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Updated description and added yaml data for the data viewer

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README.md CHANGED
@@ -1,48 +1,473 @@
1
  ---
2
  license: cc-by-4.0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
3
  ---
4
  # CSTS - Correlation Structures in Time Series
5
 
6
  ## Important Notice
7
- This dataset is published as a pre-publication release. An accompanying research paper is forthcoming on arXiv. **All usage of this dataset must include proper attribution to the original authors as specified below.**
 
8
 
9
  ## Dataset Description
10
  CSTS (**C**orrelation **S**tructures in **T**ime **S**eries) is a comprehensive synthetic benchmarking dataset for
11
  evaluating correlation structure discovery in time series data. The dataset systematically models known correlation
12
  structures between three different time series variates and enables examination of how these structures are affected by
13
  distribution shifting, sparsification, and downsampling. With its controlled properties and ground truth labels,
14
- CSTS provides algorithm developers clean benchmark data that bridges the gap between theoretical models
15
  and messy real-world data.
16
 
17
  ### Key Applications
18
- - Evaluating the ability of time series clustering algorithms to segment and group by correlation structures
19
- - Assessing clustering validation methods for correlation-based clusters
20
- - Investigating how data preprocessing affects correlation structure discovery
21
- - Establishing performance thresholds for high-quality clustering result
22
 
23
  ### Dataset Structure
24
  CSTS provides **two main splits** (exploratory and confirmatory) with **30 subjects** each, enabling proper statistical validation.
25
  The dataset structure includes:
26
- - **12 data variants** across four generation stages × three completeness levels for each split
27
- - **Generation stages**: raw (unstructured), correlated (normal-distributed), non-normal distribution shifts, downsampled (1s→1min)
28
- - **Completeness levels**: complete (100%), partial (70%), sparse (10%) of observations retained
29
 
30
  ### Subjects
31
- Each subject contains 100 segments of varying lengths and each segment encodes one of the 23 specific correlation
32
- structures. Each subject uses all 23 patterns 4-5 times.
 
33
 
34
- For each subject, CSTS includes:
35
- - a time series **data file** with three variates
36
  - a **label file** specifying the ground truth segmentation and clustering
37
- - 67 **bad clustering label files** with controlled degradations (varying numbers of segmentations and/or cluster assignment mistakes) spanning the full Jaccard Index range [0,1]
38
 
39
  ### Additional Splits
40
- CSTS also includes versions (configured as splits) that allow exploration of how cluster and segment counts affect
41
- algorithm performance. They follow the same structure as above and are:
42
- - Reduced clusters (11 or 6 instead of 23)
43
- - Reduced segments (50 or 25 instead of 100)
 
44
 
45
- Our accompanying paper provides complete methodological details, baseline findings, and usage guidance.
 
 
 
 
46
 
47
  ## Authors
48
  - Isabella Degen, University of Bristol
@@ -50,7 +475,6 @@ Our accompanying paper provides complete methodological details, baseline findin
50
  - Henry W J Reeve, University of Nanjing
51
  - Kate Robson Brown, University College Dublin
52
 
53
-
54
  ## Pre-Publication Release Details
55
  - **Release Date:** 29 Apr 2024
56
  - **Version:** 1.0-pre
@@ -79,5 +503,5 @@ Please use the following temporary citation until our paper is published:
79
  Once our paper is published on arXiv, we will update this README with the proper citation information.
80
  **Please check back for updates.**
81
 
