@conference {344, title = {W14-02: Systematizing Definitions in Ontologies}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, address = {Corvallis, Oregon, USA}, abstract = {
In this talk, I will present a methodological proposal to systematize textual and logical definitions in ontologies. I will use as a case study definitions of social entities from the Ontology of Medically Related Social Entities (OMRSE). The goal is to show how this method can simplify and accelerate the definition writing process.
}, keywords = {definition templates, definitions, logical definitions, ontologies, textual definitions}, url = {http://icbo.cgrb.oregonstate.edu/}, author = {Sepp{\"a}l{\"a}, Selja} } @conference {343, title = {W14-01: Uncovering Definition Coverage in the OBO Foundry Ontologies}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, address = {Corvallis, Oregon, USA}, abstract = {Definitions, both logical and textual, are an essential part of ontologies. Textual definitions help human users disambiguate and regularize their understanding and use of ontology terms to achieve intra- and inter-personal consistency and avoid errors, for example, when annotating scientific data, integrating databases with an ontology, or importing terms into other ontologies. Logical definitions are needed, among other things, for checking the consistency of the ontology and carrying out inferences, for example, over data that has been annotated with ontology terms. Despite the best efforts of ontology developers, it is not uncommon to see missing definitions. While the OBO Foundry explicitly states that its member ontologies should have a substantial fraction of their terms defined, these ontologies still often lack one or both kinds of definitions. Statistics on definition coverage in the OBO Foundry ontologies are scarce and it is difficult to tell what effectively constitutes a substantial fraction of terms in an ontology. In the present work, we examine the coverage of textual and logical definitions throughout the OBO Foundry ontologies in order to uncover the big picture and to give more detailed insight into logical definitions in these ontologies. We have found that textual definition coverage is reasonably good over the OBO Foundry ontologies (66\%), but that the core ontologies exhibit a higher definition coverage (86\%) than the non-core ones (64\%). Logical definitions follow a similar trend, but with lower values {\textemdash} overall, the OBO Foundry has a 30\% coverage, while core ontologies are better covered (53\%) than non-core ones (28\%).
}, keywords = {definition coverage, logical definitions, OBO Foundry, ontology, textual definitions}, url = {http://ceur-ws.org/Vol-1747/IP16_ICBO2016.pdf}, author = {Schlegel, Daniel R. and Selja Sepp{\"a}l{\"a} and Elkin, Peter L.} } @conference {364, title = {W12-06: Evolution of Floral Form: The potential of ontologies across diverse plant lineages}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {TBA
}, keywords = {evo-devo, flower development, fusion, morphological evolution, petaloidy, Zingiberales}, author = {Chelsea Specht} } @conference {W14-03, title = {W12-04: The Plant Phenology Ontology for Phenological Data Integration}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {Plant phenology the timing of life-cycle events, such as flowering or leafing-out has cascading effects on multiple levels of biological organization, from individuals to ecosystems. Despite the importance of understanding phenology for managing biodiversity and ecosystem services, we are not currently able to address continent-scale phenological responses to anticipated climatic changes. This is not because we lack relevant data. Rather, the problem is that the disparate organizations producing large-scale phenology data are using non-standardized terminologies and metrics during data collection and data processing. Here, we preview the Plant Phenology Ontology, which will provide the standardized vocabulary necessary for annotation of phenological data. We are aggregating, annotating, and analyzing the most significant phenological data sets in the USA and Europe for broad temporal, geographic, and taxonomic analyses of how phenology is changing in relation to climate change.
}, url = {http://icbo2016.cgrb.oregonstate.edu/sites/default/files/W14-03_ICBO2016.pdf}, author = {Brian J. Stucky and John Deck and Ellen Denny and Robert P. Guralnick and Ramona L. Walls and Jennifer Yost} } @conference {W14-02, title = {W12-03: The Biological Collections Ontology for linking traditional and contemporary biodiversity data}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {Biodiversity data comes from many sources, ranging from museum specimens to field surveys to genomic sequences. Domain specific standards provide vocabularies for many types of these data, but they do not fully support integrating data across methods, scales, and domains. The Biological Collections Ontology (BCO) was designed to bridge the terminology gap between traditional museum-based specimen collections and more contemporary environmental sampling methods, such as metagenomic sequencing, by providing a logically defined set of terms for biodiversity that map to standards such as the Darwin Core and Minimum Information for any Sequence. The BCO is expanding to encompass observational biodiversity data such as field surveys and taxonomic inventories. A key design principle of the BCO is to clearly distinguish the different types of processes involved in biodiversity data collection along with the inputs and outputs of those processes. The BCO has applications to plant biodiversity studies for linking herbarium specimens to sequence data, connecting trait data to specimens, and describing survey data.
