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 Linkurious user manual

This is the user manual of Linkurious.

The first two chapters titled Getting Started and Building Your First Graph Visualization will teach you the basics of using Linkurious.

The following chapters are divided in themes. They go through the features of Linkurious and explain how to apply them to successfully visualize graphs. It works both as a manual and a primer on graph visualization.

Just like our software, this guide assumes no prior knowledge of graph visualization techniques. If you read it thoroughly, you will be able to find valuable connections and structural patterns in your data, to improve your graph database, and to communicate your findings efficiently.

 First visualization

In this chapter, we will learn the basics of how to explore and visualize a graph database with Linkurious.

About the dataset

This section of the manual and the following chapters are based on a dataset coming from Crunchbase. Crunchbase is a popular website that tracks the start-up ecosystem, especially companies and investors.

We have used Crunchbase to create a graph database of approximately 75 000 nodes and 250 000 edges. From this we have then created a subset of to focus on San Francisco Bay Area companies only. It contains 14 866 nodes and 47 093 edges. A graph contains 4 types of nodes:

Companies and investors are linked to cities by the HAS_CITY edge. Companies are linked to each other by the ACQUIRED edge. Investors and companies are linked to each other by the INVESTED_IN edge. Companies are linked to markets by the HAS_MARKET edge.

In order to follow this manual, we suggest you to download and install the dataset. Extract the archive and put its content in the folder [YOUR_NEO4J_FOLDER]/data/graph.db.

 First visualization: At first glance

Here is a look at the interface of Linkurious.

Dashboard

The dashboard lists the visualizations created by the user. The following image shows a typical dashboard after starting to use Linkurious.

dashboard

Workspace

The workspace allows to explore the graph database and craft the visualization as a node-link diagram.

workspace

 First visualization: Create a new visualization

From the Quick-search bar

We can start to explore the data and have a rapid look at a node and its relations through the Quick Search bar. The Quick-search bar is accessible directly from the Dashboard. Here we will look for the Company Instagram.

Several results matching the database are proposed, we can select the one we are interested in and a visualization is created:

From New Visualization

An alternative is to create a new visualization, we click on New visualization on the Dashboard.

We can now search for nodes and edges.

For example, if we want to look for the company Instagram, we simply type the name of any property associated with this node. Here, we type Instagram, which is the name of the company. Few suggestions appear containing the word Instagram in one of their properties, we click on the one we are interested in.

Here we selected the company Instagram. The node appears in the graph area.

 First visualization: Inspect data

In order to view the different properties of a node, we click on it. Information immediately appears on the left side of the screen.

Here we can see that there is a node with the id #3886. It is called Instagram and has a Company category. Below we can see the various properties associated with the node.

For example the node has a country property with the value USA.

We can scroll down to see more properties or use the search bar to find a property.

Notice the number next to the node, it is the number of undisplayed edges.

If we want to hide the left panel, we simply click on PROPERTIES (green circle).

Inspect edges in the same manner.

Display the connections of a node

Time to find out about the particular edges of a node. The easiest way to get that information is to double-click on the node we are interested in. Here we are interested in Instagram.

Now we can see all the nodes that are connected to Instagram.

Notice the white halo around each node? All the nodes surrounded by the white halo are connected to the currently selected node (or nodes). In this case, all the nodes are connected to Instagram.

The edges between the nodes represent the edges. All the edges have a direction from one node (the node where the base of the edge is large) to another (the pointy end of the arrow).

If we click on a given edge, the properties of that edge will be displayed in the left panel.

 Search

In this chapter, we will learn how to search nodes and edges with Linkurious.

We will first look at how to search nodes and edges then we will be looking at different advanced search options Linkurious provides.

 Search: Search nodes

We may have millions of nodes in our graph. What if we want to look at a specific node?

The first possibility is to use the Quick Search bar from the Dashboard, where we can either choose to look at nodes or edges (red square). Here we look at nodes:

The second possibility is to use the search bar in the Workspace once we have created a New Visualization.

We can look for a node typing the name of any of its properties. Here, for example, we look for the property Instagram. We see the list of suggestions that match our search.

All the entries in the database containing the word Instagram will appear. These results are grouped by categories and sorted by relevance.

For each result we can see:

We click on the result of our choice, it will be added to the canvas. Now we can visualize it.

