alicia Carriquiry

Funding Source:  National Institute of Standards and Technology
Other Collaborators Involved:  Danica Ommen (Iowa State), John Libert (NIST)
Email Address:  alicia@iastate.edu
Phone Number: 
Website/URL:  https://forensicstats.org/handwriting-analysis/
Discipline:  Handwriting
Instrumentation Involved: 

Abstract: 

The overall goal of this project is to develop tools to aid handwriting and document examiners in their evaluations. The approach we propose treats handwriting as a collection of graphical objects, from which we can extract features. These features are hypothesized to be informative about the writer of the document, so that they can be used to compute a probability of authorship within a closed set of potential authors of the questioned document. (Issues such as motive, access and opportunity also impact the overall probability of writership, but are beyond the scope of this project.) An ongoing challenge is to extend the approach to the situation where the writer of a document is not a member of a closed set.

Study Dates:  April 1, 2022 – May 31, 2023
Support Requested:  Participants will be asked to provide handwriting samples at three data collection sessions, each at least three weeks apart. At each session, participants complete a short survey and transcribe the contents of three prompts, each three times. In an upcoming project phase, we will ask participants to test the handwriter package on their own samples and provide feedback on the user interface, capabilities, limitations, usefulness, and other usability features.
Estimated Participant Time Involved:  3-4 hours total over a period of 2-3 months
Deliverable Anticipated:  Peer-reviewed article


 

Forensic Processing at Crime Labs

Research Organization:  University of Virginia
Principal Investigator:  Dr. Brett Gardner

Funding Source:  National Institute of Standards and Technology
Other Collaborators Involved:  Robin Mejia (Carnegie Mellon), Dan Murrie (UVA), Sharon Kelley (UVA)
Email Address:  bg2dd@virginia.edu
Phone Number: 
Website/URL:  https://forensicstats.org/latent-print-analysis/
Discipline:  Latent Prints
Instrumentation Involved: 

Abstract: 

A primary goal of this project is to provide field data regarding the practice of latent print comparison in crime laboratories. We intend to collaborate with laboratory personnel to examine case management procedures and related data in multiple laboratories. This will expand the limited research of real-world outcomes and allow for inter-laboratory comparison. We will study actual casework and laboratory procedures with the goal of offering recommendations for practices that promote increased accuracy, reliability, and/or efficiency.

Study Dates:  April 1, 2022 – May 31, 2024
Support Requested:  CSAFE researchers have successfully collaborated with crime laboratories to examine case processing variables and clarify work flow procedures in latent print comparison units in recent years (e.g., Rairden et al., 2018; Gardner et al., 2021). Researchers are seeking to collaborate with laboratory personnel to generate and answer questions about each laboratory’s case processing and workflow. Collaboration will aim to answer the laboratories’ specific questions and inform the larger field of case processing within latent print units.
Estimated Participant Time Involved:  Time for the collaboration can vary according to a lab’s specific aims. For laboratories with available case processing data, a roughly one hour consultation with researchers to develop/finalize research questions and explain existing datasets might be all that’s needed at the outset. Laboratories with the desire to begin collecting case processing data can collaborate with researchers as needed to facilitate the development of research questions, data collection, analysis, and interpretation of results.
Deliverable Anticipated:  Peer-reviewed article


 

Triaging Crime Scene Items

Research Organization:  Yale University and University College London
Principal Investigator:  Ifat Levy

Funding Source:  National Institutes of Health (NIH) and Yale University
Other Collaborators Involved:  Ruth Morgan, Mohammed Almazrouei
Email Address:  ifat.levy@yale.edu
Phone Number:  (203) 737-1374
Website/URL: 
Discipline:  Crime Scene Investigation
Instrumentation Involved:  Online Study

Abstract: 

Would you like to participate in a study about factors affecting forensic decision making?

Dear Participant,

Judgments made at or after crime scene investigations can be crucial for legal proceedings. The aim of this study is to explore factors that may play a role in the decision-making of triaging items collected from crime scenes.

We are seeking volunteers to participate in this online study. The inclusion criteria are as follows: an adult crime scene/forensic examiner or supervisor/manager who:

1.Can be involved in the process of prioritizing or triaging items collected from crime scenes; and
2.Can be involved in the selection of testing type for triaged items, including testing for biological traces (like blood) and fingerprints.

The participant can be working in any relevant sections/ departments (such as crime scene, evidence recovery, or biology) as long as they can be involved in both of the above forensic tasks.

Fluency in English is necessary for the completion of the study tasks.

As a participant, you will be asked to evaluate a forensic casework brief and photographs of items collected from a crime scene. Under a hypothetical scenario in which you are the expert assigned to this case, you will make a series of decisions about the case.