}, url = {http://icbo.cgrb.oregonstate.edu/}, author = {Ramona Walls and Rob Guralnick} } @conference {363, title = {W12-02: TraitBank: semantic integration of biodiversity data from diverse sources}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {Easy access to large amounts of biodiversity data has the potential to transform research across the life sciences. However, most of the data generated so far are not easily integrated or repurposed due to a lack of standardization in how scientists talk about the characteristics of organisms, how they describe the context of their observations, and how they document the methods with which the data were collected. TraitBank (eol.org/traitbank) addresses this impediment by linking information aggregated from diverse sources to community-developed ontologies and controlled vocabularies. These post hoc annotations help to organize distributed, heterogeneous knowledge into a lightweight, scalable semantic framework supporting retrieval and reuse for a variety of applications, ranging from large-scale synthetic analyses of biodiversity to linked data products and hands-on data science in the classroom. The TraitBank data store currently holds over 11 million measurements and facts for more than 1.7 million taxa including animals, plants, fungi, and microbes. These data are mobilized from major biodiversity information systems (e.g., International Union for Conservation of Nature, Ocean Biogeographic Information System, Paleobiology Database), open literature repositories (e.g., Dryad, Ecological Archives, Pangaea), label data from natural history collections, and legacy/unpublished data sets. TraitBank subject coverage \ is very broad ranging from distribution, ecology, and life history to morphology and physiology. Data can be downloaded via CSV files or a JSON-LD service. Reuse and redistribution with attribution to the original data sources is encouraged. TraitBank complements taxon or subject-specific knowledge management systems by filling gaps (both in taxonomic and trait space), by recruiting new types of data (e.g., from text-mining, citizen-science, and specimen data digitization efforts) and by integrating knowledge across the entire tree of life and multiple scientific domains. The emerging semantic framework will facilitate data discovery, support queries across data sets, and advance data integration and exchange among projects, thus making more biodiversity data available for use in scientific and policy-oriented applications.
}, author = {Katja Schulz and Jennifer Hammock} } @conference {362, title = {W12-01: Some Challenges in Working with Biodiversity Ontologies}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, address = {Corvallis, OR}, abstract = {We have faced a number of ontology-related challenges in developing our botanical knowledge portal, which uses Semantic Mediawiki (SMW) to store and display structured data extracted from the Flora of North America (FNA), and to integrate this data with an open biodiversity knowledge graph. We will describe some of the challenges that we have overcome, and some that we continue to struggle with. These include issues with representing and integrating data about phenotypes, habitats, phenology, and establishment means (native vs. introduced). We will also describe the structure of our biodiversity knowledge graph, and invite collaboration in its continued construction.