How it works : by default, Linkurious indexes all the properties of your graph. If any property of a node matches your search, it will be returned.

For example, you could find the Instagram node by typing instagram, or USA or 2010-03.

The search bar in the Workspace provides an Advanced Search option not available through the Quick search bar of the Visualizations Dashboard. We can thus reduce the results to the category we are interested in. Those options are described in the Advanced search section.

 Search: Search edges

We may have millions of edges in our graph. What if we want to look at a specific edge?

The first possibility is to use the Quick Search bar available on the Dashboard, where we can either choose to look at nodes or edges (red box). Here we look at edges:

The second possibility is to use the search bar in the Linkurious interface once we have created a New Visualization.

By default the finder opens on finding nodes. To search an edge, we click on the Edges tab.

The search for edges works exactly like the search for nodes.

We simply type what we are looking for. We see the list of suggestions that match our search.

In the search result, we can see that there is a edge that has the value 1925000 for the property raised_amount_usd.

We choose the result we are interested in by clicking on it. It is immediately added to the canvas where we can visualize it.

 Search: Advanced search

You are looking for a specific node or edge and the search bar gives you too many results? The text you are searching is too common! You may want to narrow you search by searching on multiple properties.

Searching a startup that has the text facebook on any of his properties gives us 88 matches. Let's try to narrow it down.

We click on the Advanced icon, a new menu appears:

We can see the name of the different categories (city, company, investor and market) in our database and their occurrences. We hit Options to see the name of the different properties in our graph.

In our graph, Facebook is categorized as a Company. We are going to select Company to restrict our search to the nodes to the companies.

We can now see the different results.

the company label

In our graph, a Company can have properties like category, country, first_funding_at or founded_at and more. Not all the nodes categorised as a Company will have all the properties though.

In order to narrow down our results, we are going to search on multiple properties at once. To find Facebook, we are going to look for a company that uses "facebook.com" as its homepage url.

Now when we type facebook, the results are filtered to show only the nodes that have the category Company and the value facebook.com for the property homepage_url.

We can see that the results are now filtered. We can now select the result we are interested in.

The same approach can be applied to the search of edges.

Linkurious will look for exact matches for the values you enter in the search options menu.

 Search: Advanced syntax

Linkurious uses Elasticsearch. You can thus use the Elasticsearch syntax detailed in the Elastic query_string documentation.

Simply type the following commands in the Linkurious search bar.

Field name

Where the "status" field contains "active": status:active

Where the "title" field contains "quick" or "brown" (If you omit the OR operator the default operator will be used): title:(quick OR brown), title:(quick brown)

Where the "author" field contains the exact phrase "john smith": author:"John Smith"

Where any of the fields "book.title", "book.content" or "book.date" contains "quick" or "brown" (note how we need to escape the * with a backslash): book.\*:(quick brown)

Where the field "title" has no value (or is missing): _missing_:title

Where the field "title" has any non-null value: _exists_:title

Ranges

Ranges can be specified for date, numeric or string fields. Inclusive ranges are specified with square brackets [min TO max] and exclusive ranges with curly brackets {min TO max}.

Where the "date" fields has a values in 2012: date:[2012-01-01 TO 2012-12-31]

Where the "count" field in a number between 1 and 5: count:[1 TO 5]

Where the "count" field in greater than 10: count:[10 TO *]

Where the "date" field has a value before 2012: date:{* TO 2012-01-01}

Where the "count" field has a value from 1 up to but not including 5: count:[1..5}

Ranges with one side unbounded can use the following syntax:

Boolean operators

By default, all terms are optional, as long as one term matches. A search for foo bar baz will find any document that contains one or more of foo or bar or baz. We have already discussed the default_operator above which allows you to force all terms to be required, but there are also boolean operators which can be used in the query string itself to provide more control.

The preferred operators are + (this term must be present) and - (this term must not be present). All other terms are optional. For example, the query quick brown +fox -news states that:

Boosting

Use the boost operator ^ to make one term more relevant than another. For instance, if we want to find all documents about foxes, but we are especially interested in quick foxes: quick^2 fox

The default boost value is 1, but can be any positive floating point number. Boosts between 0 and 1 reduce relevance.

