What Do Forensic Laboratories Need to Succeed? A DOJ Needs Assessment Explains

examiner analyzing a shoe

How can organizations like CSAFE and the federal government help forensic laboratories succeed? What would be most beneficial as they seek to address the needs of the field?

The National Institute of Justice recently released a report to Congress asking these questions and more as they examined the interconnected relationship between forensic laboratories and the criminal justice system. The report details the results of a national needs assessment of forensic science service providers conducted in 2017-2018.

From the report:

“Forensic laboratories and ME/C (medical examiner/coroner’s) offices are constantly working to address the needs of the field, balancing operational priorities to meet stakeholder requests while introducing innovative solutions to solve emerging criminal justice questions. This needs assessment compiled demonstrative evidence of how the field is adapting to advancements in technology, the volume and types of forensic evidence, and the evolving needs of the justice system.”

The report outlines key needs in a variety of areas, such as sufficient funding and strategic planning to process increasing amounts of forensic evidence and continued efforts to strengthen quality assurance measures. The report also highlights challenges and promising practices, as well as addresses special topics. The American Academy of Forensic Sciences responded positively to this effort, and thanks Congress for its long-time support of forensic science.

Review the full report to learn more, and discover other ways the Department of Justice works to improve forensic science on their website.

NIST Ballistics Teams Preserves Kennedy Assassination Bullets

The NIST ballistics team recently undertook a unique project with great historical significance. Researchers created digital replicas of the bullet that fatally wounded beloved President John F. Kennedy using a 3D surface scanning microscope.

In partnership with the National Archives, NIST work will provide public access to these important artifacts while ensuring the originals remain safely preserved. For NIST, this project was simply about historic preservation. But now, anyone can perform forensic analysis of the bullet without risking damage to the original.

In a NIST article published on December 5, 2019, NIST explains the details.

“In the lab, the NIST ballistics team used a technique called focus variation microscopy to image the artifacts. At each location along the object’s surface, the microscope created a series of images at different focal distances. By analyzing which parts of those images were in focus, the microscope measured the distance to the object’s surface features. As the lens moved across the object, it built a 3D surface map of the microscopic landscape beneath it, like a satellite mapping a mountain range.”

While this was a special project, NIST researchers do spend significant time imaging bullets in their day-to-day work. Historically, forensic examiners match bullets by viewing them under a comparison microscope. They examine striations on a pair of bullets or microscopic photographs of those bullets to determine a match. The NIST ballistics team is working to provide greater detail and accuracy than 2D methods by using 3D surface maps.

It’s also developing methods so that, instead of just saying whether or not two bullets appear to match, forensic examiners will be able to statistically quantify their degree of similarity. CSAFE partners with NIST in this effort, conducting research to develop new and improved scientific methods for firearms and tool mark analysis.

Read more about the Kennedy bullet on the NIST website, and learn more about CSAFE advancements in bullet technology in our news section. We also invite you to visit our tools page and data portal, where you can find helpful resources to implement in your forensic analysis work.

Insights: A Robust Approach to Automatically Locating Grooves in 3D Bullet Land Scans


A Robust Approach to Automatically Locating Grooves in 3D Bullet Land Scans


Land engraved areas (LEAs) can be important distinguishing factors when analyzing 3D scans from bullets. Creating a 3D image of an LEA requires examiners to also scan portions of the neighboring groove engraved areas (GEAs). Current modeling techniques often struggle to separate LEAs from GEAs. CSAFE researchers developed a new method to automatically remove GEA data and tested this method’s performance against previously proposed techniques.

Lead Researchers

Kiegan Rice
Ulrike Genschel
Heike Hofmann


Journal of Forensic Sciences

Publication Date

13 December 2019



Present and discuss automated methods for identifying “shoulder locations” between LEAs and GEAs.

The Study

  • Rice et al. gathered 3D scans of 104 bullets from two available data sets (Hamby 44 and Houston), resulting in a total of 622 LEA scans.
  • They removed the curvature from these 3D scans to make 2D crosscuts of each LEA.
  • Using the 2D crosscuts, the team estimated the shoulder locations between LEAs and GEAs using three different models:


A function (in this case, one available through the open-source “bulletxtrctr” package) which applies a rolling average to smooth out outliers in data.

