diff --git a/examples/plots-plotly/.gitignore b/examples/plots-plotly/.gitignore
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index 00000000..9cb46da1
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+++ b/examples/plots-plotly/.gitignore
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+signac.rc
+signac_project_document.json
+workspace/
diff --git a/examples/plots-plotly/README.md b/examples/plots-plotly/README.md
new file mode 100644
index 00000000..2628537e
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+++ b/examples/plots-plotly/README.md
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+# Plotly Plots Example
+
+To run this example, call `python init.py` and then `python dashboard.py run`.
diff --git a/examples/plots-plotly/dashboard.py b/examples/plots-plotly/dashboard.py
new file mode 100755
index 00000000..b06ed2c8
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+++ b/examples/plots-plotly/dashboard.py
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+#!/usr/bin/env python3
+# Copyright (c) 2019 The Regents of the University of Michigan
+# All rights reserved.
+# This software is licensed under the BSD 3-Clause License.
+from scipy.signal import coherence
+
+from signac_dashboard import Dashboard
+from signac_dashboard.modules import PlotViewer, StatepointList, TextDisplay
+
+
+class PlotDashboard(Dashboard):
+    def job_sorter(self, job):
+        return job.sp.get("coherence_time", -1)
+
+    def job_title(self, job):
+        return f"Coherence time: {job.sp.coherence_time}"
+
+
+def correlation_text(job):
+    return "Correlation coefficient: {:.5f}".format(job.doc["correlation"])
+
+
+def plotly_args(job):
+    # Visualization adapted from:
+    # https://matplotlib.org/gallery/lines_bars_and_markers/cohere.html
+
+    # It's necessary to cast to list because the list elements of the job
+    # document are BufferedJSONAttrList, which is not serializable
+    signals_traces = [
+        {
+            "x": list(job.doc["t"]),
+            "y": list(job.doc["s1"]),
+            "name": "s1",
+        },
+        {
+            "x": list(job.doc["t"]),
+            "y": list(job.doc["s2"]),
+            "name": "s2",
+        },
+    ]
+    signals_layout = {
+        "xaxis": {
+            "title": "time",
+            "range": [0, 2],
+        },
+        "height": 200,
+        "margin": dict(t=30, b=40, l=40, r=0),
+    }
+
+    dt = job.doc["t"][1] - job.doc["t"][0]
+    coherence_x, coherence_y = coherence(
+        job.doc["s1"], job.doc["s2"], nfft=256, fs=1.0 / dt
+    )
+    coherence_traces = [
+        {
+            "x": coherence_x.tolist(),
+            "y": coherence_y.tolist(),
+        }
+    ]
+    coherence_layout = {
+        "title": f"Coherence time = {job.sp.coherence_time}",
+        "xaxis": {"title": "frequency"},
+        "yaxis": {"title": "coherence", "range": [0, 1]},
+        "height": 200,
+        "margin": dict(t=30, b=40, l=40, r=0),
+    }
+    return [
+        ("Signals", signals_traces, signals_layout),
+        ("Coherence", coherence_traces, coherence_layout),
+    ]
+
+
+if __name__ == "__main__":
+    modules = []
+    modules.append(StatepointList())
+    modules.append(PlotViewer(plotly_args=plotly_args))
+    modules.append(TextDisplay(name="Correlation", message=correlation_text))
+    PlotDashboard(modules=modules).main()
diff --git a/examples/plots-plotly/init.py b/examples/plots-plotly/init.py
new file mode 100755
index 00000000..1d1495e5
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+++ b/examples/plots-plotly/init.py
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+#!/usr/bin/env python3
+# Copyright (c) 2019 The Regents of the University of Michigan
+# All rights reserved.
+# This software is licensed under the BSD 3-Clause License.
+import numpy as np
+import signac
+
+project = signac.init_project("plots")
+
+
+def plot_coherence(job):
+    # Data generation adapted from:
+    # https://matplotlib.org/gallery/lines_bars_and_markers/cohere.html
+
+    print(f"Generating signals for coherence time {job.sp.coherence_time}, job {job}")
+    # Fixing random state for reproducibility
+    np.random.seed(job.sp.seed)
+
+    dt = 0.01
+    t = np.arange(0, 30, dt)
+    nse1 = np.random.randn(len(t))  # white noise 1
+    nse2 = np.random.randn(len(t))  # white noise 2
+
+    # Two signals with a coherent part and a random part
+    s1 = np.sin(2 * np.pi * job.sp.coherence_time * t) + nse1
+    s2 = np.sin(2 * np.pi * job.sp.coherence_time * t) + nse2
+
+    # Save the signal data
+    job.doc["t"] = t.tolist()
+    job.doc["s1"] = s1.tolist()
+    job.doc["s2"] = s2.tolist()
+
+    # Save correlation coefficient
+    job.doc["correlation"] = np.corrcoef(s1, s2)[0, 1]
+
+
+for i in range(30):
+    job = project.open_job({"coherence_time": i, "seed": 42})
+    job.init()
+    plot_coherence(job)