Boosts can also be applied to phrases or to groups: "john smith"^2 (foo bar)^4

Grouping

Multiple terms or clauses can be grouped together with parentheses, to form sub-queries: (quick OR brown) AND fox

Groups can be used to target a particular field, or to boost the result of a sub-query: status:(active OR pending) title:(full text search)^2

 Search: Shortest path

Linkurious provides an option to find the shortest past between two nodes in our graph. Here, we will be looking for the connections between the companies Facebook and LinkedIn.

We start with 2 seemingly disconnected nodes, Facebook and LinkedIn that are in our visualization.

We select Find. Next we choose Paths. Now we choose the starting node (LinkedIn) and the destination (Facebook).

We click on Find shortest paths. The results are now displayed.

We can choose Add all to view all the results or choose our preferred path by clicking on it. Our choice is added to the visualization.

 Search: Pattern search

Most graph database support a query language that can be used to express pattern queries in the graph. Neo4j supports the Cypher language, JanusGraph and DataStax Enterprise Graph support the Gremlin language and AllegroGraph and Stardog support the SPARQL language.

In Linkurious, you can directly use these query language from the "Find" > "Patterns" menu. Once a query is previewed (using the Preview button), you can click the "Add all" button to add all matching results to the current visualization.

With Neo4j: the Cypher query language

The Cypher query language is similar to SQL and can be learned from Neo4j's online documentation.

Here is an example Cypher query that is using the Crunchbase dataset (see our online demo):

MATCH (city:CITY)<-[hasCity:HAS_CITY]-(company:COMPANY)
WITH count(company) as score, city, company, hasCity
RETURN city, company, hasCity, score
ORDER BY score DESC
LIMIT 25

This query will match all companies that are connected to a city in the database, count the number of companies in each city, sort the sub-graphs by city and return the 25 cities that have the most companies, with their companies.

Note the Cypher query has to contain a RETURN statement and that all information that need to be displayed in Linkurious must be included in the RETURN statement.

 Manipulating the graph

In this chapter, we'll learn how to manipulate a graph and more exactly the different options Linkurious provides to explore and work on a visualization.

We will see how to expand or collapse nodes. Then we will learn how to select nodes and edges we are interested in, how to hide them, how to apply a layout to the graph and some useful shortcuts.

 Manipulating the graph: Nodes and edges

When we are working on a visualization, all the nodes and edges present in our graph are listed on the left panel of the Workspace. We can explore either the nodes or the edges of our graph going through the list:

If we click on a node or a edge of the list, the camera will focus on it. It is also possible to filter the results by category by clicking on the category we are interested in next to the name of the node or the edge. We can also look for a particular node or edge by using the Finding bar:

Here we filter the list by the category Investor, then we click on the node Adam D'Angelo. The camera centers on this node.

 Manipulating the graph: Expand nodes

Expanding nodes means displaying the nodes that are connected to one node or to a group of nodes.

We can expand nodes in different ways:

The Expand button on the left panel displays the list of available edge types and neighbor categories. We can choose to get everything or to filter the retrieved edges and neighbors.

If the expanded nodes have too many neighbors, it may however lead to unreadable visualization.

Linkurious prevents us from adding too many neighbors at once by asking to filter the retrieved neighborhood. A safeguard popup will appear, providing options to select a specific edge type and neighbor category, to pick the most or least connected neighbors, and to change the maximal number of retrieved neighbors. We may bypass this limit manually.

It is tempting to always add more nodes and edges to your visualization. Beware though, if you are not careful you may end up with too many nodes on your screen... and a worthless visualization.

In order to avoid that, remember to always think twice before adding more information to your visualization. The filters and the hide functionality are here to help!

 Manipulating the graph: Collapse nodes

As we explore the graph, we expand the edges of one or multiple nodes. Sometimes the nodes and edges added to our visualization may not be relevant. In that case, we can use the collapse functionality to remove them.

Collapsing means removing from the visualization the nodes that are connected to one node or to a group of nodes.

Let's say that we are looking at the edges of Instagram. We need to select the node Instagram to have access to the Collapse button.

We then select Collapse. The nodes that are connected to Instagram are removed from the visualization.

You have noticed that two nodes remain after the collapse? They are linked to Instagram and linked together. In that case Linkurious will keep them in your visualization.

 Manipulating the graph: Select nodes and edges

The easiest way to select a node or an edge is to simply click on it. It is also possible to select multiple nodes at once.

