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Phylogenetic analyses can resolve historical relationships among genes, organisms or higher taxa. Understanding such relationships can elucidate a wide range of biological phenomena including the role of adaptation as a driver of diversification, the importance of gene and genome duplications in the evolution gene function, or the evolutionary consequences of biogeographic shifts. The variety of methods of analysis and data types typically employed in phylogenetic analyses can pose challenges for semantic reasoning due to significant representational and computational complexity. These challenges could be ameliorated with the development of an ontology designed to capture and organize the variety of concepts used to describe phylogenetic data, methods of analysis and the results of phylogenetic analyses. In this paper, we discuss the development of PhylOnt — an ontology for phylogenetic analyses, which establishes a foundation for semantics-based workflows including meta-analyses of phylogentic data and trees. PhylOnt is an extensible ontology, which describes the methods employed to estimate trees given a data matrix, models and programs used for phylogenetic analysis and descriptions of phylogenetic trees including branch-length information and support values. The relational vocabulary included in PhylOnt will facilitate the integration of heterogeneous data types derived from both structured and unstructured sources. To illustrate the utility of PhylOnt, we annotated scientific literature to support semantic search. The semantic annotations can subsequently support workflows that requiring the exchange and integration of heterogeneous phylogenetic information.

Document management has become an important consideration for the scientific community over the last decade. Human knowledge is central to many scientific domains, thus it is not possible to completely automate the document management process. Managing scientific documents require a semi-automatic approach to overcome issues of large volume, yet support the human participation in the process. In this paper we present Kino, a set of tools that streamline the document management process in life science domains. Kino is integrated with National Center for Biomedical On-to logy (NCBO), providing scientists access to quality domain models. Annotated documents are indexed using a faceted indexing and search engine that provides fine grained search capabilities to the scientists. We present two use cases that highlight the pain points in managing scientific literature and also include an empirical evaluation.

This paper presents a semi-automatic Web service composition approach. This approach ranks all available candidate Web service operations based on semantic annotations and suggests service operations to a human designer during the process of Web service composition. The ranking scores are based on data mediation, functionality and formal service specifications. A formal graph model, an IODAG, is defined to formalize an input/output schema of a Web service operation. Three data mediation algorithms are developed to handle the data heterogeneities arising during Web service composition. The data mediation algorithms analyze the schemas of the inputs and outputs of service operations and consider the structures of the schemas. A typed representation for our data mediation approach, which formalizes the data mediation problem as a subtype-checking problem, is presented. An evaluation is performed to study the effectiveness of different data mediation and service suggestion algorithms used to assist designers composing Web services.