CREATING A BIOMEDICAL ONTOLOGY INDEXED SEARCH ENGINE TO IMPROVE THE SEMANTIC RELEVANCE OF RETREIVED MEDICAL TEXT

Medical Subject Headings (MeSH) is a controlled vocabulary used by the National Library of Medicine to index medical articles, abstracts, and journals contained within the MEDLINE database. Although MeSH imposes uniformity and consistency in the indexing process, it has been proven that using MeSH indices only result in a small increase in precision over free-text indexing. Moreover, studies have shown that the use of controlled vocabularies in the indexing process is not an effective method to increase semantic relevance in information retrieval. To address the need for semantic relevance, we present an ontology-based information retrieval system for the MEDLINE collection that result in a 37.5% increase in precision when compared to free-text indexing systems. The presented system focuses on the ontology to: provide an alternative to text-representation for medical articles, finding relationships among co-occurring terms in abstracts, and to index terms that appear in text as well as discovered relationships. The presented system is then compared to existing MeSH and Free-Text information retrieval systems. This dissertation provides a proof-of-concept for an online retrieval system capable of providing increased semantic relevance when searching through medical abstracts in MEDLINE

A Core Reference Hierarchical Primitive Ontology for Electronic Medical Records Semantics Interoperability

Currently, electronic medical records (EMR) cannot be exchanged among hospitals, clinics, laboratories, pharmacies, and insurance providers or made available to patients outside of local networks. Hospital, laboratory, pharmacy, and insurance provider legacy databases can share medical data within a respective network and limited data with patients. The lack of interoperability has its roots in the historical development of electronic medical records. Two issues contribute to interoperability failure. The first is that legacy medical record databases and expert systems were designed with semantics that support only internal information exchange. The second is ontological commitment to the semantics of a particular knowledge representation language formalism. This research seeks to address these interoperability failures through demonstration of the capability of a core reference, hierarchical primitive ontological architecture with concept primitive attributes definitions to integrate and resolve non-interoperable semantics among and extend coverage across existing clinical, drug, and hospital ontologies and terminologies