You will also be asked to complete a task in which you will make a series of choices between pairs of visual options. You will be asked to choose which of the two options you prefer. For example, you might be asked to choose whether you would prefer an option with a 100% chance of a certain outcome, or an option with another probability of a different outcome.

The study will take approximately 30-40 minutes to complete. There is time for a short break in the middle if you need it.

Participation is voluntary and you are free to quit at any time. Although you will be asked some basic demographic questions (e.g., age), we do not collect any individual identifying information. Thus, all data collected for this study are anonymous.

If you are interested in participating in this study, please:

-Use this link: https://uclresearch.fra1.qualtrics.com/jfe/form/SV_ex66RdIdyb6w8gm
-Make sure that your audio is turned on. Some tasks will require you to hear recordings.
-Take part in this study only if you are using a desktop/ laptop computer.

This study was approved by Yale HIC (#0910005795). If you have any questions about this study, please contact the Principal Investigator, Dr. Ifat Levy, at ifat.levy@yale.edu

Thank you very much.

Yale Decision Neuroscience Lab.

Study Dates:  March 29, 2022 – December 31, 2022
Support Requested:  Participation from practitioners in completing the online study is appreciated. For this study, the participant will be asked whether they would choose to test (or not) crime scene items for two broad types of forensic analyses: biological traces (like blood) and fingerprints. The targeted participants are any crime scene/forensic examiner or supervisor/manager who could be ‘involved’ in the triaging process. The participant can be working in any relevant sections/ departments (such as crime scene, evidence recovery, or biology, etc) if they can be involved in the item prioritization process at any stage (e.g., in the crime scene, in the laboratory, in a managerial meeting). Fluency in English is necessary for the completion of the study tasks.
Estimated Participant Time Involved:  About 30-40 minutes; on one occasion only
Deliverable Anticipated:  Peer-reviewed article, Oral Presentation


 

StegoAppDB: a reference database with variational sources for mobile steganography image forensics

Research Organization:  Iowa State University
Principal Investigator:  Dr. Jennifer Newman

Funding Source:  National Institute of Standards and Technology
Other Collaborators Involved:  Roy Maxion (Carnegie Mellon)
Email Address:  jlnewman@iastate.edu
Phone Number: 
Website/URL:  https://forensicstats.org/digital-evidence/
Discipline:  Digital Evidence
Instrumentation Involved: 

Abstract: 

The CSAFE team at ISU has developed and made public a reference dataset, StegoAppDB, comprised of more than 960,000 highly-provenanced image data created using our unique approach of modeling the steganography (stego) software applications (because their algorithms are not public). The data is used to develop and test algorithms and create new models of the camera pipeline. The next generation of algorithms for detecting hidden images will rely on deep learning algorithms with millions of free parameters (see, e.g., Boroumand et al., 2019). We are growing the database substantially through automation of the image data collection and stego creation process, such as using a drone to collect copious amounts of image data — in order to allow investigators to work with deep learning methods. We propose to add image data selectively to enhance the attractiveness of StegoAppDB for wider use in the forensic imaging community, in the following manner:

1. Add several million outdoor images so that the most successful machine learning techniques, deep learning neural networks, have access to ample data.
2. Add images that have been photo-edited before embedding payload, which we suspect is a common occurrence. In fact, it is speculated that image editing operations may affect steganalysis error rates, but little to nothing is known about this, and certainly nothing for mobile stego images.
3. Include stego apps beyond those currently in StegoAppDB and create an in-house detection tool for verification of our stego process, since no software package exists specifically to detect stego images created with mobile stego apps. We will use emulators and reverse engineering for the stego app analysis to retain accurate parameters for data provenance.

Study Dates:  March 1, 2022 – May 31, 2024
Support Requested:  Availability to discuss the issues with steganography/digital image forensics the crime lab currently has or is looking to address in the future; if a topic of mutual interest is identified, then some sample of data plus a description of the issues encountered.
Estimated Participant Time Involved:  The time is TBD. We would work with the lab to identify some aspect of the issue that could be studied based on the availability of the lab personnel.
Deliverable Anticipated:  Peer-reviewed article


 

Mobile App Evidence Analysis

Research Organization:  Iowa State University
Principal Investigator:  Dr. Yong Guan

Funding Source:  National Institute of Standards and Technology
Other Collaborators Involved: 
Email Address:  guan@iastate.edu
Phone Number: 
Website/URL:  https://forensicstats.org/digital-evidence/
Discipline:  Digital Evidence
Instrumentation Involved: 

Abstract: 

Researchers focus on designing and prototyping EviHunter, a suite of automated Android app analysis tools to analyze and discover Android-app-generated evidential data (i.e., forensic artifacts), stored in local storage, SQLite database, and/or at a remote third-party server. With EviHunter, researchers are working with NIST to build a catalog-like Android app forensic artifact database, which will host the forensic evidential artifacts (e.g., type, location, and data format) that mobile apps generated and stored on the mobile devices or remote servers. We are creating a public web portal to allow digital evidence investigators to query the database and obtain the list of evidential artifacts for the app of interest in a casework.