82
- ## Dataset Details
83
- ...coming soon
 
1
  ---
2
  license: cc-by-4.0
3
+ configs:
4
+ - config_name: raw_complete_data
5
+ data_files:
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+ - split: exploratory
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+ path: "exploratory/raw/*-data.parquet"
8
+ features: &id001
9
+ - name: subject_id
10
+ dtype: string
11
+ - name: datetime
12
+ dtype: string
13
+ type: timestamp
14
+ - name: iob
15
+ dtype: float32
16
+ - name: cob
17
+ dtype: float32
18
+ - name: ig
19
+ dtype: float32
20
+ - config_name: raw_complete_labels
21
+ data_files:
22
+ - split: exploratory
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+ path: "exploratory/raw/*-labels.parquet"
24
+ features: &id002
25
+ - name: subject_id
26
+ dtype: string
27
+ - name: id
28
+ dtype: int32
29
+ - name: start idx
30
+ dtype: int32
31
+ - name: end idx
32
+ dtype: int32
33
+ - name: length
34
+ dtype: int32
35
+ - name: cluster_id
36
+ dtype: int32
37
+ - name: correlation to model
38
+ dtype: string
39
+ - name: correlation achieved
40
+ dtype: string
41
+ - name: correlation achieved with tolerance
42
+ dtype: string
43
+ - name: MAE
44
+ dtype: float32
45
+ - name: relaxed MAE
46
+ dtype: float32
47
+ - config_name: raw_complete_badclustering_labels
48
+ data_files:
49
+ - split: exploratory
50
+ path: "exploratory/raw/bad_partitions/*-labels.parquet"
51
+ features: &id003
52
+ - name: subject_id
53
+ dtype: string
54
+ - name: cluster_desc
55
+ dtype: string
56
+ - name: id
57
+ dtype: int32
58
+ - name: start idx
59
+ dtype: int32
60
+ - name: end idx
61
+ dtype: int32
62
+ - name: length
63
+ dtype: int32
64
+ - name: cluster_id
65
+ dtype: int32
66
+ - name: correlation to model
67
+ dtype: string
68
+ - name: correlation achieved
69
+ dtype: string
70
+ - name: correlation achieved with tolerance
71
+ dtype: string
72
+ - name: MAE
73
+ dtype: float32
74
+ - name: relaxed MAE
75
+ dtype: float32
76
+ - config_name: raw_partial_data
77
+ data_files:
78
+ - split: exploratory
79
+ path: "exploratory/irregular_p30/raw/*-data.parquet"
80
+ features: *id001
81
+ - config_name: raw_partial_labels
82
+ data_files:
83
+ - split: exploratory
84
+ path: "exploratory/irregular_p30/raw/*-labels.parquet"
85
+ features: *id002
86
+ - config_name: raw_partial_badclustering_labels
87
+ data_files:
88
+ - split: exploratory
89
+ path: "exploratory/irregular_p30/raw/bad_partitions/*-labels.parquet"
90
+ features: *id003
91
+ - config_name: raw_sparse_data
92
+ data_files:
93
+ - split: exploratory
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+ path: "exploratory/irregular_p90/raw/*-data.parquet"
95
+ features: *id001
96
+ - config_name: raw_sparse_labels
97
+ data_files:
98
+ - split: exploratory
99
+ path: "exploratory/irregular_p90/raw/*-labels.parquet"
100
+ features: *id002
101
+ - config_name: raw_sparse_badclustering_labels
102
+ data_files:
103
+ - split: exploratory
104
+ path: "exploratory/irregular_p90/raw/bad_partitions/*-labels.parquet"
105
+ features: *id003
106
+ - config_name: correlated_complete_data
107
+ data_files:
108
+ - split: exploratory
109
+ path: "exploratory/normal/*-data.parquet"
110
+ features: *id001
111
+ - config_name: correlated_complete_labels
112
+ data_files:
113
+ - split: exploratory
114
+ path: "exploratory/normal/*-labels.parquet"
115
+ features: *id002
116
+ - config_name: correlated_complete_badclustering_labels
117
+ data_files:
118
+ - split: exploratory
119
+ path: "exploratory/normal/bad_partitions/*-labels.parquet"
120
+ features: *id003
121
+ - config_name: correlated_partial_data
122
+ data_files:
123
+ - split: exploratory
124
+ path: "exploratory/irregular_p30/normal/*-data.parquet"
125
+ features: *id001
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+ - config_name: correlated_partial_labels
127
+ data_files:
128
+ - split: exploratory
129
+ path: "exploratory/irregular_p30/normal/*-labels.parquet"
130
+ features: *id002
