A study of the personal and social characteristics of public offenders from three Massachusetts correctional institutions in treatment with the division of legal medicine

Thesis (M.S.)--Boston Universit

Testing Our Assumptions: Preliminary Results from the Data Curation Network

Objective: Data curation is becoming widely accepted as a necessary component of data sharing. Yet, as there are so many different types of data with various curation needs, the Data Curation Network (DCN) project anticipated that a collaborative approach to data curation across a network of repositories would expand what any single institution might offer alone. Now, halfway through a three-year implementation phase, we’re testing our assumptions using one year of data from the DCN. Methods: Ten institutions participated in the implementation phase of a shared staffing model for curating research data. Starting on January 1, 2019, for 12 months we tracked the number, file types, and disciplines represented in data sets submitted to the DCN. Participating curators were matched to data sets based on their self-reported curation expertise. Aspects such as curation time, level of satisfaction with the assignment, and lack of appropriate expertise in the network were tracked and analyzed. Results: Seventy-four data sets were submitted to the DCN in year one. Seventy-one of them were successfully curated by DCN curators. Each curation assignment takes 2.4 hours on average, and data sets take a median of three days to pass through the network. By analyzing the domain and file types of first- year submissions, we find that our coverage is well represented across domains and that our capacity is higher than the demand, but we also observed that the higher volume of data containing software code relied on certain curator expertise more often than others, creating potential unbalance. Conclusions: The data from year one of the DCN pilot have verified key assumptions about our collaborative approach to data curation, and these results have raised additional questions about capacity, equitable use of network resources, and sustained growth that we hope to answer by the end of this implementation phase

Online Sales Tax Policy: A Study of New York and Georgia State Laws and the Federal Marketplace Fairness Act

The physical presence standard for remote sales tax collection, established in 1967, remains the standard for sales tax collection today. Advances in technology have led to increases in online shopping. Online retailers act under the physical presence standard. Throughout the United States, many individual states are facing economic challenges either as a result of or in conjunction with states’ inability to collect sales tax from some online vendors without a physical presence in the state. The challenges include loss of revenue due to uncollected online sales tax and lack of fairness for brick-and-mortar retailers that do remit sales tax to the state and for less affluent citizens unable to shop online. In order to combat these challenges, some states are redefining and expanding the meaning of physical presence in what are known as state “Amazon laws.” New York and Georgia took this approach. At the federal level, the U.S. Senate’s 2013 Marketplace Fairness Act attempted to enable states to collect online sales tax through origin sourcing, which does not redefine the physical presence standard. The U.S. House Judiciary Committee is currently working on alternatives to the Marketplace Fairness Act that accomplish the same goal of allowing states to collect remote sales tax without expanding the physical presence standard. In this study, I chose to examine the Marketplace Fairness Act and New York and Georgia’s state “Amazon laws” in order to make a policy recommendation for Mississippi. I argue that Mississippi should implement a state online sales tax policy similar to New York and Georgia, while continuing to push for federal legislation like the Marketplace Fairness Act

Environmental metabolomics : databases and tools for data analysis

© The Author(s), 2015. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Marine Chemistry 177 (2015): 366–373, doi:10.1016/j.marchem.2015.06.012.Metabolomics is the study of small molecules, or ‘metabolites’, that are the end products of biological processes. While -omics technologies such as genomics, transcriptomics, and proteomics measure the metabolic potential of organisms, metabolomics provides detailed information on the organic compounds produced during metabolism and found within cells and in the environment. Improvements in analytical techniques have expanded our understanding of metabolomics and developments in computational tools have made metabolomics data accessible to a broad segment of the scientific community. Yet, metabolomics methods have only been applied to a limited number of projects in the marine environment. Here, we review analysis techniques for mass spectrometry data and summarize the current state of metabolomics databases. We then describe a boutique database developed in our laboratory for efficient data analysis and selection of mass spectral targets for metabolite identification. The code to implement the database is freely available on GitHub (https://github.com/joefutrelle/domdb). Data organization and analysis are critical, but often under-appreciated, components of metabolomics research. Future advances in environmental metabolomics will take advantage of continued development of new tools that facilitate analysis of large metabolomics datasets.The field data populating the database comes from scientific cruises funded by grants from the National Science Foundation to EBK and KL (Atlantic Ocean, OCE-1154320) and E.V. Armbrust (Pacific Ocean, OCE-1205233). The laboratory experiment with coastal seawater was funded by a grant from the Gulf of Mexico Research Initiative to EBK and H.K. White. The laboratory experiments with microbial isolates and the database development are funded by the Gordon and Betty Moore Foundation through Grant GBMF3304 to EBK

