Non-Ribbon Chord Diagram: Definition and Examples

Non-ribbon chord diagrams show who's connected without the visual weight of traditional ribbon charts. This guide covers when to use them, how to read them, data requirements, and step-by-step instructions for building one in Excel or a BI tool.

What is a non-ribbon chord diagram

Need relationship intelligence (who connects to whom) more than a precise accounting of volume? A non-ribbon chord diagram is a great fit. Need to show that one relationship dominates the volume? Pick a chart that encodes magnitude (like a ribbon chord or Sankey).

This is a circular visualization showing relationships between categories using thin curved lines instead of thick filled ribbons. Categories sit as arcs around a circle. Lines between those arcs reveal which categories connect. The lines are simple strokes, not tapered shapes.

Standard ribbon chord diagrams use thick ribbons where width encodes flow magnitude. The non-ribbon version strips that away. You lose the magnitude information, but you gain clarity when all you need to know is whether a connection exists.

Some tools call this an arc chord diagram or circos-style link diagram. The names vary, but the structure stays the same. In Domo, you can build interactive chord-style relationship visuals for dashboards, and teams that need specific behavior often use custom charts. And if you need more control than defaults allow, D3.js is a common route for teams that want a reusable template, including Domo custom charts built with Phoenix.

Key takeaways for non-ribbon chord diagrams

Before diving deeper, here is what matters most when deciding whether this chart fits your situation:

• Use this chart when: You have 8 to 25 categories and your audience cares about who connects to whom, not how much flows between them.
• Avoid this chart when: Flow volume is the insight, or you have more than 25 categories.
• Primary decision it supports: Identifying which category pairs have relationships and which are isolated.
• Best alternative if this fails: A Sankey diagram for magnitude, or an adjacency matrix for dense networks.
• Data you need to have ready: A clean many-to-many relationship table (edge list) or adjacency matrix with consistent category names.

The biggest risk? Thin lines make all connections look equally important. Viewers may completely miss that some relationships are far stronger than others.

When to use a non-ribbon chord diagram

Fewer than eight categories and a simple network graph or even a table works better. More than 25 categories or 60 links? The circle becomes a tangle that stakeholders will dismiss as spaghetti.

The sweet spot sits between those boundaries. This chart earns its place when connection presence or relative frequency matters more than exact volume. When your audience needs a quick scan of who talks to whom. When you want isolated categories to stand out visually.

Executive readouts are where this comes up a lot. People are trying to answer questions like "which regions interact most with which product lines?" without sitting through a 10-minute explanation.

Certain scenarios make this chart a poor fit:

• Flow magnitude is the insight: Viewers assume all lines are equal and miss that one connection carries 80 percent of the volume.
• Directional flows matter: Non-ribbon lines are often undirected, so viewers may misread causality.
• Dense networks: More than 60 links and the chart renders but nobody can read it.

If you choose it anyway, expect stakeholders to ask for exact numbers.

Data requirements for a non-ribbon chord diagram

Before you think about arcs and colors, get the relational data into a shape the chart can trust.

Most builds start from one of these structures:

• Edge list (relationship table): Source, Target, and an optional Value column. This is the most common format for BI tools and D3.js charts.
• Adjacency matrix: A grid where rows and columns are categories and cells indicate a connection (and optionally a weight).

A few data details determine whether your chart reads cleanly or gets confusing:

• Many-to-many relationships: Non-ribbon chord diagrams assume categories can connect to multiple other categories. If your data is strictly one-to-many, an arc diagram or Sankey often reads more naturally.
• Directionality: If Source to Target isn't the same as Target to Source (for example, "requests submitted" vs "requests received"), keep both directions in your data so you can add arrowheads or directional styling.
• Consistency across dashboards: If the underlying categories or naming conventions change week to week, your diagram can drift. Governed datasets and reusable metrics help keep the relationships consistent when the data refreshes.
• Filtering and security (for embedded views): If you plan to publish this in an embedded portal, you need row-level security and programmatic filters so each person only sees the relationship network that applies to them.

If you're the data engineer or analytic engineer on the hook for this, the main work is usually transformation. Reshaping raw tables into a clean edge list without duplicate keys or mismatched labels. One mistake I see constantly: leaving inconsistent category names across Source and Target columns, which causes the chart to treat "Marketing" and "marketing" as separate nodes. SQL-based and no-code transformation steps (like Domo Magic ETL) are typically how teams standardize that relational layer so analysts don't have to rebuild the chart every time a source system changes.

Anatomy of a non-ribbon chord diagram

D3.js, R's circlize package, and BI platforms use slightly different defaults for spacing and labels. The core structure stays consistent.

These elements make up the standard chord plot:

• Arcs (nodes): Segments around the circle, each representing a category. Arc length may be uniform or proportional to total connections.
• Links (chords): Curved lines connecting arcs. In non-ribbon variants, these are strokes rather than filled shapes.
• Stroke width: Optionally encodes connection strength. If uniform, the chart shows presence only.
• Arrowheads: Optional. Indicate direction when relationships are asymmetric.
• Labels: Category names placed outside or inside the arcs.

In interactive BI dashboards (including Domo BI), tooltips and click-to-filter behavior do a lot of heavy lifting here. They give executives the "what exactly is this line?" answer without you stapling a table next to the chart.