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+ - config_name: correlated_partial_badclustering_labels
132
+ data_files:
133
+ - split: exploratory
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+ path: "exploratory/irregular_p30/normal/bad_partitions/*-labels.parquet"
135
+ features: *id003
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+ - config_name: correlated_sparse_data
137
+ data_files:
138
+ - split: exploratory
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+ path: "exploratory/irregular_p90/normal/*-data.parquet"
140
+ features: *id001
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+ - config_name: correlated_sparse_labels
142
+ data_files:
143
+ - split: exploratory
144
+ path: "exploratory/irregular_p90/normal/*-labels.parquet"
145
+ features: *id002
146
+ - config_name: correlated_sparse_badclustering_labels
147
+ data_files:
148
+ - split: exploratory
149
+ path: "exploratory/irregular_p90/normal/bad_partitions/*-labels.parquet"
150
+ features: *id003
151
+ - config_name: nonnormal_complete_data
152
+ data_files:
153
+ - split: exploratory
154
+ path: "exploratory/non_normal/*-data.parquet"
155
+ features: *id001
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+ - config_name: nonnormal_complete_labels
157
+ data_files:
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+ - split: exploratory
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+ path: "exploratory/non_normal/*-labels.parquet"
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+ features: *id002
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+ - config_name: nonnormal_complete_badclustering_labels
162
+ data_files:
163
+ - split: exploratory
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+ path: "exploratory/non_normal/bad_partitions/*-labels.parquet"
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+ features: *id003
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+ - config_name: nonnormal_partial_data
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+ data_files:
168
+ - split: exploratory
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+ path: "exploratory/irregular_p30/non_normal/*-data.parquet"
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+ features: *id001
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+ - config_name: nonnormal_partial_labels
172
+ data_files:
173
+ - split: exploratory
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+ path: "exploratory/irregular_p30/non_normal/*-labels.parquet"
175
+ features: *id002
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+ - config_name: nonnormal_partial_badclustering_labels
177
+ data_files:
178
+ - split: exploratory
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+ path: "exploratory/irregular_p30/non_normal/bad_partitions/*-labels.parquet"
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+ features: *id003
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+ - config_name: nonnormal_sparse_data
182
+ data_files:
183
+ - split: exploratory
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+ path: "exploratory/irregular_p90/non_normal/*-data.parquet"
185
+ features: *id001
186
+ - config_name: nonnormal_sparse_labels
187
+ data_files:
188
+ - split: exploratory
189
+ path: "exploratory/irregular_p90/non_normal/*-labels.parquet"
190
+ features: *id002
191
+ - config_name: nonnormal_sparse_badclustering_labels
192
+ data_files:
193
+ - split: exploratory
194
+ path: "exploratory/irregular_p90/non_normal/bad_partitions/*-labels.parquet"
195
+ features: *id003
196
+ - config_name: downsampled_complete_data
197
+ data_files:
198
+ - split: exploratory
199
+ path: "exploratory/resampled_1min/*-data.parquet"
200
+ features: *id001
201
+ - config_name: downsampled_complete_labels
202
+ data_files:
203
+ - split: exploratory
204
+ path: "exploratory/resampled_1min/*-labels.parquet"
205
+ features: *id002
206
+ - config_name: downsampled_complete_badclustering_labels
207
+ data_files:
208
+ - split: exploratory
209