}, author = {Joel Sachs and Hong Cui and James Macklin} } @conference {W11-07, title = {W11-07: IC3-Foods: An infrastructure for the next generation internet of food systems, food, and health.}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {IC3-FOODS, The International Conference/Consortium/Center for Food Ontology, Operability, Data and Semantics, is a new effort at UC Davis, assembling ontological and semantic infrastructure components for next generation internet of food and health. It consists of 3 specific efforts: i) The International Conference for FOODS assembles stakeholders desiring to integrate data and informatics systems currently residing along the Environment<=>Ag<=>Food<=>Diet<=>Health knowledge spectrum, into the: ii) International Consortium of FOODS, which maintains membership of representative stakeholders from academia, industry and (non-)governmental organizations to guide research priorities and development trajectories carried out by: iii) The International Center for FOODS, whose mission consists of hosting the IConference--FOODS, administering the I-Consortium-FOODS, and designing, assembling, and coordinating ontological and infrastructure underpinnings for the emerging semantic web of ag, food, diet, and health.}, url = {http://icbo.cgrb.oregonstate.edu/}, author = {Matthew Lange} } @conference {W11-06, title = {W11-06: FoodON Use cases: Caution! Food Allergies Ahead}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {Millions of people worldwide live with food allergies, including all those at risk for life-threatening anaphylaxis. The lack of a standardized food vocabulary impacts food source risk assessment, food hazard control, consistent food allergy policy implementation and food-allergy research. The Canadian Healthy Infant Longitudinal Study (CHILD) examines causal factors of asthma and allergy during childhood development. The development of FoodON will benefit food allergy research by standardizing food descriptors across child cohorts, enable the correlation of food antigens with biological causation of immune response, and streamline guidelines for parents.}, url = {http://icbo.cgrb.oregonstate.edu/}, author = {Emma Griffiths} } @conference {W11-05, title = {W11-05: Food safety and infectious disease}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {Globalization of food manufacturing, distribution and consumption require food microbiology testing programs to perform high-throughput pathogen diagnostics within a short time frame. Whole-genome sequencing (WGS) can now assemble and type bacterial genomes in near real-time with improved resolution, making WGS a viable diagnostic tool during foodborne illness outbreak investigations. However, genomic data must be combined with epidemiological, clinical, laboratory and other health care data (contextual data) to be meaningfully interpreted for actionable interventions. Canada{\textquoteright}s Integrated Rapid Infectious Disease Analysis (IRIDA) project includes the development of a Genomic Epidemiology Application Ontology (GenEpiO), with the development of standardized food vocabulary as a priority area. Standardized food descriptors are essential for data sharing between public health agencies and health responders, accreditation and reproducibility of WGS pipelines, source attribution and risk assessment.}, url = {http://icbo.cgrb.oregonstate.edu/}, author = {William Hsiao} } @conference {W11-04, title = {W11-04: Food composition: Understanding what gives food its colour, taste and aroma}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {Data on the composition of foods are essential for a diversity of purposes. It provides detailed sets of information on the nutritionally important components such as proteins, carbohydrates, vitamins and minerals. In this talk, we will describe our approach to employ ontologies to identify food components in recipes described in natural language. By combining several public data sources, we link the food components to chemical compounds and their physiological and pathological effects.}, url = {http://icbo.cgrb.oregonstate.edu/}, author = {Miguel Garcia} } @conference {W11-03, title = {W11-03: Sustainable food systems and food in ecosystems}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {This brief talk will outline the need for a global food ontology to flexibly represent food across human and natural ecosystems. From an anthropocentric point of view, the sustainability and resilience of the global food system - including the sustainability of ecosystems and human-made networks which support it - should be closely interlinked with entities which realise food roles and the global policy objectives to secure food supply for all. From a more "natural" point of view, a truly global food ontology should be flexible enough to link taxa (including humans) to their consumers via the simultaneous realisation of prey, detrital, and food roles. This feature would provide a semantic basis to model food webs and, in combination with compositional inventories, nutritional profiles for ecoinformatics. These anthropogenic and natural perspectives will inevitably converge as a biospheric representation of trophic patterns emerges, a process which a flexible food ontology can greatly accelerate. Vitally, these aims will require coordination across multiple established and emerging ontologies to be feasible in the long term and a number of potential synergies with the Environment Ontology, the Agronomy Ontology, and the Sustainable Development Goal Interface Ontology will be proposed.}, url = {http://icbo.cgrb.oregonstate.edu/}, author = {Pier Luigi Buttigieg} } @conference {W11-02, title = {W11-02: International Efforts in Creating Food Vocabularies}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {A standardised system for classifying and describing food makes it easier to compare data from different sources and perform more detailed types of data analyses. As such, there have been many agency-specific, project-specific and international efforts to create food vocabularies fit for different purposes. Here we describe the different existing and ongoing efforts.