To do it, choose Select in the information panel on the left.

You now have a few options :

Shortcuts are also available for this actions. See the list of Workspace shortcuts.

 Manipulating the graph: Lasso

It is possible to select the nodes within a particular area of your visualization. For that, Linkurious provides a lasso.

To do it, choose Select in the information panel on the left. Select Toggle lasso. Move the lasso around the nodes you are interested in selecting to select them.

You can also use the lasso by pressing the ctrl key (cmd on MacOS) while dragging with the mouse to draw the outline of the desired selection.

Release the mouse when you are finished and your selection is activated.

 Manipulating the graph: Hide

Your visualization is getting too complex and you may want to remove from a visualization (i.e. hide) a few nodes or edges to make it easier to understand. Notice that hidden nodes an edges are not deleted from the database.

For example, in the picture bellow, three nodes are selected. Simply click on Hide to remove them from the visualization.

The three nodes are now removed from the visualization.

The Toggle Lasso option can be used to select the nodes we want to hide, we need to make sure the central node is not selected otherwise all the edges connected to this node will also be hidden.

 Manipulating the graph: Layouts

Visualization controls

On the Workspace, various controls are available on the right-bottom of the screen:

A click on the layout button will apply the current layout, which is a fast force-directed layout by default. Three categories of layouts are available: force-directed, hierarchical and radial. They come with pre-defined flavors:

Force-directed layout

Such layouts position nodes according to their connections: connected nodes are usually closed to each others, while disconnected nodes are usually pushed further.

By enabling "incremantal expand" active, force-directed layouts will be applied only on new nodes added to the visualization.

Best Mode: Takes the longest time to compute new node positions but provides better results than the Fast Mode.

Fast Mode (default): Quickly finds new node positions but some overlapping nodes may exist.

Hierarchical layout

Such layouts organize nodes in different layers automatically by aligning nodes of each layer either vertically or horizontally. The root nodes are automatically found.

Top to bottom Mode: Will position root nodes at the top of the screen.

Left to Right Mode: Will position root nodes at the left side of the screen.

Bottom to top Mode: Will position root nodes at the bottom of the screen.

Right to left Mode: Will position root nodes at the right side of the screen.

Radial layout

The Radial layouts positions nodes around the currently selected node (used as center of the layout) based on their graph-theoretical distance (shortest path in the graph). This is useful to reveal layers in data and to draw the rest of the graph in its relation to the pre-defined focus node.

Best mode: Will use an energy model to produce more readable layouts. It is also capable of handling special cases like disconnected components.

Fast mode: Will use a geometrical model, which is faster but can produce more overlapping edges.

 Manipulating the graph: Pinning nodes

It is possible to pin the nodes on your graph visualization. Pinning a node allows to fix it at a specific place on the graph.

To pin a node we can either click on the Pin button of the left panel or right-click on a node then select the Pin button.

A pin symbol appears on the node.

If we pin a node, this node will stay at the same place when we move the rest of the graph, for example using the force-directed layout option:

 Manipulating the graph: Undo/redo

You now have the possibility to revert your last action on a visualization.

You can revert only the last action you do on the visualization.

For example, after expanding a node, clicking the undo button (or using the shortcut ctrl-z or cmd-z on MacOS) will revert the expand by returning the graph to its previous state.

After reverting the expand, you can go back and re-run it by clicking on the redo button (or using the shortcut ctrl-y or cmd-y on MacOS).

Some actions cannot currently be undone :

 Manipulating the graph: Shortcuts

Depending of your operating system, you will have to use the ctrl key (Windows, Linux) or the cmd one (MacOS) to trigger actions.

Camera

Selecting

Creating and Editing

Undo / redo

Shortcut list

The list of shortcuts is directly available in the main menu of the workspace

 Style

In this chapter, we'll learn how to adjust the size, color, captions and text of nodes or edges. These techniques will help you make your visualizations more meaningful.

A default style may be defined by the Administrator of Linkurious, see Chapter Getting Started > Styles. Users can change the styles after creating or opening a visualization. Notice that the styles set in new visualizations are automatically re-applied to newly created visualizations. Users can reset styles at any time.

 Style: Captions

Linkurious lets you choose which of the properties of your nodes and edges should be displayed on the canvas.

