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What's New in RDFox Version 5.4: The Console Update?

The RDFox Web Console is no longer experimental, now with full SPARQL 1.1 support, Named Graph support, and the all-new CONSTRUCT Explorer!

The RDFox Web Console is no longer experimental, now with full SPARQL 1.1 support, Named Graph support, and the all-new CONSTRUCT Explorer!

The RDFox Web Console has long been utilized and well-loved by users — encompassing easy accessibility and human-centred visualisation. However, up until now it has been an experimental add-on. With RDFox v5.4 this all changes, seeing an end to the Console’s experimental tag. This change comes about with an increase in the Console’s functionality, now a more holistic and faithful portrayal of RDFox.

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RDFox Web Console Full SPARQL 1.1 Support

"Getting started with and using RDFox is even easier now that 5.4 brings full SPARQL support." — Knowledge Engineer and user of RDFox

The RDFox Console now has full support for SPARQL 1.1, allowing you to use all the queries and updates that were previously available in the Shell and through the REST endpoint.

The new, complete list of queries and updates is as follows.

RDFox Support for SPARQL 1.1 Query Types:

SELECT
CONSTRUCT
ASK

You can find more information about these queries, their application, and their syntax, in the SPARQL query documentation.

RDFox Support for SPARQL 1.1 Update Operations:

INSERT
DELETE
LOAD
CLEAR

RDFox Support for SPARQL 1.1 Graph Management Operations:

CREATE
DROP
COPY
MOVE
ADD

Similarly, you can find out all the details of these operations in the SPARQL update documentation, setting you up perfectly to implement them in your own projects.

To accompany the official SPARQL specification, examples of these commands as used in RDFox can be found in the RDFox documentation. We highly recommend the RDFox getting started guide for any newcomers looking for a simple introduction to RDFox, whether in the Console, Shell, or REST endpoint.

The one query exempt from our support is the nonnormative DESCRIBE that we have omitted for now due to its indeterminate definition.

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The RDFox CONSTRUCT Explorer

“Viewing triples in a table is a compromise, but now with the ability to run CONSTRUCT queries in the console and visually explore their results in their natural graph form, the new connections are easily perceived by the human eye.” — Ontologist and user of RDFox

A wholly new feature to RDFox is the CONSTRUCT Explorer. The concept is simple: when possible — when the result can be expressed as an RDF graph — your query answers can now be visualised as a graph in addition to the pre-existing tabular format.

Unlike the Explorer View in which the visualised nodes and edges are a subset of those present in the data store (ie. If a result exists in the datastore, it will be displayed as it is in the data, otherwise it will be omitted from the graph), the CONSTRUCT Explorer allows users to visualise any graph that can arise from legal SPARQL, regardless of whether the nodes exist in the same form (or at all) in the datastore.

Take the following query for example:

prefix : <https://oxfordsemantic.tech/RDFox/getting-started/>

CONSTRUCT {
?S :generation :child .
?P :generation :parent .
} WHERE {
?S :hasParent ?P
}

A CONSTRUCT query visualised in the CONSTRUCT Explorer. It shows ‘child’ and ‘parent’ nodes that are not present in the data store.

As you can see, the graphs in the Explorer View and the CONSTRUCT Explorer are quite different — the latter having diverged from the datastore significantly, and even added supplementary nodes that do not appear in the data.

The same CONSTRUCT query above, now seen in the Explorer View. Notice only the nodes that exist in the data store are shown, along with their connections that are not relevant to the query.

To activate this extraordinary feature, you must use the output variables ?S ?P ?O in your queries. Capitalisation is required. This ensures your results are valid triples at the very least. This incredibly powerful tool may seem simple on the surface, but it creates endless possibilities.

The table of results for the above CONSTRUCT query.

You can still manipulate the graph as you can in the Explorer View, but you cannot expand it beyond the scope of the query results.

The CONSTRUCT Explorer is restricted to display only 200 nodes (not including literals) to keep the view from becoming an illegible mess of information. Seeing as result sets larger than this cannot currently be displayed as a graph, we suggest you make use of the LIMIT keyword, so that the resulting subgraph can be shown.

An example of how to restrict queries over large data sets, in this case to 100 facts.
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Downloading Results from the RDFox Web Console

“The ability to export query results is a significant convenience, and in conjunction with CONSTRUCT, I can fine-tune queries in the console, view the results, and seamlessly load the export back into RDFox.” — Ontologist and user of RDFox

Whatever the query, you are now able to download your results in any of a range of formats, suited to your preference. These include JSON, Turtle, CSV, and many more.