+ path: "exploratory/resampled_1min/bad_partitions/*-labels.parquet"
210
+ features: *id003
211
+ - config_name: downsampled_partial_data
212
+ data_files:
213
+ - split: exploratory
214
+ path: "exploratory/irregular_p30/resampled_1min/*-data.parquet"
215
+ features: *id001
216
+ - config_name: downsampled_partial_labels
217
+ data_files:
218
+ - split: exploratory
219
+ path: "exploratory/irregular_p30/resampled_1min/*-labels.parquet"
220
+ features: *id002
221
+ - config_name: downsampled_partial_badclustering_labels
222
+ data_files:
223
+ - split: exploratory
224
+ path: "exploratory/irregular_p30/resampled_1min/bad_partitions/*-labels.parquet"
225
+ features: *id003
226
+ - config_name: downsampled_sparse_data
227
+ data_files:
228
+ - split: exploratory
229
+ path: "exploratory/irregular_p90/resampled_1min/*-data.parquet"
230
+ features: *id001
231
+ - config_name: downsampled_sparse_labels
232
+ data_files:
233
+ - split: exploratory
234
+ path: "exploratory/irregular_p90/resampled_1min/*-labels.parquet"
235
+ features: *id002
236
+ - config_name: downsampled_sparse_badclustering_labels
237
+ data_files:
238
+ - split: exploratory
239
+ path: "exploratory/irregular_p90/resampled_1min/bad_partitions/*-labels.parquet"
240
+ features: *id003
241
+ - config_name: raw_complete_data
242
+ data_files:
243
+ - split: confirmatory
244
+ path: "confirmatory/raw/*-data.parquet"
245
+ features: *id001
246
+ - config_name: raw_complete_labels
247
+ data_files:
248
+ - split: confirmatory
249
+ path: "confirmatory/raw/*-labels.parquet"
250
+ features: *id002
251
+ - config_name: raw_complete_badclustering_labels
252
+ data_files:
253
+ - split: confirmatory
254
+ path: "confirmatory/raw/bad_partitions/*-labels.parquet"
255
+ features: *id003
256
+ - config_name: raw_partial_data
257
+ data_files:
258
+ - split: confirmatory
259
+ path: "confirmatory/irregular_p30/raw/*-data.parquet"
260
+ features: *id001
261
+ - config_name: raw_partial_labels
262
+ data_files:
263
+ - split: confirmatory
264
+ path: "confirmatory/irregular_p30/raw/*-labels.parquet"
265
+ features: *id002
266
+ - config_name: raw_partial_badclustering_labels
267
+ data_files:
268
+ - split: confirmatory
269
+ path: "confirmatory/irregular_p30/raw/bad_partitions/*-labels.parquet"
270
+ features: *id003
271
+ - config_name: raw_sparse_data
272
+ data_files:
273
+ - split: confirmatory
274
+ path: "confirmatory/irregular_p90/raw/*-data.parquet"
275
+ features: *id001
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+ - config_name: raw_sparse_labels
277
+ data_files:
278
+ - split: confirmatory
279
+ path: "confirmatory/irregular_p90/raw/*-labels.parquet"
280
+ features: *id002
281
+ - config_name: raw_sparse_badclustering_labels
282
+ data_files:
283
+ - split: confirmatory
284
+ path: "confirmatory/irregular_p90/raw/bad_partitions/*-labels.parquet"
285
+ features: *id003
286
+ - config_name: correlated_complete_data
287
+ data_files:
288
+ - split: confirmatory
289
+ path: "confirmatory/normal/*-data.parquet"
290
+ features: *id001
291
+ - config_name: correlated_complete_labels
292
+ data_files:
293
+ - split: confirmatory
294
+ path: "confirmatory/normal/*-labels.parquet"
295
+ features: *id002
296
+ - config_name: correlated_complete_badclustering_labels
297
+ data_files:
298
+ - split: confirmatory
299
+ path: "confirmatory/normal/bad_partitions/*-labels.parquet"
300
+ features: *id003
301
+ - config_name: correlated_partial_data
302
+ data_files:
303
+ - split: confirmatory
304
+ path: "confirmatory/irregular_p30/normal/*-data.parquet"
305
+ features: *id001
306
+ - config_name: correlated_partial_labels
307
+ data_files:
308
+ - split: confirmatory
309
+ path: "confirmatory/irregular_p30/normal/*-labels.parquet"
310
+ features: *id002
311
+ - config_name: correlated_partial_badclustering_labels
312
+ data_files:
313
+ - split: confirmatory
314
+ path: "confirmatory/irregular_p30/normal/bad_partitions/*-labels.parquet"
315
+ features: *id003
316
+ - config_name: correlated_sparse_data
317