On the example below, only the names of the nodes are displayed by Linkurious. In order to customize this, we need to open the design panel on the right.

On the Captions tab, we can see the different properties of the nodes in our graph. The name property is first. For example, we want to show the country in the visualization. To do it, we click on country and it will be added to the displayed properties listed in the dotted area.

The text displayed next to your node changes. Instead of Instagram we have the information Instagram - USA.

The same approach can be used for the edges, which panel is available below the panel of nodes.

Linkurious will use the properties in the order it appears in the list. Placing the cursor on one property, we have the possibility to change the order or to remove a property. If a node doesn't have a property, Linkurious will look for the next property, etc.

 Style: Tooltips

When you right-click on a node or an edge, you can view its properties in a pop-up menu called a tooltip.

We can see that our node is a Company with the /organization/instagram permalink.

It is possible to customize the content of the tooltip and to display only certain properties.

In order to customize this, we need to open the design panel on the right and we go to the Tooltips tab.

We can see the different properties of the nodes of our visualization. By default all the properties are on and are thus displayed. In the bottom of the screen, it is possible to do the same with the edges.

We can turn off the properties we do not want to display.

 Style: Default colors

The default color of the nodes may be defined by the administrator of Linkurious. Here the default color is grey.

When you select nodes and edges, they are immediately highlighted in red and a white halo appears on their connected nodes.

 Style: Nodes color

If all your nodes or edges have the same color, it is difficult to distinguish differences between them without looking at their individual properties. A great way to circumvent that issue is to choose to color the nodes according to a certain property.

For example, our nodes may have a country property that we would like to highlight, thus Linkurious enables us to color the nodes according to a particular property, here country.

This way, a French and a German start-up will have different colors. It will be easier to distinguish them visually.

In the picture below, we see that the start-up Twitter is connected to many investors. At first glance we have no idea where those investors are coming from.

First of all, let's open the design panel on the right corner of the screen and hit the Design tab. We can see all node properties. We click on the color button along the property country to color nodes by this property.

We see:

Notice that the nodes that do not have a country property remain in grey.

To color the nodes according to another property, we first unset colors by clicking on the same color button:

Then, we can click on the color button of another property.

 Style: Edges color

Coloring the edges works exactly the same than coloring nodes as presented previously.

If all your edges have the same color, it is difficult to distinguish differences between them without looking at their individual properties. A great way to circumvent that issue is to choose to color the edges according to a certain property.

First of all, let's open the design panel on the right corner of the screen and hit the Design tab. We can see all edge properties. We click on the edges tab on the bottom.

We click on the color button along property type to color edges by this property.

We see:

To color the edges according to another property, we first unset colors by clicking on the same color button.

Then, we can click on the color button of another property.

 Style: Nodes size

By default all the nodes have the same size. It is possible though to choose to map the size of nodes to certain properties. This way it will be possible to visualize that property.

This technique only applies to quantitative properties.

This works similarly to the coloring functionality of Linkurious. Coloring and sizing can be combined to make powerful visualizations.

For example Andreessen Horowitz is a leading VC firm with 127 edges to different companies it has funded. Which companies have received the most funding? Hard to know by simply looking at this graph.

We are going to size the different companies according to their funding_total property in order to visualize which are the most successful.

We click on the upper right corner to open up the design panel.

We move the mouse to funding_total. In addition to being able to color the nodes according to that property, it is possible to size the nodes. Linkurious can do that for any property that has numerical values.

We are going to select the Size icon.

A new menu appears. It makes it possible to set the Min/max size difference, the difference in size between the node with the lowest value and the node with the highest value.

If we want to view the difference in funding_total we set the Min/max size difference to 12.

Now we can see that few outliers appear as nodes larger than the other nodes.

The larger nodes represent companies like Airbnb, Box, Pinterest or Zynga. We can quickly identify them as the most successful investments of Andreessen Horowitz.

 Style: Edge size

Sizing the edges works exactly the same.

By default all the edges have the same size. It is possible though to choose to map the size of edges to certain properties. This way it will be possible to visualize that property.

This technique only applies to quantitative properties.

This works similarly to the coloring functionality of Linkurious. Coloring and sizing can be combined to make powerful visualizations.

In the picture above we see the company Instagram with various companies that have invested in it.

