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Ricgraph videos

The following videos illustrate the possible uses of Ricgraph. These are not intended to demonstrate how an interface for users would look like, they are meant to illustrate how data repositories can be linked together and how metadata across several systems can be combined. The videos only give a glimpse of possible use-cases. By adding more sources, more metadata can be harvested, and more insights can be obtained.

For these videos, Ricgraph has harvested the following source systems:

  • Utrecht University persons, organizations and research outputs from Pure;
  • Utrecht University data sets from the data repository Yoda;
  • Utrecht University software from the Research Software Directory.

In the videos, you will observe nodes of several colors and sizes:

  • blue nodes indicate persons;
  • yellow nodes indicate journal articles;
  • green nodes indicate data sets;
  • red nodes indicate software;
  • grey nodes indicate all other category nodes, such as organizations and other types of research outputs;
  • small nodes are harvested from Yoda;
  • medium-sized nodes are harvested from the Pure;
  • large nodes are harvested from the Research Software Directory.

None of these videos have sound.

For other illustrations of Ricgraph, see the publications, presentations, newsletters (to subscribe, go to Ricgraph Contact), use, and mentions of Ricgraph.

Return to main README.md file.

Video Start with ORCID to find software

ricgraph_find_software_from_orcid.mp4

This video Start with ORCID to find software (45s) (click to download) first finds the ORCID of a specific person. The ORCID is expanded to show its person-root node, a node which "represents" a person. Subsequently, from this node, we find three software packages from the Research Software Directory. In a next step we follow the link to the source system a node was harvested from.

Video Find persons who contributed to a publication

ricgraph_find_persons_who_contributed_to_output.mp4

In this video Find persons who contributed to a publication (1m23s) (click to download) we find people that have contributed to a specific publication. We copy and paste a DOI from a website. Then Ricgraph shows all person-root nodes that it has found. From the contributors who work for Utrecht University, we can also see their full names. We see that one person has three (slightly) different FULL_NAMEs. For non Utrecht University contributors, this information has not been harvested, so it cannot be shown.

Video Find outputs and organizations from a person

ricgraph_find_outputs_and_organizations_from_person.mp4

In this video Find outputs and organizations from a person (1m10s) (click to download), we first look up all nodes in Ricgraph that are connected to one person, i.e. publications, software and data sets the person has contributed to, and organizations the person is a member of. Then we zoom in on the chair/subunit this person is a member of, and expand it to show his colleagues in the same chair/subunit.

Video Traverse Utrecht University organizations

ricgraph_traverse_uu_organizations.mp4

In this video Traverse Utrecht University organizations (1m12s) (click to download) we do a top-down search in Ricgraph starting with the Pure ID of Utrecht University. Then we expand this node to show all Utrecht University faculties. Next, we expand one faculty to show the people and sub organizations that link to this faculty.

Video Find output common to two persons

ricgraph_find_output_common_to_2_persons.mp4

This video Find output common to two persons (1m5s) (click to download) demonstrates how insights can be obtained by harvesting several source systems. It shows the relation between two individuals. First we find two persons using their last name. Then we let Ricgraph find the shortest path between the two nodes. It finds one node, representing a publication. This means that both people have worked together on this publication.

Video Ricgraph Explorer

ricgraph_ricgraph_explorer.mp4

As mentioned, the videos in the previous sections show how the graph looks like that represents the information in Ricgraph. This can be used to understand how nodes connect to each other. However, for an end user it might be complicated to use the correct search queries. Also, expanding nodes may result in a lot of nodes, so the user might get confused what there is to be learned. That is why we have made Ricgraph Explorer.

The video Ricgraph Explorer (2m20s) (click to download) shows how a more user-centric interface may look like. This video uses Ricgraph Explorer from March 2023. In this video, we look up a specific person with his last name. As can be observed, there are three FULL_NAME nodes for this person, each with a different spelling, from four different sources we have harvested. If we click on one of them, we observe that we have found a lot of information about this person.

The first table shows the node used for the search. The second table displays the IDs of the person found, connected to the person-root node, and the third table shows all other nodes connected to the person-root node. This includes research outputs like publications, data sets and software, as well as the (sub)organization this person works. We can sort columns, and we can use faceted navigation (i.e. filter on name or category nodes).

Epilogue

Intrigued by the possibilities? Do you have a specific use case you would like to see? Don’t hesitate to contact us.

Return to main README.md file

Return to main README.md file.