The Data meets Applied Ontologies in Open Science and Innovation (DAO-SI) workshop will take place at the fourth edition of the Joint Ontology Workshops (JOWO) to be held on September 19-21, 2018 in Cape Town, South Africa.
Workshop description and objectives
The Internet of Thing era is delivering any kind of information (Floridi, 2014), and `Big Data’ has become the de-facto buzzword for referring to large amounts of heterogeneous data. Big data can be exploited to deliver data as a service applications in different domains, such as smart factories, recommendation systems, strategic dashboards, etc.
Although collecting large amounts of data is effortless given the almost unlimited storage capacity offered by cloud infrastructures, accessing these data and analysing them is more challenging, especially due to the different representation formats used to store the data and to the almost unexploited semantics implicit in the data themselves.
Ontologies, on the other hand, provide a common conceptual layer for different representation formats, and, they make data semantics explicit. Therefore, ontologies can mediate data heterogeneity by fostering a common representation on which data analysis and visualisation techniques can operate, and can enrich data with semantics, allowing to exploit all the available knowledge contained.
This explains why ontologies, and ontology-based platforms for data management, play an increasingly prominent role in supporting evidence-based decision and policy-making both in public and private organisations (e.g., universities, research institutions, companies, founding agencies and public administrations). Data is the factual evidence to:
- define future research priorities (e.g., fields, technologies, sectors);
- identify emerging technology and competitive solutions for transfer and investments;
- shape new innovation policies based on scientific and technological evidence;
- perform investment impact measuring and monitoring.
Currently, key S&I data elements are dispersed across a multitude of distinct agencies and research institutions or are in third-party databases. They are often neither in structured format nor systematically shared across organisations, and the universe of data on patents, publications, and citations is typically maintained into closed-off silos (J.Lane, 2011). In such a context, ontology-mediated data management infrastructures can help bringing together inputs and outcomes from a variety of sources in an open and interoperable fashion. The total budget absorbed by all European R&I data management infrastructures is today in the range of 10 billion € per year (ESFRI roadmap, 2016), and it is partially invested to promote synergies in regards to the semantic interoperability among data, services and their final users through the application of domain ontologies, taxonomies, context-sensitive data interlinking, metadata quality and standardisation, etc.
The goal of the 2018 edition of DAO-SI is to provide opportunities for stakeholders from the academia, industry and public organisations to present their latest developments in ontology-mediated data integration and analysis techniques, and data-driven applications, with a special focus on open S&I data management for decision and policy-making.
The workshop will be a great opportunity to synthesise new insights, and disseminate knowledge across field boundaries to promote interaction between these stakeholders.
July 2, 2018: submission deadline (EXTENDED)
July 23, 2018: acceptance notification to authors
August 15, 2018: camera ready versions due
September 17-18, 2018: JOWO 2018
September 19-21, 2018: FOIS 2018
Papers must be submitted in PDF format and must follow the IOS Press FOIS formatting guidelines, available on the iopress.nl website. Submissions should not be longer than 14 pages. Moreover, to be published in the CEUR proceedings, a paper must contain at least 5 pages.
Accepted articles will be published in the JOWO proceedings (as CEUR workshop proceedings – see previous editions here).
Submission of an article should be regarded as an agreement that, should the article be accepted, at least one of the authors will attend the workshop to present the work.
Roberto Confalonieri, Smart Data Factory, Faculty of Computer Science, Free University of Bozen-Bolzano, Italy
Alessandro Mosca, SIRIS Lab, Research division of SIRIS Academic, Barcelona, Spain
Diego Calvanese, Smart Data Factory, Faculty of Computer Science, Free University of Bozen-Bolzano, Italy
Said Fathalla, University of Bonn, Germany
Christoph Lange, Smart Data Analytics, Applied Computer Science, University of Bonn
Ali Khalili, Vrije Universiteit Amsterdam, Netherlands
Patrick Ohnewein, IDM Südtirol, Italy
Niklas Petersen, Smart Data Analytics, Fraunhofer IAIS, Bonn, Germany
Fernando Rodas, SIRIS Academic, Barcelona, Spain
Guillem Rull, SIRIS Academic, Barcelona, Spain
Vitalis Wiens, Smart Data Analytics, Fraunhofer IAIS, Bonn, Germany