Data Ontology and an Information System Realization for Web-Based Management of Image Measurements

Image acquisition, processing, and quantification of objects (morphometry) require the integration of data inputs and outputs originating from heterogeneous sources. Management of the data exchange along this workflow in a systematic manner poses several challenges, notably the description of the heterogeneous meta-data and the interoperability between the software used. The use of integrated software solutions for morphometry and management of imaging data in combination with ontologies can reduce meta-data loss and greatly facilitate subsequent data analysis. This paper presents an integrated information system, called LabIS. The system has the objectives to automate (i) the process of storage, annotation, and querying of image measurements and (ii) to provide means for data sharing with third party applications consuming measurement data using open standard communication protocols. LabIS implements 3-tier architecture with a relational database back-end and an application logic middle tier realizing web-based user interface for reporting and annotation and a web-service communication layer. The image processing and morphometry functionality is backed by interoperability with ImageJ, a public domain image processing software, via integrated clients. Instrumental for the latter feat was the construction of a data ontology representing the common measurement data model. LabIS supports user profiling and can store arbitrary types of measurements, regions of interest, calibrations, and ImageJ settings. Interpretation of the stored measurements is facilitated by atlas mapping and ontology-based markup. The system can be used as an experimental workflow management tool allowing for description and reporting of the performed experiments. LabIS can be also used as a measurements repository that can be transparently accessed by computational environments, such as Matlab. Finally, the system can be used as a data sharing tool

MiMiR - an integrated platform for microarray data sharing, mining and analysis

Background: Despite considerable efforts within the microarray community for standardising data format, content and description, microarray technologies present major challenges in managing, sharing, analysing and re-using the large amount of data generated locally or internationally. Additionally, it is recognised that inconsistent and low quality experimental annotation in public data repositories significantly compromises the re-use of microarray data for meta-analysis. MiMiR, the Microarray data Mining Resource was designed to tackle some of these limitations and challenges. Here we present new software components and enhancements to the original infrastructure that increase accessibility, utility and opportunities for large scale mining of experimental and clinical data.Results: A user friendly Online Annotation Tool allows researchers to submit detailed experimental information via the web at the time of data generation rather than at the time of publication. This ensures the easy access and high accuracy of meta-data collected. Experiments are programmatically built in the MiMiR database from the submitted information and details are systematically curated and further annotated by a team of trained annotators using a new Curation and Annotation Tool. Clinical information can be annotated and coded with a clinical Data Mapping Tool within an appropriate ethical framework. Users can visualise experimental annotation, assess data quality, download and share data via a web-based experiment browser called MiMiR Online. All requests to access data in MiMiR are routed through a sophisticated middleware security layer thereby allowing secure data access and sharing amongst MiMiR registered users prior to publication. Data in MiMiR can be mined and analysed using the integrated EMAAS open source analysis web portal or via export of data and meta-data into Rosetta Resolver data analysis package.Conclusion: The new MiMiR suite of software enables systematic and effective capture of extensive experimental and clinical information with the highest MIAME score, and secure data sharing prior to publication. MiMiR currently contains more than 150 experiments corresponding to over 3000 hybridisations and supports the Microarray Centre's large microarray user community and two international consortia. The MiMiR flexible and scalable hardware and software architecture enables secure warehousing of thousands of datasets, including clinical studies, from microarray and potentially other -omics technologies

Development of a client interface for a methodology independent object-oriented CASE tool : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Computer Science at Massey University

The overall aim of the research presented in this thesis is the development of a prototype CASE Tool user interface that supports the use of arbitrary methodology notations for the construction of small-scale diagrams. This research is part of the larger CASE Tool project, MOOT (Massey's Object Oriented Tool). MOOT is a meta-system with a client-server architecture that provides a framework within which the semantics and syntax of methodologies can be described. The CASE Tool user interface is implemented in Java so it is as portable as possible and has a consistent look and feel. It has been designed as a client to the rest of the MOOT system (which acts as a server). A communications protocol has been designed to support the interaction between the CASE Tool client and a MOOT server. The user interface design of MOOT must support all possible graphical notations. No assumptions about the types of notations that a software engineer may use can be made. MOOT therefore provides a specification language called NDL for the definition of a methodology's syntax. Hence, the MOOT CASE Tool client described in this thesis is a shell that is parameterised by NDL specifications. The flexibility provided by such a high level of abstraction presents significant challenges in terms of designing effective human-computer interaction mechanisms for the MOOT user interface. Functional and non-functional requirements of the client user interface have been identified and applied during the construction of the prototype. A notation specification that defines the syntax for Coad and Yourdon OOA/OOD has been written in NDL and used as a test case. The thesis includes the iterative evaluation and extension of NDL resulting from the prototype development. The prototype has shown that the current approach to NDL is efficacious, and that the syntax and semantics of a methodology description can successfully be separated. The developed prototype has shown that it is possible to build a simple, non-intrusive, and efficient, yet flexible, useable, and helpful interface for meta-CASE tools. The development of the CASE Tool client, through its generic, methodology independent design, has provided a pilot with which future ideas may be explored