How to read a non-ribbon chord diagram

Start with the outer circle. Look at the gaps first. Empty spaces on the perimeter tell you exactly who operates in a silo. Categories with no incoming or outgoing lines are isolated, and that isolation is often the actual insight.

Then trace the lines. Each curved line connects two categories. If the lines have varying thickness, thicker means stronger connection. If all lines look the same, the chart only shows whether a connection exists, not how strong it is.

Where interpretation fails: viewers naturally assume that more lines means more importance. But a category with many weak connections may matter less than one with a single critical link. It's something that's easily missed. The chart doesn't distinguish between these situations unless you encode weight through stroke width.

Presenting this to non-technical stakeholders? Interactive hints help. Tooltips that spell out "Source, Target, Value" in plain language, plus a short annotation calling out a key cluster, can turn a pretty circle into a decision.

Examples of non-ribbon chord diagrams

A company tracks which departments submit requests to other departments. The non-ribbon chord shows Engineering and Product with dense mutual connections, while Legal sits nearly isolated with only one link to Compliance. A bar chart of requests sent would show Legal's low volume but wouldn't reveal that the isolation is structural.

An analyst maps which geographic regions trade with each other based on presence, not volume. The chord diagram immediately highlights that Region C trades with all other regions while Region D only trades with Region A. A Sankey would emphasize volume and bury the topology insight.

A research team visualizes co-authorship patterns. The non-ribbon chord reveals clusters of frequent collaborators and identifies authors who bridge multiple clusters. A table of co-author counts would miss the cluster structure entirely.

A marketing operations team shows how customers move between channels for cross-channel attribution across touchpoints. The chord diagram highlights that social media is a dead end with no outbound connections, while email connects to every other channel. A funnel chart would force a linear sequence that doesn't actually exist.

This same "connections without the clutter" approach also shows up in supply chain dashboards (mapping interdependencies between suppliers and distribution centers, for example) and in embedded customer portals where each customer needs to see how data flows between their integrated systems.

How to create a non-ribbon chord diagram in Excel

Excel doesn't have a native chord diagram chart type. This requires a workaround using XY scatter plots with curved connectors. If you need to build these often, a BI tool or D3.js can be a better long-term option after the first build because the layout can be automated and reused.

1. Prepare source, target, and value columns

Structure your data as an edge list with three columns: Source, Target, and an optional Value. Each row represents one connection.

Sum the Value column and confirm it matches your expected total connections.

If your source data lives in multiple systems with inconsistent schemas, do the cleanup upstream. Data engineers often standardize category names, remove duplicates, and generate the edge list with SQL transformations (or a no-code flow) so the chart stays stable when the data refreshes.

2. Arrange categories around the circle

List unique categories and assign each an angle based on position. For n categories, each arc spans 360/n degrees. Calculate x and y coordinates using cos(angle) and sin(angle). Create a helper table with Category, Angle, X, and Y columns.

3. Map connections with lines

For each edge, look up the x and y coordinates of source and target. Use an XY Scatter chart and add each connection as a separate series with two points. Connect points with a smooth line.

Set line weight to 1 or 2 pt for uniform presence encoding. Remove all markers. Use low opacity (around 30 to 50 percent) if many lines overlap.

A frequent build error: forgetting to lock axis scales between -1.2 and 1.2. Without fixed ranges, the circle distorts into an oval when data changes.

This workaround becomes tedious past 10 categories or 20 links. Each link requires a separate data series. For ongoing dashboards, Domo BI can render an interactive non-ribbon chord diagram directly from a governed dataset, and teams that need custom behavior often use D3.js (including Domo Custom Charts built with Phoenix) so the chart logic is reusable instead of rebuilt every quarter.

Related charts for relationship data

So which chart type actually fits? The non-ribbon chord diagram is one option among several. Density, directionality, and whether magnitude matters will push you toward different answers.

• Sankey diagram: Use when flow volume is the primary insight. Switch to Sankey if stakeholders keep asking for exact numbers after seeing a chord diagram.
• Adjacency matrix: Use when you have more than 25 categories. The matrix scales better and avoids line overlap.
• Arc diagram: Use when you want a linear layout for sequential or hierarchical data.
• Network graph: Use when you need to show clusters, centrality, or path length.

You'll notice I didn't mention force-directed graphs. They can be useful for exploration, but they often raise readability questions in executive readouts.

Final thoughts on non-ribbon chord diagrams

This chart works when you need to show connection presence between a moderate number of categories. It shines when your audience cares about who connects to whom rather than how much volume moves between them.

Before building one, confirm your category count sits in the 8 to 25 range. Make sure your link count won't turn the chart into visual noise. If stakeholders will ask for exact numbers, switch to a Sankey or ribbon chord.

For teams building relationship visualizations regularly, consistency matters as much as the chart itself. Governed datasets and reusable metrics help keep the relational story straight across multiple dashboards, even when the data changes.

And if you need to deliver this outside your BI environment, embedding options matter too. Domo Embed (part of Domo Everywhere) supports embedding interactive dashboards, including relationship visuals like non-ribbon chord diagrams, with role-based access controls like row-level security, so each customer or partner sees the right network. If you're building a workflow experience, Domo Apps (built in App Studio) can place the chart inside a guided app so managers can explore connections and act.

Ready to turn your edge list into an interactive "who's connected to whom" view stakeholders can actually explore, without the Excel gymnastics? Join the Domo community to swap templates, get chart-build tips, and learn how other teams make chord diagrams dashboard-ready.