Researchers are also developing virtual machine-based EviHunter VM images. With the support of EviHunter team, practitioners can utilize their own computers or third-party cloud services, for example Amazon AWS or Google Cloud, to run their own instances of EviHunter to analyze the apps in their caseworks. In addition, the Android apps (latest version, as well as its older versions) analyzed by EviHunter will be hosted in a separate app database, which is only accessible to the EviHunter team. In this project, we will also investigate software optimization and obfuscation techniques that change the resulted apps’ APKs, and conduct third-party SDK analysis. A large-scale evaluation using real-world Android apps and the development of Android app forensic artifacts database are on-going.

Study Dates:  March 1, 2022 – May 31, 2024
Support Requested:  We will work with the crime lab practitioners to get a better understanding on the frequently-used digital evidence types in casework, areas of confusion and potential errors in communicating and analyzing these evidence types. We hope to gain insights on what factors limit the practitioners’ efficacy and efficiency in their daily casework.
Estimated Participant Time Involved:  Varied, depending on actual work and the need for further clarifications. Usually, one or two hours every two months. We plan to visit the crime labs for in-person and/or virtual Zoom meetings, based on the needs and mutual interest/availability.
Deliverable Anticipated:  Peer-reviewed article


 

Blind Proficiency Testing

Research Organization:  Carnegie Mellon, University of Virginia
Principal Investigator:  Robin Mejia

Funding Source:  National Institute of Standards and Technology
Other Collaborators Involved:  Sharon Kelley, Brett Gardner
Email Address:  rmejia@andrew.cmu.edu
Phone Number: 
Website/URL:  https://forensicstats.org/latent-print-analysis/
Discipline:  Latent Prints
Instrumentation Involved: 

Abstract: 

In this project, we will work with laboratories to implement or increase the use of blind proficiency testing. We will document these experiences in CSAFE white papers covering lessons learned and best practices for laboratories of a range of sizes. We will evaluate the results of these programs to provide data of use to laboratories themselves and to better assess LPA as performed in practice, and we will work with laboratories to develop a collaborative infrastructure to support the implementation of blinding in mid-sized and possibly smaller laboratories that do not have the infrastructure of larger laboratories (e.g., HFSC). Our overarching goal is to work with labs to develop and implement their own internal processes for blind proficiency testing.

Study Dates:  March 1, 2022 – May 31, 2024
Support Requested:  CSAFE researchers have collaborated with laboratories to analyze data from existing blind proficiency testing programs and have consulted with laboratories that are considering or are in the process of establishing blind proficiency testing programs. We welcome contacts from laboratories that conduct blind PT or are considering it. Collaborations can range from a single discussion to ongoing logistical or analytical support, potentially including connecting those who would be interested in inter-laboratory collaboration.
Estimated Participant Time Involved:  Varies depending on level of interest.
Deliverable Anticipated:  Peer-reviewed article


 

DNAmix

Research Organization:  Noblis/Bode
Principal Investigator:  Austin Hicklin/Jon Davoren

Funding Source:  NIJ
Other Collaborators Involved: 
Email Address:  dnamix@noblis.org
Phone Number: 
Website/URL:  https://dnamix.edgeaws.noblis.org/
Discipline:  Biology/Serology
Instrumentation Involved: 

Abstract: 

Noblis and Bode Technology are currently seeking forensic laboratories to participate in the DNAmix 2021 study. Please register now: registration closes January 31, 2022!

DNAmix 2021 is a large-scale independent study being conducted to evaluate the extent of consistency and variation among forensic laboratories in interpretations and statistical analyses of DNA mixtures, and to assess the effects of various potential sources of variability. The study will be comprised of four phases. Laboratories are encouraged to participate in the early phases even if they cannot commit to the later phases. The study is being conducted under NIJ grant # 2020-R2-CX-0049.

