Upload folder using huggingface_hub

.gitattributes

@@ -59,3 +59,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 latentscope/lancedb/scopes-001.lance/_indices/1a8d05fe-515e-4d3a-ae46-277cc938ded5/index.idx filter=lfs diff=lfs merge=lfs -text
 latentscope/lancedb/scopes-001.lance/_indices/bcd0cafb-df81-4e68-a17b-3821960ee5b7/bitmap_page_lookup.lance filter=lfs diff=lfs merge=lfs -text
 latentscope/lancedb/scopes-001.lance/data/f3d6713e-0252-495a-a526-1cc2af10ca2a.lance filter=lfs diff=lfs merge=lfs -text
+latentscope/lancedb/scopes-001.lance/_indices/5ab6253c-5c48-42d3-b01f-8bfd2e4a7036/bitmap_page_lookup.lance filter=lfs diff=lfs merge=lfs -text
+latentscope/lancedb/scopes-001.lance/_indices/6dc61e99-9838-4f6f-aec4-fcf754edaa78/index.idx filter=lfs diff=lfs merge=lfs -text
+latentscope/lancedb/scopes-001.lance/data/eb9e671b-09f8-4e74-a329-911239aae35a.lance filter=lfs diff=lfs merge=lfs -text

latentscope/jobs/0030ae9d-d6f4-4b2e-b602-012d86125287.json

@@ -0,0 +1 @@
+{"id": "0030ae9d-d6f4-4b2e-b602-012d86125287", "dataset": "ls-datavis-misunderstood", "job_name": "upload-dataset", "command": "ls-upload-dataset \"/Users/enjalot/latent-scope-demo/ls-datavis-misunderstood\" \"ls-datavis-misunderstood\" --main-parquet=\"scopes/scopes-001-input.parquet\" --private=false", "status": "running", "last_update": "2025-03-28 15:07:41.152954", "progress": ["ARGS Namespace(directory='/Users/enjalot/latent-scope-demo/ls-datavis-misunderstood', dataset_name='ls-datavis-misunderstood', main_parquet='scopes/scopes-001-input.parquet', private='false', token=None)", "get key /Users/enjalot/code/latent-scope", "The token has not been saved to the git credentials helper. Pass `add_to_git_credential=True` in this function directly or `--add-to-git-credential` if using via `huggingface-cli` if you want to set the git credential as well.", "Token is valid (permission: write).", "Your token has been saved to /volumes/T9/huggingface/token", "Login successful", "USERNAME enjalot", "Creating repository: ls-datavis-misunderstood", "Repository created/verified: https://huggingface.co/datasets/enjalot/ls-datavis-misunderstood", "DIRECTORY /Users/enjalot/latent-scope-demo/ls-datavis-misunderstood"], "times": ["2025-03-28 15:07:40.506537", "2025-03-28 15:07:40.506781", "2025-03-28 15:07:40.506962", "2025-03-28 15:07:40.679936", "2025-03-28 15:07:40.683011", "2025-03-28 15:07:40.683473", "2025-03-28 15:07:40.726251", "2025-03-28 15:07:40.726688", "2025-03-28 15:07:41.151853", "2025-03-28 15:07:41.152941"]}