}, url = {http://icbo.cgrb.oregonstate.edu/}, author = {Robert Hoehndorf and Matthew Lange} } @conference {W11-01, title = {W11-01: Why we Need Food Ontology}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {The need to represent knowledge about food is central to many fields such as health, food safety, nutrition, food allergy, sustainable development, trade, ecosystems etc. Academic, national, provincial and departmental databases are all silos of food terminology and data models. Several resources and standards exist for indexing food descriptors however their content and architecture are not semantically and logically coherent. Here we present a unified approach to developing a Farm-to-Fork food ontology which will facilitate data sharing and interoperability between different health, regulatory, development and research communities worldwide.}, url = {http://icbo.cgrb.oregonstate.edu/}, author = {Damion Dooley} } @conference {W05-07, title = {W05-07: Ontology-based literature mining of E. coli vaccine-associated gene interaction networks}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {Pathogenic Escherichia coli infections cause various diseases in humans and many animal species. While extensive E. coli vaccine research has been conducted, we are still unable to fully protect ourselves against E. coli infections. In this study, we first extended the Vaccine Ontology (VO) to semantically represent various E. coli vaccines and genes used in the vaccine development. We also normalized E. coli gene names compiled from the annotations of various E. coli strains. The Interaction Network Ontology (INO) includes various interaction-related keywords useful for literature mining. Using VO, INO, and normalized E. coli gene names, we applied an ontology- based SciMiner literature mining strategy to mine all PubMed abstracts and retrieve E. coli vaccine-associated gene interactions. Using vaccine-related abstracts, our study identified 11,350 sentences that contain 88 unique INO interaction types and at least two out of 1,781 unique E. coli genes. From this big network, a sub-network that contains 5 E. coli vaccine genes, 62 other E. coli genes, and 25 INO interaction types were also identified. A centrality analysis of these gene interaction networks identified top ranked E. coli genes and INO interaction types. Our INO hierarchical classification also provided an effective way to identify and study the relations and patterns among the 25 interaction types.}, url = {http://icbo.cgrb.oregonstate.edu/}, author = {Junguk Hur and Arzucan Ozgur and Edison Ong and Yongqun He} } @conference {W05-06, title = {W05-06: Hierarchical Sentiment Analysis on HPV Vaccines Related Tweets Using Machine Learning Based Approaches}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {In order to figure out the reasons behind the low HPV vaccine coverage and come up with corresponding strategies to improve vaccine uptake, understand public opinions on HPV vaccines would be of great help. As a precious and rich data source to analyze public opinions, Twitter is now attracting more attention from medical informatics researchers. In order to use machine learning based methods to automatically track and analyze rapidly-growing HPV vaccine related public opinions on Twitter, we first collected and manually annotated 6,000 related tweets as a gold standard. In order to model the possible sentiments especially the negative sentiments over HPV vaccine on Twitter, a preliminary ontology for hierarchical sentiment classification was built as the annotation scheme. A Kappa annotation agreement at 0.851 was reached. Different features (word n-grams, POS and word clusters) were extracted. Experiments were conducted to test the performance of the different combinations features sets on different levels of classification tasks. Macro F scores at 0.8043 and 0.7552 were reached for top-level classification and finest level classification respectively. The limitations and challenges were also discussed. Our results and analysis indicate that it is feasible to do hierarchical classification tasks on HPV vaccine related tweets using machine learning approaches.}, url = {http://icbo.cgrb.oregonstate.edu/}, author = {Jingcheng Du and Jun Xu and Hsingyi Song and Xiangyu Liu and Cui Tao} } @conference {W05-05, title = {W05-05: Co-occurrence Analysis of Adverse Events for Typhoid Fever Vaccines}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {Salmonella enterica serotype Typhi is considered as one of the high-priority potential bioterrorism agents by the Center for Disease Control and Prevention (CDC). Vaccines against Typhi can help with the prophylaxis against typhoid fever. However, little effort has been conducted for post-market safety monitoring of typhoid fever vaccines. In this paper, we proposed a novel network-based computational approach to investigate the co-occurrence relationships among adverse events reported after typhoid fever vaccine (TYP). We focused on association data that were recorded in the Vaccine Adverse Event Reporting System (VAERS) between 1990 and 2014. First, we extracted and summarized adverse event (AE) information from TYP related reports in the VAERS database using Resource Description Framework (RDF). Then, we applied a series of network approaches to the AE co-occurrence network to identify potential associations among these AEs. Specifically, we (1) constructed an AE co-occurrence network after the typhoid fever vaccines; (2) calculated network properties of AE co-occurrence network; (3) identified condensed subnetworks in AE co-occurrence network; and (4) compared MedDRA terms associated with AEs in each subnetwork. We observed that (1) AE co-occurrence network shares the same scale-free network property as other biological networks and social networks; (2) AEs clustered in one subnetwork are usually enriched in certain MedDRA terms.