Register at https://dnamix.edgeaws.noblis.org/

Study Dates:  September 9, 2021 – January 31, 2022
Support Requested: 
Estimated Participant Time Involved:  12 hours
Deliverable Anticipated:  Peer-reviewed article, Oral Presentation


 

DNAmix 2021

Research Organization:  Noblis and Bode Technology
Principal Investigator:  Austin Hicklin and Jon Davoren

Funding Source:  NIJ
Other Collaborators Involved: 
Email Address:  hicklin@noblis.org
Phone Number: 
Website/URL:  https://dnamix.edgeaws.noblis.org
Discipline:  Biology/Serology
Instrumentation Involved: 

Abstract: 

Please participate in DNAmix 2021 — this large-scale independent study is being conducted to evaluate the extent of consistency and variation among forensic laboratories in interpretations and statistical analyses of DNA mixtures, and to assess the effects of various potential sources of variability. The study is being conducted by Noblis and Bode Technology, under a grant from NIJ. Register at https://dnamix.edgeaws.noblis.org

Study Dates:  July 6, 2021 – January 31, 2022
Support Requested:  Participation
Estimated Participant Time Involved:  12 hours
Deliverable Anticipated:  Peer-reviewed article, Oral Presentation


 

Case Contextual Information and its Variation among Forensic Laboratories

Research Organization:  Duquesne University Forensic Science and Law Program
Principal Investigator:  Taylor Hopkins

Funding Source:  Duquesne University
Other Collaborators Involved:  Lyndsie Ferrara, Ph.D.
Email Address:  hopkinst1@duq.edu
Phone Number: 
Website/URL:  https://duq.az1.qualtrics.com/jfe/form/SV_9ZegMKAFFn32gnQ
Discipline:  All disciplines may participate!
Instrumentation Involved: 

Abstract: 

Contextual bias is one of the most common biases discussed in the forensic science community as it can cause scientists to let case contextual information guide their decisions as opposed to the actual evidence. The purpose of my research is to investigate the amount of case contextual information requested by forensic laboratories, via their lab submission forms, and how they vary between forensic disciplines. Data will be collected using a survey that asks participants about their laboratory, laboratory submission form, and laboratory procedures as it relates to case contextual information and how it is transmitted. While more research is being done, current research articles evaluate the procedures within specific disciplines without giving a holistic view of how the forensic science community is combatting bias. The data collected will provide a comprehensive outlook on what different laboratories and disciplines are doing, or not doing, to mitigate the effects of contextual bias.

Study Dates:  June 21, 2021 – August 31, 2021
Support Requested:  Participants of this study will be asked to fill out a survey describing their laboratory, laboratory submission form, and laboratory procedures as it relates to case contextual information and how it is transmitted. Participation is voluntary and the participant may discontinue at any time. The form should take 5-10 minutes to complete. The survey is also anonymous and has been reviewed and approved by the IRB at Duquesne University.
Estimated Participant Time Involved:  5-10 Minutes
Deliverable Anticipated:  Oral Presentation, Poster Presentation


 

Calculation of likelihood ratios from forensic comparison of fired cartridge cases

Research Organization:  Staffordshire University & Aston University
Principal Investigator:  Dr Rachel Bolton-King & Dr Geoffrey Morrison

Funding Source:  Research England, Expanding Excellence in England (E3)
Other Collaborators Involved:  Dr Basu & Dr Vogiatzis, Aston University
Email Address:  r.bolton-king@staffs.ac.uk
Phone Number: 
Website/URL: 
Discipline:  Firearms/Toolmarks
Instrumentation Involved:  Evofinder Data Acquisition System

Abstract: 

Dr Bolton-King is creating a database of scans of 9 mm Luger type cartridge cases fired from semi-automatic pistols. The aim is to scan 10 cartridge cases fired from each of 1000 pistols (10,000 cartridge cases total). We currently only have 30% of our required number and therefore urgently seek support from practitioners in creating test fires for our database.

Ammunition used in test firing should have a brass primer cap and brass cartridge case. The pistols we seek test fires from should have parallel breechface marks and hemispherical firing pin impressions. Example 9mm Luger firearms include Sig Sauer P226 and P228, Hi-Point C9, Beretta 92, Ruger P85, P89 and P94, Smith & Wesson 59, Springfield P9, Browning Hi-Power, CZ 75, Kahr K9, Kel-Tec P-11, and their variants. This list is not comprehensive so please contact Rachel directly for further details if you are able to assist.

Dr Morrison and his team will subsequently exploit the database to develop and validate a system that uses image-processing and machine-learning techniques to calculate likelihood ratios addressing the hypotheses that questioned- and known-origin cartridge casings were fired from the same pistol versus that they were fired from different pistols (pistols that fire 9 mm Luger type ammunition).

Study Dates:  April 25, 2021 – July 23, 2021
Support Requested:  10 fired cartridge cases from as many 9mm Luger firearms with parallel breechface marks and hemispherical firing pin impressions as possible. Submission of the corresponding test-fired bullets would also be of value, but are not essential for this phase of the research.
Estimated Participant Time Involved:  Unknown – it may depend on the number of available and relevant firearms in your collection
Deliverable Anticipated:  Peer-reviewed article, Oral Presentation


 


 

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