From workflows to Research Objects: an architecture for preserving the semantics of science (original) (raw)

Semantic Integration for Research Environments

Handbook of Research on Computational Grid Technologies for Life Sciences, Biomedicine, and Healthcare

Research environments for modern, cross-disciplinary scientific endeavors have to unite multiple users, with varying levels of expertise and roles, along with multitudes of data sources and processing units. The high level of required integration contrasts with the loosely-coupled nature of environments which are appropriate for research. The problem is to support integration of dynamic service-based infrastructures with data sources, tools and users in a way that conserves ubiquity, extensibility and usability. This chapter presents a close examination of related achievements in the field and the description of proposed approach. It shows that integration of loosely-coupled system components with formallydefined vocabularies may fulfill the listed requirements. The authors demonstrate that combining formal representations of domain knowledge with techniques like data integration, semantic annotations and shared vocabularies, enables the development of systems for modern e-Science. ...

Workflow-Centric Research Objects: A First Class Citizen in the Scholarly Discourse

2012

A workflow-centric research object bundles a workflow, the provenance of the results obtained by its enactment, other digital objects that are relevant for the experiment (papers, datasets, etc.), and annotations that semantically describe all these objects. In this paper, we propose a model to specify workflow-centric research objects, and show how the model can be grounded using semantic technologies and existing vocabularies, in particular the Object Reuse and Exchange (ORE) model and the Annotation Ontology (AO). We describe the life-cycle of a research object, which resembles the life-cycle of a scientific experiment.

CaosDB—Research Data Management for Complex, Changing, and Automated Research Workflows

Data, 2019

We present CaosDB, a Research Data Management System (RDMS) designed to ensure seamless integration of inhomogeneous data sources and repositories of legacy data in a FAIR way. Its primary purpose is the management of data from biomedical sciences, both from simulations and experiments during the complete research data lifecycle. An RDMS for this domain faces particular challenges: research data arise in huge amounts, from a wide variety of sources, and traverse a highly branched path of further processing. To be accepted by its users, an RDMS must be built around workflows of the scientists and practices and thus support changes in workflow and data structure. Nevertheless, it should encourage and support the development and observation of standards and furthermore facilitate the automation of data acquisition and processing with specialized software. The storage data model of an RDMS must reflect these complexities with appropriate semantics and ontologies while offering simple me...