Towards Linked Data for Oceanographic Science: The R2R Eventlogger Project, Controlled Vocabularies, and Ontologies at The MBLWHOI Library

Objective: Research vessels coordinated by the United States University-National Oceanographic Laboratory System (US-UNOLS) collect data which are considered important oceanographic science research products. The NSF-funded Rolling Deck to Repository (R2R) project aims to improve access to these data and diminish barriers to their use. One aspect of the R2R project has been to develop a shipboard scientific event logging system, Eventlogger, which incorporates best practice guidelines, controlled vocabularies, a cruise metadata schema, and a scientific event log. Eventlogger facilitates the eventual ingestion of datasets into oceanographic data repositories for subsequent integration and synthesis by investigators. The careful use of controlled vocabularies and ontologies is an important feature of this system, as the use of internationally-informed, consensus-driven controlled vocabularies will make data sets more interoperable, discoverable and reusable. Methods: The R2R Eventlogger project is led by Woods Hole Oceanographic Institution (WHOI), and the management of the controlled vocabularies is led by the Data Librarian in the Marine Biological Laboratory/Woods Hole Oceanographic Institution (MBLWHOI) Library. The first target vocabulary has been one for oceanographic instruments. Management of this vocabulary has thus far consisted of reconciling project vocabulary terms with the more widely used community vocabularies served by the NERC Vocabulary Server v2.0 (NVS2.0): terms included in the SeaDataNet Device Catalogue (L22) and the SeaDataNet Device Category vocabularies (L05). Rather than adopt existing community terms, it is more often the case that local terms are mapped by the Data Managers in the NSF-funded Biological and Chemical Oceanographic Data Management Office (BCO-DMO) to community terms, which preserves any important information and meaning investigators impart through the process of assigning these local terms, and has less impact on researchers. New terms, those that cannot be mapped to the existing community vocabularies (often custom, or modified instruments), are submitted for review to the SeaVOX governance process for addition to the community vocabularies. These vocabularies and their mappings are an important part of the aforementioned Eventlogger system. Before a research cruise, investigators configure the instruments they intend to use for their science activities. The instruments available for selection are provided by the MBLWHOI Data Librarian, who curates UNOLS ship-specific lists of standard shipboard instruments using terms for instruments from the R2R Eventlogger Project Vocabulary. Nonstandard shipboard instruments a researcher or investigator wishes to use can also be added, and these instrument terms will eventually be inducted into the R2R Eventlogger Project Vocabulary. Results: Eventlogger is currently being tested across the UNOLS fleet. A large submission of suggested instrument terms to the SeaDataNet community listserv is currently in progress. New tools for facilitating the management, mapping, and use of these controlled vocabularies are being developed, and new projects with eager partners are envisioned. Ideas for future controlled vocabularies for the ocean science community include: Cruise IDs, Persons, and Ships. Conclusions: The promotion and use of controlled vocabularies and ontologies will pave the way for linked data in oceanographic science. By mapping local terms to authoritative and community-accepted terms, links are created whereby related data sets can be better discovered, and utilized. Librarians have an established history of working with controlled vocabularies and metadata. Libraries, have and will continue to, serve as centers for information discovery as well as a natural home for the management of standards

Rural Implications of Geographic Rating of Health Insurance Premiums

This brief examines how and to what extent states allow health plans to vary premiums by geographic rating area and, using insurance data from selected states, assesses the direction and magnitude of variations in rural and urban geographic rating factors. The authors conclude with a discussion of strategies that federal and state policymakers might use to help ensure that premium variations based on geography are justified. KEY POINTS: There is no clear pattern of geographic rating factors favoring rural or urban areas. This lack of a clear pattern suggests that health plans may use geographic rating for business purposes other than adjusting for underlying cost/price differences. Geographic rating could reduce insurance risk pooling and be used as a proxy for experience rating. To limit the effect of market segmentation resulting from geographic rating, rate bands could be imposed on area rating factors