A design recording framework to facilitate knowledge sharing in collaborative software engineering

This paper describes an environment that allows a development team to share knowledge about software artefacts by recording decisions and rationales as well as supporting the team in formulating and maintaining design constraints. It explores the use of multi-dimensional design spaces for capturing various issues arising during development and presenting this meta-information using a network of views. It describes a framework to underlie the collaborative environment and shows the supporting architecture and its implementation. It addresses how the artefacts and their meta-information are captured in a non-invasive way and shows how an artefact repository is embedded to store and manage the artefacts

Specifications and Development of Interoperability Solution dedicated to Multiple Expertise Collaboration in a Design Framework

This paper describes the specifications of an interoperability platform based on the PPO (Product Process Organization) model developed by the French community IPPOP in the context of collaborative and innovative design. By using PPO model as a reference, this work aims to connect together heterogonous tools used by experts easing data and information exchanges. After underlining the growing needs of collaborative design process, this paper focuses on interoperability concept by describing current solutions and their limits. Then a solution based on the flexibility of the PPO model adapted to the philosophy of interoperability is proposed. To illustrate these concepts, several examples are more particularly described (robustness analysis, CAD and Product Lifecycle Management systems connections)

Towards structured sharing of raw and derived neuroimaging data across existing resources

Data sharing efforts increasingly contribute to the acceleration of scientific discovery. Neuroimaging data is accumulating in distributed domain-specific databases and there is currently no integrated access mechanism nor an accepted format for the critically important meta-data that is necessary for making use of the combined, available neuroimaging data. In this manuscript, we present work from the Derived Data Working Group, an open-access group sponsored by the Biomedical Informatics Research Network (BIRN) and the International Neuroimaging Coordinating Facility (INCF) focused on practical tools for distributed access to neuroimaging data. The working group develops models and tools facilitating the structured interchange of neuroimaging meta-data and is making progress towards a unified set of tools for such data and meta-data exchange. We report on the key components required for integrated access to raw and derived neuroimaging data as well as associated meta-data and provenance across neuroimaging resources. The components include (1) a structured terminology that provides semantic context to data, (2) a formal data model for neuroimaging with robust tracking of data provenance, (3) a web service-based application programming interface (API) that provides a consistent mechanism to access and query the data model, and (4) a provenance library that can be used for the extraction of provenance data by image analysts and imaging software developers. We believe that the framework and set of tools outlined in this manuscript have great potential for solving many of the issues the neuroimaging community faces when sharing raw and derived neuroimaging data across the various existing database systems for the purpose of accelerating scientific discovery

Neuroimaging study designs, computational analyses and data provenance using the LONI pipeline.

Modern computational neuroscience employs diverse software tools and multidisciplinary expertise to analyze heterogeneous brain data. The classical problems of gathering meaningful data, fitting specific models, and discovering appropriate analysis and visualization tools give way to a new class of computational challenges--management of large and incongruous data, integration and interoperability of computational resources, and data provenance. We designed, implemented and validated a new paradigm for addressing these challenges in the neuroimaging field. Our solution is based on the LONI Pipeline environment [3], [4], a graphical workflow environment for constructing and executing complex data processing protocols. We developed study-design, database and visual language programming functionalities within the LONI Pipeline that enable the construction of complete, elaborate and robust graphical workflows for analyzing neuroimaging and other data. These workflows facilitate open sharing and communication of data and metadata, concrete processing protocols, result validation, and study replication among different investigators and research groups. The LONI Pipeline features include distributed grid-enabled infrastructure, virtualized execution environment, efficient integration, data provenance, validation and distribution of new computational tools, automated data format conversion, and an intuitive graphical user interface. We demonstrate the new LONI Pipeline features using large scale neuroimaging studies based on data from the International Consortium for Brain Mapping [5] and the Alzheimer's Disease Neuroimaging Initiative [6]. User guides, forums, instructions and downloads of the LONI Pipeline environment are available at http://pipeline.loni.ucla.edu