About


The OpenBio-C project aims to develop a self-sustaining and community-responsive platform that streamlines the wealth of available open Bioinformatics resources to accelerate multi-disciplinary collaboration and boost innovation in post-genomics biomedical research. Our approach adopts the principles of reproducible, reusable and remixable computer-aided research, and builds on top of state-of-the-art concepts and converging technologies for simple, fast and scalable specification and execution of scientific workflows. The foreseen platform enables innovative networking and community building among researchers, facilitates knowledge sharing and co-creation, assures better-informed collaboration, and expedites gaining of insights. Paying particular attention to the issues of data and research provenance and attribution, the platform integrates a set of innovative services for the management of research resources and competences. The overall approach ensures the interoperability of the abovementioned resources and services from a technical, conceptual and user interface point of view.


The main challenge of the contemporary research ecosystem is to enable optimal use of the complex research landscape, both in terms of research data and the analytical methods involved. Computational analysis to discover meaningful patterns in massive, interlinked datasets is rapidly becoming a routine research activity. Providing machine-readable data as the main substrate for knowledge discovery and for enabling these complex scientific processes to run smoothly and sustainably is one of the grand challenges of current research infrastructures. This is most relevant for the interdisciplinary post-genomics biomedical research domain. The motivation that guides our approach is to offer simple bridging among existing gaps in research without trying to overshadow other initiatives and without willing to offer another monolithic introvert environment that demands from users to do science in a predefined way.

Our approach in OpenBio-C aims to include existing bridging solutions and promote, engage and guide users to create new ones. The existing gaps to bridge are:

  • the data gap, which is due to the existence of many unlinked and diverse data sources – to remedy this, our solution offers detailed data description, provides data provenance, links data sources with tools to import them, and connects data with formats, ontologies and tools; it also makes visible which computational environments are more appropriate for specific data analysis and which are the available visualization options;
  • the semantic gap, which is due to the existence of multiple vocabularies and unmerged ontologies – to remedy this, users can include existing ontologies and tools for the semantic annotations to be attached to data and tools, and provide statistics on which ontologies are most used and which are obsolete or incomplete according to user comments and ratings;
  • the knowledge gap, which is due to the existence of heterogeneous, fast growing and fragmented knowledge resources – to remedy this, data, tools and workflows are linked to published papers and online documentation; rich text description and keywords can be attached to every object in the platform; relevant information is made visible and searchable; and simple recommendations for data/tools/workflows integration are offered;
  • the collaboration gap, which is due to the existence of differences in user interests, objectives and methodologies – to remedy this, users are allowed to: build personal profiles where they state their expertise, publications and preferences in tools, languages and operating environments; build reputation according to their contributions similar to popular services (i.e. stackexchange.com, biostars.com); express opinions and rate every object in the environment including the comments of other users; and search and locate other users according to their profile or contributions.


The foreseen OpenBio-C platform will empower biomedical and post-genomics research communities to efficiently and effectively collaborate thanks to reliable and user-friendly access to integrated and interoperable resources of different types. The platform integrates and manages heterogeneous data and knowledge sources, as well as respective processing methodologies and tools, through a service-oriented Scientific Workflow editing and execution environment. The overall approach builds on the synergy between human and machine reasoning capabilities to tame information overload and cognitive complexity in biomedical and post-genomics research settings. It provides researchers with the required capacity to easily assemble their own working environment using their preferred tools, and exploit the wealth of available resources and competences.

Workpackages & Deliverables

WP1. User requirements and system specifications

   (Μ1 – Μ9)

WP2. Development of an environment for the synthesis of scientific workflows

   (Μ6 – Μ36)

WP3. Development of a scientific collaboration environment

   (Μ6 – Μ36

WP4. Semantic representation of research objects

   (Μ6 – Μ36)

WP5. Development of an environment for the execution of scientific workflows

   (Μ13 – Μ36)

WP6. Platform validation with real scientific workflows

   (Μ13 – Μ36)

WP7. Sustainability and strategic exploitation of the project results

   (Μ13 – Μ36)

WP8. Publicity of project results in trade fairs

   (Μ13 – Μ36)


