Please contact the organizers at firstname.lastname@example.org for any questions.
Scholarly Communication has evolved significantly in recent years, with an increasing focus on Open Research, FAIR data sharing and community-developed open source methods. The concepts of authorship and citation are changing, as researchers are increasingly reusing and evolving common software tools and datasets. Yet with a growing amount of cloud compute power and open platforms available, reproducibility of computational analyses becomes more challenging, and not yet commonly included in peer review. While recent advances in scientific workflows and provenance capture systems have improved on this situation, a question remains on how to publish, archive, explore and understand digital research outputs, as academic authors and publishers remain focused on PDFs and the occasional CSV file, with the Web and Open Research often left to “best effort” rather than being the expected norm.
A number of community initiatives have begun to explore how to package various multi-part research outcomes with their context, how to handle distributed and living content and how to port and safely exchange these “Research Objects” between platform and between researchers.
One such approach is Research Object which has proposed a way to package and describe research outputs, data, methods, workflows, provenance and structured metadata, reusing existing Web standards and formats. Research Objects, and Research Object-like approaches have gathered pace across:
However, many challenges remain as to how to increase Research Object uptake with data providers, researchers, infrastructures, publishers and other stakeholders; credit and tracking metrics; develop supporting tooling; building effective community efforts and the relationship of rich metadata manifests with emerging container platforms.
In this workshop, following on from the successful RO2018 held at eScience 2018, we will explore recent advancements in Research Objects and publishing of research data.
This workshop aims for a mix of presentation sessions and “unconferencing” sessions including:
Submissions are welcome for Short articles (about 4-8 pages), Abstracts for oral communication (1-2 pages) and Poster and demo abstracts (1-2 pages)
RO2019 encourages open peer review, and recommend that reviewers are named and attributed; however reviewers may be anonymous if so desired.
Please see our submission guide for details, then either:
Carole Goble heads researchobject.org along with her team in the eScience Lab at the University of Manchester, whose mission is to disseminate knowledge about research objects, their concept and their adoption. She has spent 25 years working in e-Science on computational workflows, reproducible science, open sharing, and knowledge and metadata management in a range of disciplines.
She co-established the myExperiment.org workflow repository and the FAIRDOMHub.org for systems biology asset sharing. She is the co-lead of the interoperability platform for ELIXIR, the EU Research Infrastructure for Life Sciences, Head of Node of ELIXIR-UK and co-founder of the UK’s Software Sustainability Institute. She has keynoted twice for IEEE e-Science (2005, 2012). In 2008 she was honoured by Microsoft Jim Gray award for outstanding contributions to eScience.
Raul Palma is the semantic technologies coordinator in the network services division at Poznan Supercomputing and Networking Center (PSNC). He has more than twelve years of experience in research and development in different areas related to Artificial Intelligence, such as knowledge representation, discovery and reasoning, Open and Linked Data, and the application of Semantic technologies in different domains.
He has been involved in the development of the Research Object model and supporting technologies since their conception, and has been devoted to their dissemination, adoption and exploitation in different domains. He has led the development team of the research object management platform ROHub (http://www.rohub.org/), built entirely around the research object model and inspired by sustainable software management principles.
Currently, Raul is leading PSNC activities in EVER-EST project, where Research Objects and ROHub have been used as the cornerstone to build a Virtual Research Environment for Earth Sciences. An ACM member and former MAE-AECI scholarship holder, Raul holds a Ph.D. in Computer Science and Artificial Intelligence (cum laude) and regularly publishes and reviews for top scientific conferences and journals in the area.
Stian Soiland-Reyes is a senior Research Software Engineer, working at the eScience Lab in the University of Manchester since 2006. His research and development interests are in reproducible Open Science by applying semantic technologies and distributed computing. He is a persistent advocate of Open Access, data sharing and improving practices of academic publishing. As a keen open source developer and Foundation Member of Apache Software Foundation, he has a key role in development of the workflow system Apache Taverna (incubating) and Common Workflow Language (he is on the CWL leadership team), as well as contributing to Linked Data initiatives such as Commons RDF, Jena and JSON-LD.
Stian was a key participant in the Wf4Ever project, where he co-led specifications for preserving and publishing workflow-based Research Objects. He is a co-author of the W3C PROV-O standard for provenance as well as the PAV provenance ontology, he has contributed to the W3C Web Annotation Data Model, ORCID and OAI-ORE. Stian currently work with the BioExcel Centre of Excellence with attention to interoperable workflows in HPC and HTC environments for biomolecular simulation and modelling.
Daniel is a researcher at the Information Sciences Institute of the University of Southern California and along term collaborator with the Ontology Engineering Group at the Artificial Intelligence Department of the Computer Science Faculty of Universidad Politécnica de Madrid.
His research activities focus on e-Science and the Semantic Web, specifically on how to increase the understandability of scientific workflows using their provenance (i.e., steps, outputs, inputs, intermediate results) and exposing them as Linked Data.
Daniel has participated in standardization efforts and collaborated with different researchers throughout his career, which have led to significant contributions to my PhD work. He has been involved in the development of the Research Object model and its ontologies since the concepts inception in the EU project Wf4ever.