If we zoom in on the edge between Instagram and Sequoia Capital, we can see it has a raised_amount_usd property with the value 55 000 000.

We are going to size the edges between different companies according to their raised amount property in order to quickly glimpse who invested the most money in Instagram.

We click on the upper right corner to open up the design panel and choose the Edges tab.

We move the mouse to raised amount. In addition to being able to color the edges according to that property, it is possible to size the edges. Linkurious can do that for any property that has numerical values.

We click on the Size icon.

A new menu appears. It makes it possible to set the Min/max size difference, the difference in size between the edge with the lowest value and the edge with the highest value.

If we want to view the difference in raised amount we are going to set the Min/max size difference to 2.

Now we can see that few outliers appear thicker than the other edges.

 Style: Icons

In order to obtain a more intuitive visualization, Linkurious allows you to change the appearance of nodes with a set of icons provided by Font Awesome

We click on the corner of the Workspace to open up the Design panel and choose the Nodes tab.

We move the mouse over categories for example and we have access to both the button to color the nodes or to change their icons.

Hitting the + button, the list of icons available appears. It is then possible to select the icon we want to illustrate our property.

We can thus illustrate our graph with icons to directly obtain a visual explanation of the data at first glance:

Here we have chosen 4 different icons to differentiate the Company nodes according to their property

 Filters

In this chapter, we will learn how to filter the nodes or edges within a visualization according to their properties.

This technique will help you focus on the relevant information in your graph and avoid information overload.

 Filters: Filtering nodes by property

At some point in our graph exploration, we may want to focus on a specific part of our current visualization. A good way to do that is to use filters.

Filters enable us to select or hide multiple nodes or edges at once according to a specific property.

In the graph below, we see the companies who have invested in Grabit, a small firm form the USA.

Where are these companies located in? We could color the nodes according to their country property to know that. But what if we only want to see the American companies Grabit is involved with?

To do that, we open the design panel on the right.

We can see the different properties associated with the nodes in our graph.

We are going to click on country. The different values present in our graph for the property country appear.

We can see that there are companies from CHE and USA.

To select the companies from USA, we fill the check boxes (here we have colored the nodes, see how to color nodes, in order to make the filter action more visible):

Now, on the top of the design panel two buttons appear: Filter and Select.

To select all the nodes from USA, we could click on Select. Instead we are going to choose Filter.

Instantly, all the nodes with the values CHE are removed from the visualization

We can see on the bottom right corner, a symbol for the filter we added to the visualization is created.

Filtering is a great way to remove unimportant information from a visualization. Use it accordingly!

 Filters: Filtering edges by property

We have seen it is possible to use filters to select or remove specific nodes in our visualization according to a property. It is possible to do the same thing with edges.

In the graph below we see the connections of "Grabit". Each edge represents an investment in a start-up. But what kind of investment?

We can open up the design panel to investigate. Let's select Edges on the bottom right corner. We can see the different properties attached to the edges in our dataset. We are going to focus on the funded_at. Let's click on it.

We want to view only the funded_at with the 03/06/2014 code. Let's check the checkbox to keep only 03/06/2014 and click on Filter.

The edges with the 03/06/2014 funded_at are displayed. The other funded_at values are removed from the visualization and a filter symbol is added on the bottom right corner.

 Filters: Combining filters

We have seen that it is possible to filter nodes or edges according to a single property. What if we want to also filter the visualization according to a second property? Linkurious makes it possible to combine filters to do just that.

Simply create a filter after the next and voilà, you can combine filters.

 Filters: Removing a filter

Remove filters

So we have applied one or several filters to your visualization. Maybe it was a mistake or maybe we want to go back a step. How to remove a filter?

An icon for each filter we create is added on the bottom right corner of the screen. The first filter is on the right and the latest on the left.

In this visualization, there are two filters. The nodes are filtered according to the country property. The edges are filtered according to the funding_at property.

To remove the country filter, we click on the cross next to its icon.

The filter is instantly removed. The nodes it hid are then added back to the visualization. The other filter remains active.

 Edit data

In this chapter, we will learn to edit, add and remove nodes or edges to our graph.

 Edit data: Edit properties and categories

Properties are key-value information stored in nodes and edges. It can be the name of a company for instance. Categories are special information to tag nodes and edges. Nodes can be of category Investor or Company, or both.

