Cleaning-up and Marketing OHSU Digital Collections

Cleaning-up and Marketing OHSU Digital Collections focuses on the metadata clean-up and marketing of our new Tind digital collection platform. This lightning talk will highlight the work we did in OpenRefine to be able to have newly cleaned records to show people, increasing deposits. We will also share our communication plan which focuses on the following audiences: general students, faculty/program directors, researchers/research mission/, clinicians, and postdocs. Continuing conversations started at the earlier phase of implementation is essential to a successful marketing plan

Undertaking a Digital Collection Platform Evaluation at a Health Sciences Library

This presentation will discuss the process of completing a comprehensive digital collection platform evaluation at Oregon Health & Science University (OHSU). Guided by its mission to advance the effective, efficient and ethical use of information in support of education, research and healthcare, the OHSU Library serves institutional faculty, staff and students, as well as external health science professionals and researchers, and residents of the State of Oregon and surrounding areas. Our unique physical and virtual collections include over 8 TB of digital files, which document the institution’s history, research and scholarly output.; learning from primary source materials is facilitated by these holdings. In 2017, the Library elected to migrate to the Samvera digital collection platform seemingly without a full evaluation process leading to unforeseen difficulties in the following years. This presentation will describe key challenges, such as a lack of metrics, that have caused us to evaluate other platforms. Our approach for evaluating platforms will be described, as well as how our role as a health sciences library catering to groups that include marketing departments, historical researchers, and data scientists, shapes our platform needs

Is authorship sufficient for today’s collaborative research? A call for contributor roles

Assigning authorship and recognizing contributions to scholarly works is challenging on many levels. Here we discuss ethical, social, and technical challenges to the concept of authorship that may impede the recognition of contributions to a scholarly work. Recent work in the field of authorship shows that shifting to a more inclusive contributorship approach may address these challenges. Recent efforts to enable better recognition of contributions to scholarship include the development of the Contributor Role Ontology (CRO), which extends the CRediT taxonomy and can be used in information systems for structuring contributions. We also introduce the Contributor Attribution Model (CAM), which provides a simple data model that relates the contributor to research objects via the role that they played, as well as the provenance of the information. Finally, requirements for the adoption of a contributorship-based approach are discussed

VIVO: a system for research discovery

In this paper the software VIVO is described. VIVO is a member-supported, enterprise open source software and an ontology for representing scholarship

Is Authorship Sufficient for Today’s Collaborative Research? A Call for Contributor Roles

Assigning authorship and recognizing contributions to scholarly works is challenging on many levels. Here we discuss ethical, social, and technical challenges to the concept of authorship that may impede the recognition of contributions to a scholarly work. Recent work in the field of authorship shows that shifting to a more inclusive contributorship approach may address these challenges. Recent efforts to enable better recognition of contributions to scholarship include the development of the Contributor Role Ontology (CRO), which extends the CRediT taxonomy and can be used in information systems for structuring contributions. We also introduce the Contributor Attribution Model (CAM), which provides a simple data model that relates the contributor to research objects via the role that they played, as well as the provenance of the information. Finally, requirements for the adoption of a contributorship-based approach are discussed

Better BioData with Ontologies and Linked Data

Have you ever wondered…What an ontology is and why anyone would use one? Who’s using ontologies, and how are they using them? How ontologies are created and maintained? How to use an ontology to make your research data more reusable? Come to the next BioData Club to find out! After a brief introduction to the subject, we’ll walk through a modified version of the OBO Tutorial to get first-hand experience using biomedical ontologies to mark-up research data for improved reuse. No previous experience with ontologies or linked data is required. Bring a laptop and your curiosity

Linked Data for Local Search: Helping patients find their way around a geographically complex academic health center

<p>Oregon Health and Science University’s (OHSU) main and expansion campuses are respectively situated at the top and eastern base of Portland's Marquam Hill, a beautiful but geographically challenging location that can present significant obstacles for patients finding their way to appointments with OHSU healthcare providers. These wayfinding challenges are exacerbated by a lack of search engine exposure to detailed structured data describing the university’s campuses, buildings, clinics, satellite locations, and providers, which also hampers the ability of both current and future patients to find information about seeking healthcare services at the university in general. OHSU commits significant resources to assisting patients find their way around once they arrive at a campus, including parking valets and information concierges, but until recently there had not been a focus on the quality and accuracy of information about OHSU entities found on the web. In 2016, OHSU launched the Project to Inform Local Search, also known as PILS, a collaborative effort between the university’s Digital Engagement and Digital Strategy teams and the OHSU Library to implement a semantic data model that would allow the university to canonically describe all of its campuses, buildings, locations, clinics, and providers in order to provide accurate and trustworthy structured data about these entities to search engines, map providers, healthcare review sites, and other consumers of structured and linked data on the web. The ultimate goal of the project is to enhance patient experience around seeking information on the web about the university’s healthcare services, with a particular focus on the structured data that would assist patients in getting to appointments. This presentation will describe some of the specific local search issues OHSU set out to resolve, the background research conducted to develop competency questions to inform the creation of the model, the implementation of the semantic model, the data integration approach, the project deliverables, and potential future expansions and applications of the model. The PILS collaborators hope our work might inspire similar efforts at other academic health centers</p

Start Somewhere: Programming Fundamentals in Python

In this BioData Club workshop, attendees will gain skills and an understanding of key concepts foundational to computer programming. Instructors Eric Earl and Marijane White will teach with Python, a popular and friendly programming language. Topics covered will include: variables, data types, looping, and conditionals. There will also be time for open questions. Join us if you’ve never programmed before, but want to get started, or if you’re new to programming and want a refresh on the fundamentals and to experiment with Python

Data Rigor and Reproducibility

Course materials for OHSU PMBC PERT Data Rigor &amp; Reproducibility nanocourse, Spring 201