+ data_files:
318
+ - split: confirmatory
319
+ path: "confirmatory/irregular_p90/normal/*-data.parquet"
320
+ features: *id001
321
+ - config_name: correlated_sparse_labels
322
+ data_files:
323
+ - split: confirmatory
324
+ path: "confirmatory/irregular_p90/normal/*-labels.parquet"
325
+ features: *id002
326
+ - config_name: correlated_sparse_badclustering_labels
327
+ data_files:
328
+ - split: confirmatory
329
+ path: "confirmatory/irregular_p90/normal/bad_partitions/*-labels.parquet"
330
+ features: *id003
331
+ - config_name: nonnormal_complete_data
332
+ data_files:
333
+ - split: confirmatory
334
+ path: "confirmatory/non_normal/*-data.parquet"
335
+ features: *id001
336
+ - config_name: nonnormal_complete_labels
337
+ data_files:
338
+ - split: confirmatory
339
+ path: "confirmatory/non_normal/*-labels.parquet"
340
+ features: *id002
341
+ - config_name: nonnormal_complete_badclustering_labels
342
+ data_files:
343
+ - split: confirmatory
344
+ path: "confirmatory/non_normal/bad_partitions/*-labels.parquet"
345
+ features: *id003
346
+ - config_name: nonnormal_partial_data
347
+ data_files:
348
+ - split: confirmatory
349
+ path: "confirmatory/irregular_p30/non_normal/*-data.parquet"
350
+ features: *id001
351
+ - config_name: nonnormal_partial_labels
352
+ data_files:
353
+ - split: confirmatory
354
+ path: "confirmatory/irregular_p30/non_normal/*-labels.parquet"
355
+ features: *id002
356
+ - config_name: nonnormal_partial_badclustering_labels
357
+ data_files:
358
+ - split: confirmatory
359
+ path: "confirmatory/irregular_p30/non_normal/bad_partitions/*-labels.parquet"
360
+ features: *id003
361
+ - config_name: nonnormal_sparse_data
362
+ data_files:
363
+ - split: confirmatory
364
+ path: "confirmatory/irregular_p90/non_normal/*-data.parquet"
365
+ features: *id001
366
+ - config_name: nonnormal_sparse_labels
367
+ data_files:
368
+ - split: confirmatory
369
+ path: "confirmatory/irregular_p90/non_normal/*-labels.parquet"
370
+ features: *id002
371
+ - config_name: nonnormal_sparse_badclustering_labels
372
+ data_files:
373
+ - split: confirmatory
374
+ path: "confirmatory/irregular_p90/non_normal/bad_partitions/*-labels.parquet"
375
+ features: *id003
376
+ - config_name: downsampled_complete_data
377
+ data_files:
378
+ - split: confirmatory
379
+ path: "confirmatory/resampled_1min/*-data.parquet"
380
+ features: *id001
381
+ - config_name: downsampled_complete_labels
382
+ data_files:
383
+ - split: confirmatory
384
+ path: "confirmatory/resampled_1min/*-labels.parquet"
385
+ features: *id002
386
+ - config_name: downsampled_complete_badclustering_labels
387
+ data_files:
388
+ - split: confirmatory
389
+ path: "confirmatory/resampled_1min/bad_partitions/*-labels.parquet"
390
+ features: *id003
391
+ - config_name: downsampled_partial_data
392
+ data_files:
393
+ - split: confirmatory
394
+ path: "confirmatory/irregular_p30/resampled_1min/*-data.parquet"
395
+ features: *id001
396
+ - config_name: downsampled_partial_labels
397
+ data_files:
398
+ - split: confirmatory
399
+ path: "confirmatory/irregular_p30/resampled_1min/*-labels.parquet"
400
+ features: *id002
401
+ - config_name: downsampled_partial_badclustering_labels
402
+ data_files:
403
+ - split: confirmatory
404
+ path: "confirmatory/irregular_p30/resampled_1min/bad_partitions/*-labels.parquet"
405
+ features: *id003
406
+ - config_name: downsampled_sparse_data
407
+ data_files:
408
+ - split: confirmatory
409
+ path: "confirmatory/irregular_p90/resampled_1min/*-data.parquet"
410
+ features: *id001
411
+ - config_name: downsampled_sparse_labels
412
+ data_files:
413
+ - split: confirmatory
414
+ path: "confirmatory/irregular_p90/resampled_1min/*-labels.parquet"
415
+ features: *id002
416
+ - config_name: downsampled_sparse_badclustering_labels
417
+ data_files:
418
+ - split: confirmatory
419
+ path: "confirmatory/irregular_p90/resampled_1min/bad_partitions/*-labels.parquet"
420
+ features: *id003
421
  ---
422
  # CSTS - Correlation Structures in Time Series
423
 
