Poster for the 2018 International Conference on Knowledge Management. This poster compares and contrasts four different provenance models.

Poster for the 2018 International Conference on Knowledge Management. This poster uses a questionnaire to identify which information sources respondents would use in specific situations and which qualities of those sources were most important to them.

Poster describes a study analyzing the need for and student attitudes towards data literacy and library instruction in earth science students at the University of Chinese Academy Sciences.

Poster for the 2017 International Conference on Knowledge Management. This poster proposes a system of rapid automated assessment of student participation and performance quality in collaborative learning.

Presentation discusses how the topic of data ethics has historically been addressed in LIS research, and takes a close look at the key research themes of privacy, research ethics, ethical ecosystems, and control in the papers found.

Poster shows the results of a study that closely examines the transaction logs of e-journal databases over a one-year period at the University of Engineering and Technology, Lahore.

With advances in natural language processing (NLP), machine learning (ML) and artificial intelligence (AI), there are new opportunities for improving findability among existing public-facing resources. This project seeks to inform findability, especially for multiple chronic condition (MCC) resources, by describing current search capabilities and limitations across several of AHRQ’s publicly available domains and by identifying and piloting a novel NLP/ML approach to make suggested improvements. This work intentionally engages with the overlap of numerous disciplines including information extraction, information retrieval, data and text mining, knowledge management, and best practices in health care. We are looking to apply this work across all domains but will start by focusing on specific AHRQ domains. Given limited API access, we scraped the content of digital.ahrq.gov and the patient centered medical home (PCMH) resources and performed automated search using a set of related terms that align with an MCC scenario: hypertension, osteoarthritis, and chronic kidney disease. We obtained results confirming the limitations of existing search.