Graph Data-Models and Semantic Web Technologies in Scholarly Digital Editing

This volume is based on the selected papers presented at the Workshop on Scholarly Digital Editions, Graph Data-Models and Semantic Web Technologies, held at the Uni- versity of Lausanne in June 2019. The Workshop was organized by Elena Spadini (University of Lausanne) and Francesca Tomasi (University of Bologna), and spon- sored by the Swiss National Science Foundation through a Scientific Exchange grant, and by the Centre de recherche sur les lettres romandes of the University of Lausanne. The Workshop comprised two full days of vibrant discussions among the invited speakers, the authors of the selected papers, and other participants.1 The acceptance rate following the open call for papers was around 60%. All authors – both selected and invited speakers – were asked to provide a short paper two months before the Workshop. The authors were then paired up, and each pair exchanged papers. Paired authors prepared questions for one another, which were to be addressed during the talks at the Workshop; in this way, conversations started well before the Workshop itself. After the Workshop, the papers underwent a second round of peer-review before inclusion in this volume. This time, the relevance of the papers was not under discus- sion, but reviewers were asked to appraise specific aspects of each contribution, such as its originality or level of innovation, its methodological accuracy and knowledge of the literature, as well as more formal parameters such as completeness, clarity, and coherence. The bibliography of all of the papers is collected in the public Zotero group library GraphSDE20192, which has been used to generate the reference list for each contribution in this volume. The invited speakers came from a wide range of backgrounds (academic, commer- cial, and research institutions) and represented the different actors involved in the remediation of our cultural heritage in the form of graphs and/or in a semantic web en- vironment. Georg Vogeler (University of Graz) and Ronald Haentjens Dekker (Royal Dutch Academy of Sciences, Humanities Cluster) brought the Digital Humanities research perspective; the work of Hans Cools and Roberta Laura Padlina (University of Basel, National Infrastructure for Editions), as well as of Tobias Schweizer and Sepi- deh Alassi (University of Basel, Digital Humanities Lab), focused on infrastructural challenges and the development of conceptual and software frameworks to support re- searchers’ needs; Michele Pasin’s contribution (Digital Science, Springer Nature) was informed by his experiences in both academic research, and in commercial technology companies that provide services for the scientific community. The Workshop featured not only the papers of the selected authors and of the invited speakers, but also moments of discussion between interested participants. In addition to the common Q&A time, during the second day one entire session was allocated to working groups delving into topics that had emerged during the Workshop. Four working groups were created, with four to seven participants each, and each group presented a short report at the end of the session. Four themes were discussed: enhancing TEI from documents to data; ontologies for the Humanities; tools and infrastructures; and textual criticism. All of these themes are represented in this volume. The Workshop would not have been of such high quality without the support of the members of its scientific committee: Gioele Barabucci, Fabio Ciotti, Claire Clivaz, Marion Rivoal, Greta Franzini, Simon Gabay, Daniel Maggetti, Frederike Neuber, Elena Pierazzo, Davide Picca, Michael Piotrowski, Matteo Romanello, Maïeul Rouquette, Elena Spadini, Francesca Tomasi, Aris Xanthos – and, of course, the support of all the colleagues and administrative staff in Lausanne, who helped the Workshop to become a reality. The final versions of these papers underwent a single-blind peer review process. We want to thank the reviewers: Helena Bermudez Sabel, Arianna Ciula, Marilena Daquino, Richard Hadden, Daniel Jeller, Tiziana Mancinelli, Davide Picca, Michael Piotrowski, Patrick Sahle, Raffaele Viglianti, Joris van Zundert, and others who preferred not to be named personally. Your input enhanced the quality of the volume significantly! It is sad news that Hans Cools passed away during the production of the volume. We are proud to document a recent state of his work and will miss him and his ability to implement the vision of a digital scholarly edition based on graph data-models and semantic web technologies. The production of the volume would not have been possible without the thorough copy-editing and proof reading by Lucy Emmerson and the support of the IDE team, in particular Bernhard Assmann, the TeX-master himself. This volume is sponsored by the University of Bologna and by the University of Lausanne. Bologna, Lausanne, Graz, July 2021 Francesca Tomasi, Elena Spadini, Georg Vogele

A Quadruple-Based Text Analysis System for History and Philosophy of Science

abstract: Computational tools in the digital humanities often either work on the macro-scale, enabling researchers to analyze huge amounts of data, or on the micro-scale, supporting scholars in the interpretation and analysis of individual documents. The proposed research system that was developed in the context of this dissertation ("Quadriga System") works to bridge these two extremes by offering tools to support close reading and interpretation of texts, while at the same time providing a means for collaboration and data collection that could lead to analyses based on big datasets. In the field of history of science, researchers usually use unstructured data such as texts or images. To computationally analyze such data, it first has to be transformed into a machine-understandable format. The Quadriga System is based on the idea to represent texts as graphs of contextualized triples (or quadruples). Those graphs (or networks) can then be mathematically analyzed and visualized. This dissertation describes two projects that use the Quadriga System for the analysis and exploration of texts and the creation of social networks. Furthermore, a model for digital humanities education is proposed that brings together students from the humanities and computer science in order to develop user-oriented, innovative tools, methods, and infrastructures.Dissertation/ThesisDoctoral Dissertation Biology 201

Current Understanding, Support Systems, and Technology-led Interventions for Specific Learning Difficulties

In January 2019, the Government Office for Science commissioned a series of 4 rapid evidence reviews to explore how technology and research can help improve educational outcomes for learners with Specific Learning Difficulties (SpLDs). This review examined: 1) current understanding of the causes and identification of SpLDs, 2)the support system for learners with SpLDs, 3)technology-based interventions for SpLDs 4) a case study approach focusing on dyscalculia to explore all 3 theme