ro2019

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Workshop on Research Objects 2019

View the Project on GitHub ResearchObject/ro2019

Peer Review of RO-13

Review 1

Quality of Writing

Is the text easy to follow? Are core concepts defined or referenced? Is it clear what is the author’s contribution?

Abstract is easy to follow, presents a good motivation and introduces clearly the key contribution

Research Object / Zenodo

URL for a Research Object or Zenodo record provided?   Guidelines followed?   Open format (e.g. HTML)?   Sufficient metadata, e.g. links to software?   Some form of Data Package provided?   Add text below if you need to clarify your score.

Overall evaluation

Please provide a brief review, including a justification for your scores. Both score and review text are required.

This abstract introduces a computational approach to attribution, which considers different types of roles and contributions made to a research or scholarship work, beyond the traditional publication counts and grant dollars received.

In particular, the abstract discusses briefly the Contributor Role Ontology (CRO) as the underlying model to implement such system. This model was created based on the requirements gathered from different stakeholders (e.g., scholars, researchers, publishers, funders, and librarians), and its goal is to support the collection, provision and exchange of contribution metadata, which can then be used for visualisation, querying and computational analyses.

Additionally, authors are now on the process to build a model to represent the relationship between an entity, an agent that contributes to it, and the contributions role, whereas the entity can be any research artefact/product (physical or digital). Hence, this model can be also applied to any type of research object (RO).

So, this work is quite relevant to the research object community and related models.

There are some points to discuss. First, authors didn’t mention how they are building this new model; however, it seems that PROV-O could be a very relevant starting point (base) for such model. PROV-O models different relations between an entity, the agent responsible for the creation of such entity, and the activity used or that generated such entity. So, it would be nice to hear authors thoughts about this.

Second, this model and CRO could be nicely integrated/connected to the RO model ontologies. In particular, the RO evolution ontology (roevo) [1], would be the perfect connection point, as it models changes to the research object. These changes, are basically contributions, which are made by the different stakeholders involved in the research/scholarship work. Additionally, roevo is already based on PROV-O, so the connection would be very straightforward and useful.

And even thought authors didn’t mention such connections, it would be interesting to hear their thoughts about this during the workshop.

Review 2

Quality of Writing

Is the text easy to follow? Are core concepts defined or referenced? Is it clear what is the author’s contribution?

Research Object / Zenodo

URL for a Research Object or Zenodo record provided?   Guidelines followed?   Open format (e.g. HTML)?   Sufficient metadata, e.g. links to software?   Some form of Data Package provided?   Add text below if you need to clarify your score.

Overall evaluation

Please provide a brief review, including a justification for your scores. Both score and review text are required.

This talk describes a community initiative with the goal of capturing scientific contributions.

I think the talk is very relevant for the workshop and the conference, as Research Objects are often created collaboratively and it becomes crucial to give proper credit to authors. As the authors mention, this initiative will only be possible with the involvement of the academic community. There are many ways of recording credit automatically, and I would like to know if the authors plan on capturing them in their framework, or just rely on author annotation. Do the authors plan on doing any long term study on the impact of these kind of initiatives in a researcher’s career? Maybe that would be a nice selling point for the community to get more engaged.

As a side comment, I find odd that the contributor role ontology is not derreferenceable (just returns plain rdf), and I wasn’t able to find documentation in human-readable format. In addition, shouldn’t the ontology reflect who contributed to it and how? I only see the same creator for all properties.