Services and support for IU School of Medicine and Clinical Affairs Schools by the UITS/PTI Advanced Biomedical Information Technology Core and Research Technologies Division in FY 2013 - Extended Version

The report presents information on services delivered in FY 2013 by ABITC and RT to the IU School of Medicine and the other Clinical Affairs schools that include the Schools of Nursing, Dentistry, Health and Rehabilitation Sciences, and Optometry; the Fairbanks School of Public Health at IUPUI; the School of Public Health at IU Bloomington; and the School of Social Work

Fostering Cross-institutional Collaboration for Open Educational Resources Production

An editable version of this resource is available at http://open.umich.edu/education/med/oernetwork/reports/oer-collab-report/2010.Although there are over a quarter of a million open courses published by an increasing number of universities, it remains unclear whether Open Educational Resources (OER) is scalable and productively sustainable. The challenge is compounded when OER is examined in the light of its potential to allow both educators and learners in developing countries to contribute geographically bound learning resources in the context of varied infrastructural, technological and skill constraints. Between October and December 2009, 52 participants involved in various roles related to Health OER from five universities (one in the USA, two in Ghana and two in South Africa) were interviewed. The aim of the study was to investigate sustainability of OER based on possible cross-institutional collaboration as well as social and technical challenges in creating and sharing OER materials. The analytical framework was adopted from prior research in related areas: distributed scientific collaboration; cyber infrastructure; open source development; and Wikipedia. We adopted a qualitative approach for data collection, which included semi structured interviews and document analysis. The findings were analyzed and reported with many direct quotations included. The outcome of the data analysis is a model for productive, scalable, and sustainable OER based on cross-institutional collaboration. The report concludes with practical recommendations on how to the model can be operationalized.William and Flora Hewlett Foundationhttp://deepblue.lib.umich.edu/bitstream/2027.42/94546/1/2010.12.08_oer_collaboration_report-final_0.pd

Indiana University’s advanced cyberinfrastructure in service of IU strategic goals: Activities of the Research Technologies Division of UITS and National Center for Genome Analysis Support – two Pervasive Technology Institute cyberinfrastructure and service centers - during FY2014

This report presents information on the activities of the Research Technologies Division of UITS and the National Center for Genome Analysis Support, two cyberinfrastructure and service centers of the Pervasive Technology Institute. Research Technologies (RT) is a subunit of University Information Technology Services (UITS) and it operates and supports the largest computational, data, and visualization systems at IU. The National Center for Genome Analysis Support (NCGAS) is primarily federally funded, serving the national community of genome scientists. NCGAS leadership is drawn from the Office of the Vice President for Information Technology, UITS, the College, and the School of Informatics and Computing. This report focuses on contributions of RT and NCGAS to accomplishment of IU’s bicentennial goals, and is organized according to those goals. Together the activities of NCGAS and RT represent a large share of the activities of PTI in support of the IU community. PTI’s Research Centers (Data to Insight Center, Digital Science Center, and the Center for Applies Cybersecurity Research) also provide support to the IU community in various forms but the primary focus of these research centers is informatics, information technology, and computer science research

Equity Of Urban Neighborhood Infrastructure: A Data-Driven Assessment

Neighborhood infrastructure, such as sidewalks, medical facilities, public transit, community gathering places, and tree canopy, provides essential support for safe, healthy, and resilient communities. This thesis proposes, develops, and implements an innovative approach to thoroughly examine the presence and condition of neighborhood infrastructure. It demonstrates the necessity of considering multiple infrastructure types when studying neighborhood infrastructure and its equity. This thesis provides an automated assessment framework as well as case studies among four major metropolitan cities across the United States, which expands the research opportunities for future infrastructure-related research

The relationship between research data management and virtual research environments

The aim of the study was to compile a conceptual model of a Virtual Research Environment (VRE) that indicates the relationship between Research Data Management (RDM) and VREs. The outcome of this study was that VREs are ideal platforms for the management of research data. In the first part of the study, a literature review was conducted by focusing on four themes: VREs and other concepts related to VREs; VRE components and tools; RDM; and the relationship between VREs and RDM. The first theme included a discussion of definitions of concepts, approaches to VREs, their development, aims, characteristics, similarities and differences of concepts, an overview of the e-Research approaches followed in this study, as well as an overview of concepts used in this study. The second theme consisted of an overview of developments of VREs in four countries (United Kingdom, USA, The Netherlands, and Germany), an indication of the differences and similarities of these programmes, and a discussion on the concept of research lifecycles, as well as VRE components. These components were then matched with possible tools, as well as to research lifecycle stages, which led to the development of a first conceptual VRE framework. The third theme included an overview of the definitions of the concepts ‘data’ and ‘research data’, as well as RDM and related concepts, an investigation of international developments with regards to RDM, an overview of the differences and similarities of approaches followed internationally, and a discussion of RDM developments in South Africa. This was followed by a discussion of the concept ‘research data lifecycles’, their various stages, corresponding processes and the roles various stakeholders can play in each stage. The fourth theme consisted of a discussion of the relationship between research lifecycles and research data lifecycles, a discussion on the role of RDM as a component within a VRE, the management of research data by means of a VRE, as well as the presentation of a possible conceptual model for the management of research data by means of a VRE. This literature review was conducted as a background and basis for this study. In the second part of the study, the research methodology was outlined. The chosen methodology entailed a non-empirical part consisting of a literature study, and an empirical part consisting of two case studies from a South African University. The two case studies were specifically chosen because each used different methods in conducting research. The one case study used natural science oriented data and laboratory/experimental methods, and the other, human orientated data and survey instruments. The proposed conceptual model derived from the literature study was assessed through these case studies and feedback received was used to modify and/or enhance the conceptual model. The contribution of this study lies primarily in the presentation of a conceptual VRE model with distinct component layers and generic components, which can be used as technological and collaborative frameworks for the successful management of research data.Thesis (DPhil)--University of Pretoria, 2018.National Research FoundationInformation ScienceDPhilUnrestricte

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science.</p

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research