In Neo4j databases, edges have one and only one category. It is not possible to modify it.

Edition Mode

First of all we need to switch the edition mode to On in the top left corner.

Editing or removing a property

Now if we select a node or an edge and move the mouse cursor next to a property, we can Edit or Delete it.

If we click on Edit, we can change the value of the property. When we are finished, we click on Save. Here we will edit the Name of the Company.

If you wish to delete a property, simply click on Delete.

Editing or removing a category

It is possible to add or remove a category from a node.

Click on the x next to the category to remove it.

To add a category, we click on +. For example, we might be interested in adding the activity of the investors to our graph.

Here we had the category "Angel Investor" to precise the field of work of the company "Ron Conway".

We type the new category, here Angel Investor and hit Save.

The category is added.

 Edit data: Create nodes and edges

On the more options panel, we can choose to create either a node or an edge.

Create a node

We enter a value for the Categorieshere Investor and hit add.

Then for each property we can fill the corresponding value. When it is done, we click on the Save button.

Here we entered the value Paris for the City property, the value France for the Country property and the value NewInvestor for the Name property.

We can see the node created NewInvestor added to our graph.

Create an edge

We have to provide the following information :

Like for the nodes, we can add as many properties as we want to the edge. When we are done, we click on the Save button.

Here we entered the value NewInvestor for the Source, the value INVESTED_IN for the Type property and the value Twitter for the Target and finally 2015 for the funded_year property.

Finally, we can see in our graph our new node and our new edge:

It is also possible to create a new edge between two nodes by selecting those two nodes, right-clicking on the visualization background to display the context menu, then choose Create a new edge. The source and target nodes will be filled.

 Edit data: Delete nodes and edges

Delete a node

If we want to delete a node from our database, we select the node we want to delete and we right-click on the background of our graph. We click onDelete selection in the menu as shown below then we click on Delete from Database.

The node is deleted from the database.

Delete an edge

If we want to delete an edge from our database, we select the edge we want to delete then we right-click on the background of our graph. We click on Delete selection in the menu as shown below then we click on Delete from Database.

The edge is deleted from the database.

 Geography

In this chapter, we will learn how to display graph data on a geographic map.

 Geography: Geographic data

Nodes must contain geographic coordinates as properties. Latitude and longitude data must be expressed in decimal degrees (e.g. "38.8897,-77.0089") as available in many geographic information systems (GIS).

The Administrator should configure which property is the latitude property, and which property is the longitude property of the nodes of the data-source. Without configuration, Linkurious will try to use properties called "latitude" or "lat", and "longitude", "long" or "lng".

When geographic coordinates exist in a node of the visualization, we can switch to the geo mode.

 Geography: Display a geographic map

The Geo mode switch is available on the left panel of the Workspace. We can enable and disable the geo mode at will to switch between the standard "network" view and the geographic view.

Click on it to display the geographical map. Nodes are positioned on the map according to their geographic coordinates. Other nodes are hidden by the "geo coordinates" filter.

We can zoom in and out, drag nodes on the map to improve readability, select nodes and edges, etc. We can always reset the node coordinates to their original location via the actions menu:

Hover the layer icon on the bottom-right of the Workspace with your mouse. The list of available layers is displayed. We can pick another base-map and add overlays, depending on those available on your instance of Linkurious as seen below using the Mapbox provider:

Finally, we can publish an interactive widget from Workspace menu > Publish with the geographical layers.

 Manage visualizations

In this chapter, we'll learn how to save and share the visualization created with Linkurious.

 Manage visualizations: Auto-save

When we are working on a visualization, we can save it through the Menu button then click on Save. Further, the modifications will be automatically saved.

We can access to a saved visualization via the Linkurious dashboard.

 Manage visualizations: Organize

Visualizations are by default added to the Dashboard. From the dashboard we can delete, rename or open a visualization.

We can also organize the visualizations in folders.

Open, rename or delete a visualization

The following actions are possible either when we right-click on a visualization or on the right menu of the dashboard:

Arrange visualizations in folders

To create a folder, we either right-click on the dashboard background or in the right menu Create folder.

We enter the name of our folder.

We hit Save. Our folder is created.

We open the folder by clicking on it. If we want to move a visualization into the folder we used the actions move to when right-clicking on our visualization:

We select the folder we want to move to our visualization:

The visualization has been moved to the folder.