latentscope/jobs/02296371-a6ff-4f0b-8cd0-5e1738f3a3ad.json

@@ -0,0 +1 @@
+{"id": "02296371-a6ff-4f0b-8cd0-5e1738f3a3ad", "dataset": "ls-datavis-misunderstood", "job_name": "scope", "command": "ls-scope \"ls-datavis-misunderstood\" \"embedding-001\" \"umap-001\" \"cluster-001\" \"cluster-001-labels-010\" \"Data Visualization Misunderstood\" \"700 free responses from a survey about Data Visualization.\" --sae_id=sae-001 --scope_id=scopes-001", "status": "completed", "last_update": "2025-03-28 15:06:38.857268", "progress": ["Loading environment variables from: /Users/enjalot/code/latent-scope/.env", "DATA DIR /Users/enjalot/latent-scope-demo", "RUNNING: scopes-001", "umap columns Index(['x', 'y'], dtype='object')", "cluster columns Index(['cluster', 'raw_cluster', 'label'], dtype='object')", "scope_id scopes-001", "scope columns Index(['x', 'y', 'tile_index_64', 'tile_index_128', 'cluster', 'raw_cluster',", "'label', 'deleted', 'ls_index'],", "dtype='object')", "creating combined scope-input parquet", "exporting to lancedb", "Exporting scope scopes-001 to LanceDB database in /Users/enjalot/latent-scope-demo/ls-datavis-misunderstood", "Loading scope from /Users/enjalot/latent-scope-demo/ls-datavis-misunderstood/scopes", "Loading embeddings from /Users/enjalot/latent-scope-demo/ls-datavis-misunderstood/embeddings/embedding-001.h5", "Converting embeddings to numpy arrays (765, 768)", "SAE scope detected, adding metadata", "Existing table 'scopes-001' has been removed.", "Creating table 'scopes-001'", "Creating ANN index for embeddings on table 'scopes-001'", "Partitioning into 256 partitions, 48 sub-vectors", "[2025-03-28T19:06:38Z WARN  lance_linalg::kmeans] KMeans: more than 10% of clusters are empty: 33 of 256.", "Help: this could mean your dataset is too small to have a meaningful index (less than 5000 vectors) or has many duplicate vectors.", "[2025-03-28T19:06:38Z WARN  lance_linalg::kmeans] KMeans: more than 10% of clusters are empty: 32 of 256.", "Help: this could mean your dataset is too small to have a meaningful index (less than 5000 vectors) or has many duplicate vectors.", "[2025-03-28T19:06:38Z WARN  lance_linalg::kmeans] KMeans: more than 10% of clusters are empty: 28 of 256.", "Help: this could mean your dataset is too small to have a meaningful index (less than 5000 vectors) or has many duplicate vectors.", "[2025-03-28T19:06:38Z WARN  lance_linalg::kmeans] KMeans: more than 10% of clusters are empty: 32 of 256.", "Help: this could mean your dataset is too small to have a meaningful index (less than 5000 vectors) or has many duplicate vectors.", "[2025-03-28T19:06:38Z WARN  lance_linalg::kmeans] KMeans: more than 10% of clusters are empty: 29 of 256.", "Help: this could mean your dataset is too small to have a meaningful index (less than 5000 vectors) or has many duplicate vectors.", "[2025-03-28T19:06:38Z WARN  lance_linalg::kmeans] KMeans: more than 10% of clusters are empty: 27 of 256.", "Help: this could mean your dataset is too small to have a meaningful index (less than 5000 vectors) or has many duplicate vectors.", "[2025-03-28T19:06:38Z WARN  lance_linalg::kmeans] KMeans: more than 10% of clusters are empty: 33 of 256.", "Help: this could mean your dataset is too small to have a meaningful index (less than 5000 vectors) or has many duplicate vectors.", "[2025-03-28T19:06:38Z WARN  lance_linalg::kmeans] KMeans: more than 10% of clusters are empty: 26 of 256.", "Help: this could mean your dataset is too small to have a meaningful index (less than 5000 vectors) or has many duplicate vectors.", "[2025-03-28T19:06:38Z WARN  lance_linalg::kmeans] KMeans: more than 10% of clusters are empty: 32 of 256.", "Help: this could mean your dataset is too small to have a meaningful index (less than 5000 vectors) or has many duplicate vectors.", "[2025-03-28T19:06:38Z WARN  lance_linalg::kmeans] KMeans: more than 10% of clusters are empty: 26 of 256.", "Help: this could mean your dataset is too small to have a meaningful index (less than 5000 vectors) or has many duplicate vectors.", "[2025-03-28T19:06:38Z WARN  lance_linalg::kmeans] KMeans: more than 10% of clusters are empty: 28 of 256.", "Help: this could mean your dataset is too small to have a meaningful index (less than 5000 vectors) or has many duplicate vectors.", "[2025-03-28T19:06:38Z WARN  lance_linalg::kmeans] KMeans: more than 10% of clusters are empty: 29 of 256.", "Help: this could mean your dataset