Robust Linear Model:

A quadratic linear model that minimizes absolute deviations and is therefore less influenced by outliers.

Robust Locally Weighted Regression (LOESS):

A weighted average of many parametric models to fit subsets of data.


Hamby set 44

Houston test set

areas of misidentification:

In this graphic, an Area of Misidentification less than 100 is considered a small deviation, between 100 and 1000 is medium, and greater than 1000 is a large deviation.

  • The Robust LOESS model significantly outperformed the Rollapply and Robust Linear models, resulting primarily in small deviations across all test sets.
  • Conversely, the Robust Linear model had the weakest performance of all three, with mostly large deviations across both Houston sets, and only outperforming the Rollapply model in the right shoulder section of the Hamby 44 set.
  • These results were expected, as the Robust LOESS model is intended to be flexible and handle areas that a quadratic linear model would fail to address.



Both the Hamby 44 and Houston datasets used firearms from the same manufacturer. Future studies can expand on these findings by using a wider variety of barrel types, including different caliber sizes, manufacturers and nontraditional rifling techniques.

Insights: Quantifying the Association Between Discrete Event Time Series with Applications to Digital Forensics


Quantifying the Association Between Discrete Event Time Series with Applications to Digital Forensics

Effects of Proficiency and Cross-examination


Digital devices provide a new opportunity to examiners because for every user event — like opening software, browsing online, or sending an email — an event time series is created, logging that data. Yet, using this type of user-generated event data can be difficult to correlate between
two devices for examiners. The research team set out to quantify the degree of association between two event time series both with and without population data.

Lead Researchers

Christopher Galbraith
Padhraic Smyth
Hal S. Stern


Journal of the Royal Statistical Society

Publication Date

January 2020

The Goals


Investigate suitable measures to quantify the association between two event series on digital devices.


Determine the likelihood that the series were generated by the same source or by different sources –– ultimately to assess the degree of association between the two event series.


Researchers explored a variety of measures for quantifying the association between two discrete event time series. They used multiple score functions to determine the similarity between the series. These score functions were discriminative for same- and different-source pairs of event series.

The following methods for assessing the strength of association for a given pair of event series proved most accurate:


Constructing score-based likelihood ratios (SLRs) that assess the relative likelihood of observing a given degree of association when the series came from the same or different sources. This uses a population-based approach.


Calculating coincidental match probabilities (CMPs) to simulate a different-source score distribution via what the research team refers to as sessionized resampling when working with a single pair of event series. When a sample from a relevant population is not available, this method still produces accurate results.

KEY TAKEAWAYS for Practitioners


The population-based approach of SLRs remains the preferred technique in terms of accuracy and interpretability.


The resampling technique using CMPs shows significant potential for quantifying the association between a pair of time event series, helping examiners determine the likelihood that two different time series were created by the same person, especially when no population sampling data is available.


With multiple-event series, combining these techniques could be valuable for pattern mining to determine which event series are associated with one another.


Developments in this area have the capacity to positively impact work in forensic and cybersecurity settings.

Next Steps


Both SLR and CMP techniques require more extensive study and testing before being used in practice by forensic examiners.

All techniques that are described are implemented in the open-source R package assocr.

Texas Forensic Science Commission Advises Implementation of OSAC Registry Standards for Crime Laboratories

In a unanimous October 2019 decision, the Texas Forensic Science Commission recommended that all crime laboratories accredited to perform forensic analysis in the State of Texas voluntarily adopt the Organization of Scientific Area Committees for Forensic Science (OSAC) standards for forensic science. The Commission is the first regulatory body in the United States to recommend the implementation of these standards.

OSAC standards found on the OSAC Registry describe best practices, explain scientific protocols and define minimum requirements for the field. Each standard aims to ensure the reliability and reproducibility of forensic analysis results.

CSAFE partner Houston Forensic Science Center has already announced the laboratory will adopt these standards. CEO and President Peter Stout states that his team continuously seeks to improve the services provided to the community, and adopting these standards is the next step in the process.

NIST created OSAC in 2014 in partnership with the Department of Justice. The organization is comprised of roughly 560 members with expertise in 25 forensic disciplines, in addition to general expertise in scientific research, measurement science, statistics, law, and policy. At this time, 12 standards are available on the OSAC Registry, with more than 200 in development.