 Manage visualizations: Duplicate

It is possible to duplicate a visualization. This feature might be useful when we want to try new things in our visualization and keep a record of the last version, this way the duplicate is used as a draft.

From the Dashboard

It is possible to duplicate a saved visualization from the Dashboard as follows:

We then click on Duplicate and a copy of our visualization is displayed and directly accessible on the Dashboard:

From the Workspace

It is also possible to duplicate a saved visualization from the Workspace via the Menu:

The duplicate is then accessible from the Dashboard menu.

Note that when duplicating from the Workspace, we are directly switching to the duplicate version to work on it.

It is possible to duplicate a visualization shared with you by another user.

If a user has shared a visualization with you but you are not allowed to modify it, duplicate this visualization. You will be able to modify the copy.

 Manage visualizations: Share

It is possible to share a visualization with another Linkurious user. People we share a visualization with will be able to access it through the interface. If we right-click on a visualization, we can share it as follows:

We click on the Share menu and type the username or email of the person we want to share the visualization with.

We can give read-only rights or allow modifications.

 Manage visualizations: Publish

Linkurious offers the possibility to publish interactive visualizations online. Published visualizations can be accessed with an URL or embedded in a Web page à la Google Maps. They contain a snapshot of graph data at the time the visualization is published. The visualization author can update or un-publish his visualizations anytime. Anyone can explore these visualizations interactively, enabling easier collaboration around graph data.

We can publish a visualization from the Workspace via the left menu:

Before publishing a visualization, we can choose various options to customize the interface:

The options are:

On the screenshot below, we have disabled the legend option and the share option. We can see that the Share button on the right of the screen disappeared. Finally, we can publish it:

The visualization is now available online! We can share the link or integrate it into a web page by adding the script of the web widget into the source code of a web page.

If the server that hosts Linkurious is accessible via intranet only, published visualizations will be available within the organization and won’t be available outside.

 Manage visualizations: Export

We have created a visualization and we want to share or modify its content. We open the Workspace menu, then click on the Export button.

The visualization data can be exported in the following formats:

After clicking on a format, the file is automatically downloaded by the browser.

The PNG export available here will create an image of the complete graph even if we are currently zooming to a specific area. Here is an example:

The PNG export is configurable: setting the zoom ratio of the exported visualization from 1 (zoomed out) to 0.2 (zoomed in) will not only adapt the size of the image, but will also influence the amount of information displayed in the same way it is done on screen.

This feature is different from the Take Screenshot button available by right click in the Workspace or from the Actions menu: they create an image of the displayed area on screen only.

 Manage visualizations: Delete

From the Workspace

We open the Workspace menu, then click on the Delete button. We confirm to delete the visualization.

From the Dashboard

Either:

The visualization is deleted after confirmation.

 Alerts

In this chapter, we will learn how to work collaboratively on alerts. Administrators can configure alerts through the Administration panel. Users will then get a list of matches for each alert.

In fraud investigation or IT monitoring, alert matches happen when anomalous patterns appear in data. A team of analysts will investigate the matches to confirm the cases or dismiss the false positives. Graph visualization helps them to explore data in detail and to collect visual evidence of suspicious activity. They can report the results to escalate the matches by sharing the corresponding visualization.

Challenges rely on the quantity of alert matches processed by analysts: they have limited time and can select which matches to focus on. A score can be defined for an alert such as potential money lost, risk score, or date of the match.

 Alerts: List alerts

If at least one alert is configured by the administrator, users can access the list of alerts from the Alert menu item.

 Alerts: List matches

After double-clicking on an alert we get the list of newly detected matches. Matches are ordered by creation date. If the administrator has set up specific columns to this alert, we can sort matches by those columns.

Each row represents a match.

A match is either new, confirmed, or dismissed. On the left we can access the list of matches by status. For instance the following image shows the list of dismissed matches. We can see who has changed the status of those matches.

To take a decision, you must investigate on a match. Simply click on a row to open the match visualization.

 Alerts: Investigate a match

We visualize a match within a specific interface. On top of the visualization, you can :

Just below, you can download an image of the match, toggle the geo mode, and undo or redo your last action.

By clicking on a node or edge, you will open its property panel to see its type and properties.

Some features of the workspace are present to help you investigate, including expanding nodes or hide items.