Rail Safety: Targeting Oversight and Assessing Results

Rail safety has emerged as a significant issue in the past two years as a result of two major factors: a statistical lack of improvement in rail safety in the past decade, and a catalytic event in the form of a major derailment involving loss of life at Graniteville, South Carolina, in January 2005. The convergence of long-term leveling of rail safety indicators and the shock of a major rail accident prompted the Senate Appropriations Committee to ask the Government Accountability Office to assess the oversight role of the Federal Railroad Administration, the modal agency of the U.S. Department of Transportation charged with overseeing rail safety. The report is a reminder of the continuing importance of regulatory activities and the general movement in federal management toward greater use of data and performance measures since the Government Performance and Results Act of 1993.     

Models of E‐Government: Are They Correct? An Empirical Assessment

Research into e-government is relatively new. Nevertheless, much contemporary thinking and writing about e-government is driven by normative models that appeared less than a decade ago. The authors present empirical evidence from three surveys of local e-government in the United States to test whether these models are accurate or useful for understanding the actual development of e-government. They find that local e-government is mainly informational, with a few transactions but virtually no indication of the high-level functions predicted in the models. Thus, the models do not accurately describe or predict the development of e-government, at least among American local governments. These models, though intellectually interesting, are purely speculative, having been developed without linkage to the literature about information technology and government. The authors offer grounded observations about e-government that will useful to scholars and practitioners alike.     

Evaluating Bioinformatic Pipeline Performance for Forensic Microbiome Analysis*,†,‡

Microbial communities have potential evidential utility for forensic applications. However, bioinformatic analysis of high-throughput sequencing data varies widely among laboratories. These differences can potentially affect microbial community composition and downstream analyses. To illustrate the importance of standardizing methodology, we compared analyses of postmortem microbiome samples using several bioinformatic pipelines, varying minimum library size or minimum number of sequences per sample, and sample size. Using the same input sequence data, we found that three open-source bioinformatic pipelines, MG-RAST, mothur, and QIIME2, had significant differences in relative abundance, alpha-diversity, and beta-diversity, despite the same input data. Increasing minimum library size and sample size increased the number of low-abundant and infrequent taxa detected. Our results show that bioinformatic pipeline and parameter choice affect results in important ways. Given the growing potential application of forensic microbiology to the criminal justice system, continued research on standardizing computational methodology will be important for downstream applications.