Event Abstract Back to Event BioScholar: a knowledge engineering system for biology and its application to neural connectivity data Gully Burns1*, Russ Thomas1, Ingulfsen Tommy1 and Hovy Eduard1 1 ISI / USC, Computer Science, United States We provide a demonstration of the BioScholar system, a tool developed to allow scientists to construct small-scale knowledge bases from collections of scientific documents. Given a medium-to-large sized collection of PDF documents (such as that pertaining to the research interests of a large laboratory), BioScholar provides a framework to curate and manage a knowledge base designed to synthesize the contents of these documents into a valuable online resource.The design of the system is based on the semantic separation between observations and interpretations. Data for any particular experiment may be expressed within a framework called 'Knowledge Engineering from Experimental Design' (KE-f-ED) which is based on representing the relationships between independent and dependent variables by modeling the experiment's protocol. The KE-f-ED framework utilizes standardized vocabulary from the Ontology for Biomedical Investigation (OBI). We then use PowerLoom, a first order logic reasoning system, as an inference framework that may be programmed to construct interpretative assertions based on experimental observations of a specific type. Because the KE-f-ED system is tailored specifically to known independent and dependent variables (and their values) for specific experimental types, we use information extraction (IE) techniques to (semi-) automate the process of entering new data into the system.We demonstrate the system's capabilities through a neuroinformatics use-case based on a collection of papers describing tract tracing experiments in the rat. This is a well-studied data set of high value that provides the raw data for our understanding of system's level neural connectivity and has already given rise to neuroinformatics solutions in the past (such as CoCoMac, the Brain Architecture Management System or 'BAMS' and the precursor to this project: NeuroScholar). This demonstration will illustrate the generality of the methodology we propose and provide an example of a working demonstration system.It is anticipated that a neuroscientist could conceivably adapt the tools presented here to accommodate data from other types of experiment. Given that the complexity of neuroscientific knowledge has hindered the development of effective neuroinformatics tools, the system we present here could provide the basis for a general-purpose knowledge engineering toolkit for neuroscientists to develop knowledge bases based on their own collections of scientific documents. Conference: Neuroinformatics 2009, Pilsen, Czechia, 6 Sep - 8 Sep, 2009. Presentation Type: Oral Presentation Topic: Infrastructural and portal services Citation: Burns G, Thomas R, Tommy I and Eduard H (2019). BioScholar: a knowledge engineering system for biology and its application to neural connectivity data. Front. Neuroinform. Conference Abstract: Neuroinformatics 2009. doi: 10.3389/conf.neuro.11.2009.08.076 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 22 May 2009; Published Online: 09 May 2019. * Correspondence: Gully Burns, ISI / USC, Computer Science, Los Angeles, United States, gully@usc.edu Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Gully Burns Russ Thomas Ingulfsen Tommy Hovy Eduard Google Gully Burns Russ Thomas Ingulfsen Tommy Hovy Eduard Google Scholar Gully Burns Russ Thomas Ingulfsen Tommy Hovy Eduard PubMed Gully Burns Russ Thomas Ingulfsen Tommy Hovy Eduard Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.