424
  ## Important Notice
425
+ This dataset is published as a pre-publication release. An accompanying research paper is forthcoming on arXiv.
426
+ **All usage of this dataset must include proper attribution to the original authors as specified below.**
427
 
428
  ## Dataset Description
429
  CSTS (**C**orrelation **S**tructures in **T**ime **S**eries) is a comprehensive synthetic benchmarking dataset for
430
  evaluating correlation structure discovery in time series data. The dataset systematically models known correlation
431
  structures between three different time series variates and enables examination of how these structures are affected by
432
  distribution shifting, sparsification, and downsampling. With its controlled properties and ground truth labels,
433
+ CSTS provides algorithm developers clean benchmark data that bridge the gap between theoretical models
434
  and messy real-world data.
435
 
436
  ### Key Applications
437
+ - Evaluating the ability of **time series clustering algorithms** to segment and group segments by correlation structures
438
+ - Assessing **clustering validation** methods for correlation-based clusters
439
+ - Investigating how **data preprocessing** affects correlation structure discovery
440
+ - Establishing **performance thresholds** for high-quality clustering result
441
 
442
  ### Dataset Structure
443
  CSTS provides **two main splits** (exploratory and confirmatory) with **30 subjects** each, enabling proper statistical validation.
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  The dataset structure includes:
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+ - **12 data variants**: 4 generation stages × 3 completeness levels for each split
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+ - **Generation stages**: raw (unstructured data), correlated (normal-distributed data), nonnormal (extreme value and negative binomial distribution shifts), downsampled (1s→1min)
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+ - **Completeness levels**: complete (100% of observations), partial (70% of observations), sparse (10% of observations)
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  ### Subjects
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+ Each subject contains 100 segments of varying lengths (900-36000) and each segment encodes one of the 23 specific correlation
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+ structures. Each subject uses all 23 patterns 4-5 times. For the complete data variants each subject consists of ~1.26 mio
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+ observations.
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+ Subjects each have the following information, accessible as subsets:
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+ - a time series **data file** with three variates (iob, cob, ig) and time stamps (datetime)
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  - a **label file** specifying the ground truth segmentation and clustering
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+ - 67 **bad clustering label files** with controlled degradations (varying numbers of segmentations and/or cluster assignment mistakes) spanning the entire Jaccard Index range [0,1]
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  ### Additional Splits
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+ CSTS also includes versions (configured as splits) that allow exploring how cluster and segment counts affect
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+ algorithm performance. They follow the same dataset structure (exploratory and confirmatory splits with each 12 data variants subset with each 3 information file subsets).
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+ These versions are:
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+ - Reduced cluster count: 11 or 6 instead of 23
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+ - Reduced segment count: 50 or 25 instead of 100
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+ Our accompanying paper provides complete methodological details, baseline findings, and usage guidance. Our
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+ GitHub codebase includes the generation, validation and use case code and is configured to automatically load the data.
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+
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+ ## Usage Guidance
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+ ... coming soon
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  ## Authors
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  - Isabella Degen, University of Bristol
 
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  - Henry W J Reeve, University of Nanjing
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  - Kate Robson Brown, University College Dublin
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  ## Pre-Publication Release Details
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  - **Release Date:** 29 Apr 2024
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  - **Version:** 1.0-pre
 
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  Once our paper is published on arXiv, we will update this README with the proper citation information.
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  **Please check back for updates.**
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+ ## Acknowledgements
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+ ... coming soon