The format options for exporting console results when not using the special output variables ?S ?P ?O and ?G.

The secondary benefit of using the output variables ?S ?P ?O and now ?G when leveraging named graphs (again, case-specific) derives from their original purpose — forcing the results to be triples or quads. Due to this fact, RDFox will allow you to download your results in a triple or quad friendly format — specifically Turtle, N-Triples, N-Quads, and Trig variants.

Now using the special output variables ?S ?P ?O and ?G, more export formats become available.

Even though the maximum number of results displayed in the Console is 200, exporting the results will export the entire set of results, not just those shown.

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RDFox Named Graph Support

“Adding named graph support to the Console is game changing. The depth and flexibility that it brings to my work is invaluable. I love that we can import data files, such as turtle, directly into a named graph with just a click.” — Software Engineer and user of RDFox

Another game-changing addition to the console is named graph support! You can now visualise and otherwise make use of named graphs just as you would expect, in line with the shell functionality.

An empty named graph can be generated using the CREATE update:

prefix : <https://oxfordsemantic.tech/RDFox/getting-started/>

CREATE GRAPH :firstNamedGraph

You can then populate your new graph with an INSERT or LOAD update. Alternatively, you can navigate to ‘add content’ in the menu, select your desired graph, and ‘drag and drop’ a file containing your data, importing it directly to the graph.

prefix : <https://oxfordsemantic.tech/RDFox/getting-started/>

INSERT DATA { GRAPH :firstNamedGraph { :RDFox :latestVersion 5.4 } }

The ‘drag and drop’ function of RDFox that enables quick and easy file imports into named graphs.

Once filled with data, you are free to update or query as you please — any results can be visualised in the Explorer View, just as with the Default graph. If the results contain more than one graph, you can select which are displayed — one, multiple, or all of them. This of course allows you to switch between graphs simply by choosing one at a time.

Shown is the ability to select named graphs in the Explorer View. Here two graphs have been selected and results from both can be seen on the canvas.
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Filter Options in the Explorers

“The small UI changes have made a huge difference to the way I use RDFox. Working is smoother, more intuitive, and I can navigate my data more efficiently.” — Knowledge Engineer and user of RDFox

For a while now the visualised graph in the Explorer has been malleable, allowing the user to pick and choose what they see after they’ve executed their query. This hasn’t changed. It has, however, become easier and more user friendly.

Upon right-clicking a node, you will see the option to hide the node itself or to hide (or unhide) its in- and out-bound edges. A small dot will appear in the top right-hand corner of the node if some of its edges are hidden. To make this process smoother, we’ve added a filter option to the list — allowing you to search for specific edges, either by the edge IRI or IRI of the connected node. We have also added an ‘All’ option, which simply selects or deselects all of the connecting edges for faster tweaking of large visualisations.

By right-clicking a node, you can choose to hide or reveal other nodes. You can select all at once or use the filer to find specific targets.

It is important to note that changing the graph visually does not change the data, only what is shown.

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Aesthetic Improvements

There have been a number of more subtle changes to the way the Console looks and behaves — all striving to make your life more comfortable. For example, the ‘Query’ and ‘Explore’ buttons at the top have been renamed to ‘SPARQL’ and ‘Explore’ respectively for clarity, and the editor is now resizable. These are just a couple of many ergonomic improvements that we have added, the rest are yours to discover.

The editor can be resized by clicking and dragging its lower border.
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These exciting new additions to the Console have unleashed a myriad of possibilities — allowing you to use RDFox like never before. Using the proper tool doesn’t just make life easier: the right tool in the right hands creates opportunities that go far beyond what could ever be achieved without, enriching and enhancing the possible. This is the RDFox Web Console, now in your hands.

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The Team and Resources

The team behind Oxford Semantic Technologies started working on RDFox in 2011 at the Computer Science Department of the University of Oxford with the conviction that flexible and high-performance reasoning was a possibility for data-intensive applications without jeopardising the correctness of the results. RDFox is the first market-ready knowledge graph designed from the ground up with reasoning in mind. Oxford Semantic Technologies is a spin-out of the University of Oxford and is backed by leading investors including Samsung Venture Investment Corporation (SVIC), Oxford Sciences Innovation (OSI) and Oxford University’s investment arm (OUI). The author is proud to be a member of this team.