D1. User requirements and initial prototype implementation

D2. Building a scientific workflow management system with virtual computing technology

D3. Building a computer-supported collaborative research system

D4. Models and mechanisms for the semantic representation and extraction of research objects

D5. Scientific workflow execution environment

D6. Final version of the OpenBio-C platform

D7.1. Sustainability and strategic exploitation plan – first version

D7.2. Sustainability and strategic exploitation plan – final version

D8.1. Trade fairs publicity material – first version

D8.2. Trade fairs publicity material – final version


Partners


forth ics

FORTH-ICS (PI: George Potamias , Principal Researcher) participates in the OpenBio-C project with the Laboratory of Computational Biomedicine (CBML, www.ics.forth.gr/cbml). CBML research activities related to the OpenBio-C project include: semantic indexing and integration of heterogeneous clinical genomic data; development of methodologies and techniques for large-scale genomic analysis (GWAS studies, management and processing of NGS data analysis with advanced workflows / pipelines; development of innovative IT technologies in the context of personalized / genomic / precision medicine; development of methodologies, tools and systems for the discovery of knowledge from heterogeneous biomedical data (including biomedical literature mining) with the development of advanced natural language processing (NLP) techniques. CBML has actively participated and participates in a large number of National/Greek and European projects. CBML members have published several papers related to the OpenBio-C objectives and targets.


The company “Moumouris Konstantinos” has been operating since 1999; its main activities concern the design, management and installation of PC networks for large customers. It has participated either directly or as a subcontractor in several large IT projects in the field of health. Work carried out focuses on the integrated provision of IT management solutions through Virtual Cloud Infrastructure and the provision of Voice over IP solutions. The company manages a series of third-party networks and IT infrastructures adhering to international standards. Annually, it takes care of the smooth operation of approximately 4000 workstations, 237 Servers, 9476 network ports and 749 Wi-Fi Access Points. The company has collaborated with public sector bodies such as the Region of Crete (Department of Physical Education), the Institute of Informatics at FORTH, the hospitals of Crete, the Asklepios Diagnostic Center, and the Chronic Diseases Hospitals of Lassithi and Chania. In addition, the company operates in the Hospitality sector, offering VoIP Unified Communication & Centralized Wi-fi solutions. It builds on open software solutions to reduce the cost of managing client infrastructures while also delivering more efficient CaPex and OpEx combinations. As a subcontractor of the Orco Unisystems Group, the company also participates in the management of the Oracle Clusters that support the integrated information system of the 7th Health District of Crete. Also committed to carry out research work, the company has participated in the project “Development of research infrastructure of clinical computer tools and services for the best diagnosis and assessment of the optimal personalized treatment of oncological diseases” of the Cross Border Cooperation Program “Greece-Cyprus 2007-2013”.


unip

The University of Patras (UPAT) is the third largest University in Greece regarding the size of students’ potential, the faculty members, administrative personnel, number of departments, and accredited students titles. It includes 24 Departments, with a large number of sectors and consequently a great range of disciplines. Participation of UPAT in the OpenBio-C project is through the Industrial Management & Information Systems (IMIS) Lab of the Mechanical Engineering & Aeronautics Department (PI: Prof. N. Karacapilidis). IMIS Lab members have a large experience in designing and implementing innovative software to enhance collaboration and support knowledge management and collective decision making processes in various types of communities and organizations. This experience is documented through the strong involvement of the Lab’s members in competitive R&D projects funded by the EC in the context of FP6 and FP7 programs (e.g. DICODE and PALETTE). IMIS Lab members have participated in all major European and National R&D programs, as well as in several international collaborative programs; through such actions, they have also gained substantial experience in handling diverse Big Data management issues and in achieving interoperability with external information systems and web services. The solutions developed build on the synergy of human and machine reasoning and provide alternative forms of visual representation of the relevant information. In addition, IMIS Lab members have the necessary scientific skills to analyze the practices and problems that characterize modern collaborative environments, both technologically and organisationally. Finally, they possess the necessary cutting-edge know-how to develop semantic and technology integration software.

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