}, url = {http://icbo.cgrb.oregonstate.edu/}, author = {Yuji Zhang and Jingcheng Du and Cui Tao} } @conference {W05-04, title = {W05-04: LAERTES: An open scalable architecture for linking pharmacovigilance evidence sources with clinical data}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {Integrating multiple sources of pharmacovigilance evidence has the potential to advance the science of safety signal detection and evaluation. Consistent with these results, there has been a recent call for more research on how to integrate multiple disparate evidence sources while making the evidence computable from a knowledge representation perspective (i.e., semantic enrichment). Existing frameworks integrating various sources provide some of the input needed for combinatorial signal detection. However, none have been specifically designed to support both regulatory and clinical use cases, nor developed using an open architecture allowing interested scientists to easily add new sources. This paper discusses the architecture and functionality of a system called Large-scale Adverse Effects Related to Treatment Evidence Standardization (LAERTES). LAERTES provides an open and scalable architecture for linking evidence sources relevant to investigating the association of drugs with health outcomes of interest (HOIs). Standard terminologies/ontologies are used to represent different entities. For example, drugs and HOIs are represented respectively using RxNorm and SNOMED-CT. At the time of this writing, six evidence sources have been loaded into LAERTES. Also, a prototype evidence exploration user interface and set of Web API services are available. This system operates within a larger software environment provided by the OHDSI clinical research framework.}, url = {http://icbo.cgrb.oregonstate.edu/}, author = {Richard D. Boyce and Erica A. Voss and Vojtech Huser and Lee Evans and Christian Reich and Jon D. Duke and Nicholas P. Tatonetti and Michel Dumontier and Manfred Hauben and Magnus Wallberg and Lili Peng and Sara Dempster and Yongqun He and Anthony G. Sena and Patrick B. Ryan} } @conference {W05-03, title = {W05-03: Modulated Evaluation Metrics for Drug-Based Ontologies}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {Our review of randomly selected biomedical ontologies from the National Center for Biomedical Ontology Bioportal showed that majority of the ontologies hosted did not have any documented evidence of formal ontology evaluation. The review points to the need to address this gap, if the ontology research community were to continually produce and maintain high-quality datasets for a wide-range of applications and research endeavors. As a result, this research presents a method to accurately evaluate specific domain ontologies using a semiotic framework that is delineated by the following parts {\textendash} syntactic, semantic, pragmatic, and social. Thusly, we propose the following, 1) whether a semiotic-based approach for ontology evaluation can provide meaningful assessment for biomedical ontologies and 2) if this approach can provide a more accurate assessment of the overall quality of an ontology. We applied this evaluation framework on drug-based ontologies and tailored the metric suite based on features of the drug ontologies. The results of our effort produced a customized metric for drug based ontologies, and also revelations specific to drug ontologies that may offer prescriptions for improvement {\textendash} better selection, consistency, and expressiveness of terms and labels. While ontology evaluation may be a neglected sub-field in ontology research, this study can offer a feasible direction for further research for biomedical ontologies.}, url = {http://icbo.cgrb.oregonstate.edu/}, author = {Muhammad Amith and Cui Tao} } @conference {W05-02, title = {W05-02: Therapeutic Indications and Other Use-case-driven Updates in the Drug Ontology}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {The Drug Ontology (DrOn) is a an OWL2-based representation of drug products and their ingredients, mechanisms of action, strengths, and dose forms, as well as of packaged drug products as represented by United States National Drug Codes (NDCs) [1-3]. The primary goal of DrOn is to support analyses of large, drug-related datasets such as pharmacy claims and EHR data.}, url = {http://icbo.cgrb.oregonstate.edu/}, author = {William R. Hogan and Josh Hanna and Amanda Hicks and Samira Amirova and Baxter Bramblett and Matthew Diller and Rodel Enderez and Timothy Modzelewski and Mirela Vasconcelos and Chris Delcher} } @conference {W05-01, title = {W05-01: On Prescribing Drug Prescriptions}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {n/a}, url = {http://icbo.cgrb.oregonstate.edu/}, author = {Ryeyan Taseen and Jean-Francois Ethier and Adrien Barton} } @conference {W04-05, title = {W04-05: OntONeo: The Obstetric and Neonatal Ontology}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {OntONeo is an ontology for the obstetric and neonatal domain, which has been created to provide a consensus representation of salient electronic health record (EHR) data and in order to serve interoperability of the associated data and information systems. Regardless of medical specialty, in general, every EHR deal with data about the entities involved in a health care appointment. We observed the existence at least three actors: health care facility, the physician, and the patient. Besides dealing with the social entities that participating in a health care appointment, we must also deal with the characteristics that define them and the events that are involved. Here, we demonstrate the utility of ontologies of social entities in the obstetric and neonatal domain. We present how OntONeo is dealing with the material entities who perform or participates in a health care encounter. The definition of these actors plus their related characteristics and events will also contribute to turning on the interoperability of information among EHR from different specialties. OntONeo is being developed with an approach based on ontological realism and the principles of OBO Foundry, including reuse of reference ontologies. Among our reusable ontologies, we can mention for instance the OMRSE, d-acts, PATO and OBI.
