The Research Object Suite of Ontologies: Sharing and Exchanging Research Data and Methods on the Open Web

Research in life sciences is increasingly being conducted in a digital and online environment. In particular, life scientists have been pioneers in embracing new computational tools to conduct their investigations. To support the sharing of digital objects produced during such research investigations, we have witnessed in the last few years the emergence of specialized repositories, e.g., DataVerse and FigShare. Such repositories provide users with the means to share and publish datasets that were used or generated in research investigations. While these repositories have proven their usefulness, interpreting and reusing evidence for most research results is a challenging task. Additional contextual descriptions are needed to understand how those results were generated and/or the circumstances under which they were concluded. Because of this, scientists are calling for models that go beyond the publication of datasets to systematically capture the life cycle of scientific investigations and provide a single entry point to access the information about the hypothesis investigated, the datasets used, the experiments carried out, the results of the experiments, the people involved in the research, etc. In this paper we present the Research Object (RO) suite of ontologies, which provide a structured container to encapsulate research data and methods along with essential metadata descriptions. Research Objects are portable units that enable the sharing, preservation, interpretation and reuse of research investigation results. The ontologies we present have been designed in the light of requirements that we gathered from life scientists. They have been built upon existing popular vocabularies to facilitate interoperability. Furthermore, we have developed tools to support the creation and sharing of Research Objects, thereby promoting and facilitating their adoption.Comment: 20 page

Expressing the tacit knowledge of a digital library system as linked data

Library organizations have enthusiastically undertaken semantic web initiatives and in particular the data publishing as linked data. Nevertheless, different surveys report the experimental nature of initiatives and the consumer difficulty in re-using data. These barriers are a hindrance for using linked datasets, as an infrastructure that enhances the library and related information services. This paper presents an approach for encoding, as a Linked Vocabulary, the "tacit" knowledge of the information system that manages the data source. The objective is the improvement of the interpretation process of the linked data meaning of published datasets. We analyzed a digital library system, as a case study, for prototyping the "semantic data management" method, where data and its knowledge are natively managed, taking into account the linked data pillars. The ultimate objective of the semantic data management is to curate the correct consumers' interpretation of data, and to facilitate the proper re-use. The prototype defines the ontological entities representing the knowledge, of the digital library system, that is not stored in the data source, nor in the existing ontologies related to the system's semantics. Thus we present the local ontology and its matching with existing ontologies, Preservation Metadata Implementation Strategies (PREMIS) and Metadata Objects Description Schema (MODS), and we discuss linked data triples prototyped from the legacy relational database, by using the local ontology. We show how the semantic data management, can deal with the inconsistency of system data, and we conclude that a specific change in the system developer mindset, it is necessary for extracting and "codifying" the tacit knowledge, which is necessary to improve the data interpretation process

Addressing the tacit knowledge of a digital library system

Recent surveys, about the Linked Data initiatives in library organizations, report the experimental nature of related projects and the difficulty in re-using data to provide improvements of library services. This paper presents an approach for managing data and its "tacit" organizational knowledge, as the originating data context, improving the interpretation of data meaning. By analyzing a Digital Libray system, we prototyped a method for turning data management into a "semantic data management", where local system knowledge is managed as a data, and natively foreseen as a Linked Data. Semantic data management aims to curates the correct consumers' understanding of Linked Datasets, driving to a proper re-use

Unleashing the Effectiveness of Process-oriented Information Systems: Problem Analysis, Critical Success Factors, Implications

Process-oriented information systems (IS) aim at the computerized support of business processes. So far, contemporary IS have often fail to meet this goal. To better understand this drawback, to systematically identify its rationales, and to derive critical success factors for business process support, we conducted three empirical studies: an exploratory case study in the automotive domain, an online survey among 79 IT professionals, and another online survey among 70 business process management (BPM) experts. This paper summarizes the findings of these studies, puts them in relation with each other, and uses them to show that "process-orientation" is scarce and "process-awareness" is needed in IS engineering

Towards Grid Interoperability

The Grid paradigm promises to provide global access to computing resources, data storage and experimental instruments. It also provides an elegant solution to many resource administration and provisioning problems while offering a platform for collaboration and resource sharing. Although substantial progress has been made towards these goals, nevertheless there is still a lot of work to be done until the Grid can deliver its promises. One of the central issues is the development of standards and Grid interoperability. Job execution is one of the key capabilities in all Grid environments. This is a well understood, mature area with standards and implementations. This paper describes some proof of concept experiments demonstrating the interoperability between various Grid environments