}, url = {http://ceur-ws.org/Vol-1747/IT403_ICBO2016.pdf}, author = {F. Farinelli and M.B. Almeida} } @conference {W04-04, title = {W04-04: Who{\textquoteright}s paying and who{\textquoteright}s graying? The organizations and roles associated with insurance policies, funding agencies, and national census data}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {Many social roles are necessarily related to organizations. Employee roles and primary insured roles are just a few examples. However, the relations between such roles and organizations have yet to be systematically worked out in the context of BFO-based ontologies. As an initial step toward developing such a systematic representation, we present use-case driven representations connecting roles to organizations in the context of insurance policies, scientific grants, and U.S. National Census data in OWL/RDF.}, url = {http://icbo.cgrb.oregonstate.edu/}, author = {A. Hicks and W.R. Hogan} } @conference {W04-03, title = {W04-03: An ontological study of healthcare corporations and their social entities}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {Healthcare corporations have a primary goal to provide high-quality health care to those who seek its assistance. The quality and safety of care provided by a healthcare corporation depends on many factors involving both medical and business decisions. One crucial factor in healthcare corporations function is the information management mainly performed through information systems, which process information for both clinical decision making and for fulfilling internal and external legal obligations. In this lecture, we propose a sketch of an ontology-based model for healthcare corporations with the aim of facilitating the coordination of the information systems involved in either medical or management activities. In order to accomplish this, we focus on three efforts: i) to shed some light on the ontological status of corporations; ii) to clarify the relations that exist between the corporation as whole and both its members and units; iii) to explain how an corporation administers its duties and responsibilities on behalf of people who compose it.}, url = {http://icbo.cgrb.oregonstate.edu/}, author = {M.B. Almeida} } @conference {W04-02, title = {W04-02: Relations between Institutional Roles and Deontic Roles in Biomedical Organizations}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {Doctors, nurses, surgeons, and other healthcare professionals are bearers of institutional roles (e.g. physician role), and it is common to think of these roles as having deontic powers as parts. This is reflected in sentences like: "Part of my job involves an obligation to oversee patient care" and "Doctors at this hospital have the following privileges...". The Document Act Ontology (d-acts; http://purl.obolibrary.rog/obo/iao/d-acts.owl) enables us to represent how deontic powers are created by document acts. Deontic powers are realizable entities that we treat as deontic roles (e.g. obligor role). This means deontic powers are roles themselves. In this talk, we turn to the question of the relationships between institutional roles and deontic roles. We propose that institutional roles can have deontic roles as parts. We illustrate how different kinds of deontic powers give rise to different parthood relations, and we conclude by arguing that such relations can better capture the nature of organizational structure than the traditional reliance on institutional roles alone.}, url = {http://icbo.cgrb.oregonstate.edu/}, author = {Otte J.N. and Brochhausen M.} } @conference {W04-01, title = {W04-01: Ontology of the Organigram}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {Basic Formal Ontology (BFO) is a domain-neutral top-level ontology designed to serve as the starting point for development of domain ontologies designed to support the consistent annotation not only of scientific research data but also of data arising through clinical practice, hospital administration, and regulatory oversight. In each of these areas data are generated relating to what are called deontic entities {\textendash} obligations, duties, contracts, permissions, consents, licenses, and so forth. I will sketch how we can understand entities of these sorts within the BFO framework.}, url = {http://icbo.cgrb.oregonstate.edu/}, author = {B. Smith} } @conference {360, title = {W01-05: Uncertainty analysis and visualization in Large-Scale Vector Fields}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, address = {Corvallis, Oregon, USA}, abstract = {Vector fields are omnipresent in science, engineering, and medicine. Due to the big-data nature of simulated vector field data, uncertainty in the data can lead to difficulties in their physical interpretations. In this talk, we will describe how Morse-decomposition can serve as a means to quantify and control the uncertainty in the data.
}, keywords = {Big data, data uncertainty, data visualization}, url = {http://icbo.cgrb.oregonstate.edu/}, author = {Eugene Zhang} } @conference {350, title = {W01-04: Telling a genome{\textquoteright}s story graphically}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, address = {Corvallis, Oregon, USA}, abstract = {Scientific research is inherently a collaborative task; a dialog among different researchers to reach a consensus understanding of the underlying biology. Information graphics facilitate this dialog because humans are visually wired and can absorb well-executed graphics more quickly than they can absorb the written word or columns of numbers. Visual representations communicate complex ideas quickly and clearly.
This talk will briefly introduce basic principles of designing interactive graphics, with examples from the genomics community illustrating various points. It will also discuss the lessons learned with our own annotation tools: PAINT{\textemdash}a phylogenetically based functional annotation tool (https://github.com/geneontology/paint) , Apollo{\textemdash}a genomic feature editor designed to support structural annotation of gene models (http://genomearchitect.org/),\ and Noctua{\textemdash}a biological-process model builder designed for describing the functional roles of gene products (http://noctua.berkeleybop.org/).
In addition to the graphical elements we summarize the requirements that enable any annotation tool to meet the needs of the research community, including: Real time updates to allow geographically dispersed researchers to conduct joint efforts; Parallel chat mechanisms; Maintaining an evidence trail for all assertions; Well supported history mechanisms and browsing of past versions; Providing different levels of permissions; Facilitating publication; Responsiveness to users{\textquoteright} requests; Documentation and dedicated resources for training and support.
To build the Tree of Life, scientists collect data on all heritable features {\textendash} both genotypes (e.g., DNA sequences) and phenotypes (e.g., anatomy, behavior, physiology) for all living and extinct species.\ The collection of phenomic data for tree-building has lagged far behind the collection of genomic data. Advances in computer vision have the potential to change this situation. In this talk, I will present a computer vision system developed in our lab for extending phenomic matrices, and in this way\ building the Tree of Life.\ Rows of a phenomic matrix represent images of specimens belonging to various species of interest, and columns represent scores of their phenomic characters. Given a\ phenomic matrix where only few rows are manually annotated with character scores, our vision system extends the matrix row-wise by populating missing character scores of the remaining species in the matrix. The talk will present our experimental results on scoring phenomic characters in images of bat skulls, nematocysts, and leaves, available in the Morphobank and Bisque data repositories.
}, keywords = {Bisque data repository, data visualization, Morphobank, Phenotypes, Tree of Life}, url = {http://icbo.cgrb.oregonstate.edu/}, author = {Sinisa Todorovic} } @conference {359, title = {W01-02: Topology-Driven Data Visualization of Large-Scale Tensor Fields}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, address = {Corvallis, Oregon, USA}, abstract = {Spatial-temporally varying simulation data sets are growing at a scale that traditional\ visualization techniques are inadequate to handle. In this talk, we review topology-driven techniques which focus on extracting the key (topological) features in 3D symmetric tensor fields, which can provide a more compact visualization of the data.
}, keywords = {data visualization, tensor fields, topology}, url = {http://icbo.cgrb.oregonstate.edu/}, author = {Yue Zhang} } @conference {361, title = {W01-01: Big Data Visual Analysis}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, address = {Corvallis, Oregon, USA}, abstract = {We live in an era in which the creation of new data is growing exponentially such\ that every two days we create as much new data as we\ did from the beginning of\ mankind until the year 2003. One of the greatest scientific challenges of the 21st\ century is to effectively\ understand and make use of the vast amount of information\ being produced. Visual data analysis will be among our most important tools\ to\ understand such large and often complex data. In this talk, I will present state-of-the-art visualization techniques, applied to important Big Data problems in science, engineering, and\ medicine.
}, keywords = {BIG-data, data visualization}, url = {http://icbo.cgrb.oregonstate.edu/}, author = {Christopher Johnson} }