is too small to have a meaningful index (less than 5000 vectors) or has many duplicate vectors.", "[2025-03-28T19:06:38Z WARN  lance_linalg::kmeans] KMeans: more than 10% of clusters are empty: 29 of 256.", "Help: this could mean your dataset is too small to have a meaningful index (less than 5000 vectors) or has many duplicate vectors.", "[2025-03-28T19:06:38Z WARN  lance_linalg::kmeans] KMeans: more than 10% of clusters are empty: 26 of 256.", "Help: this could mean your dataset is too small to have a meaningful index (less than 5000 vectors) or has many duplicate vectors.", "[2025-03-28T19:06:38Z WARN  lance_linalg::kmeans] KMeans: more than 10% of clusters are empty: 27 of 256.", "Help: this could mean your dataset is too small to have a meaningful index (less than 5000 vectors) or has many duplicate vectors.", "[2025-03-28T19:06:38Z WARN  lance_linalg::kmeans] KMeans: more than 10% of clusters are empty: 29 of 256.", "Help: this could mean your dataset is too small to have a meaningful index (less than 5000 vectors) or has many duplicate vectors.", "[2025-03-28T19:06:38Z WARN  lance_linalg::kmeans] KMeans: more than 10% of clusters are empty: 29 of 256.", "Help: this could mean your dataset is too small to have a meaningful index (less than 5000 vectors) or has many duplicate vectors.", "[2025-03-28T19:06:38Z WARN  lance_linalg::kmeans] KMeans: more than 10% of clusters are empty: 31 of 256.", "Help: this could mean your dataset is too small to have a meaningful index (less than 5000 vectors) or has many duplicate vectors.", "[2025-03-28T19:06:38Z WARN  lance_linalg::kmeans] KMeans: more than 10% of clusters are empty: 27 of 256.", "Help: this could mean your dataset is too small to have a meaningful index (less than 5000 vectors) or has many duplicate vectors.", "[2025-03-28T19:06:38Z WARN  lance_linalg::kmeans] KMeans: more than 10% of clusters are empty: 30 of 256.", "Help: this could mean your dataset is too small to have a meaningful index (less than 5000 vectors) or has many duplicate vectors.", "[2025-03-28T19:06:38Z WARN  lance_linalg::kmeans] KMeans: more than 10% of clusters are empty: 26 of 256.", "Help: this could mean your dataset is too small to have a meaningful index (less than 5000 vectors) or has many duplicate vectors.", "[2025-03-28T19:06:38Z WARN  lance_linalg::kmeans] KMeans: more than 10% of clusters are empty: 30 of 256.", "Help: this could mean your dataset is too small to have a meaningful index (less than 5000 vectors) or has many duplicate vectors.", "[2025-03-28T19:06:38Z WARN  lance_linalg::kmeans] KMeans: more than 10% of clusters are empty: 28 of 256.", "Help: this could mean your dataset is too small to have a meaningful index (less than 5000 vectors) or has many duplicate vectors.", "[2025-03-28T19:06:38Z WARN  lance_linalg::kmeans] KMeans: more than 10% of clusters are empty: 30 of 256.", "Help: this could mean your dataset is too small to have a meaningful index (less than 5000 vectors) or has many duplicate vectors.", "[2025-03-28T19:06:38Z WARN  lance_linalg::kmeans] KMeans: more than 10% of clusters are empty: 27 of 256.", "Help: this could mean your dataset is too small to have a meaningful index (less than 5000 vectors) or has many duplicate vectors.", "[2025-03-28T19:06:38Z WARN  lance_linalg::kmeans] KMeans: more than 10% of clusters are empty: 33 of 256.", "Help: this could mean your dataset is too small to have a meaningful index (less than 5000 vectors) or has many duplicate vectors.", "Creating index for cluster on table 'scopes-001'", "Creating index for sae_indices on table 'scopes-001'", "Table 'scopes-001' created successfully", "wrote scope scopes-001"], "times": ["2025-03-28 15:06:38.100871", "2025-03-28 15:06:38.101444", "2025-03-28 15:06:38.101590", "2025-03-28 15:06:38.390826", "2025-03-28 15:06:38.403362", "2025-03-28 15:06:38.403532", "2025-03-28 15:06:38.403883", "2025-03-28 15:06:38.404004", "2025-03-28 15:06:38.404099", "2025-03-28 15:06:38.405579", "2025-03-28 15:06:38.409300", "2025-03-28 15:06:38.666785", "2025-03-28 15:06:38.666978", "2025-03-28 15:06:38.668410", "2025-03-28 15:06:38.675352", "2025-03-28 15:06:38.681707", "2025-03-28 15:06:38.689294", "2025-03-28 15:06:38.689427", "2025-03-28 15:06:38.727353", "2025-03-28 15:06:38.727857", "2025-03-28 15:06:38.770060", "2025-03-28 15:06:38.770238", "2025-03-28 15:06:38.770331", "2025-03-28 15:06:38.780033", "2025-03-28 15:06:38.780525", "2025-03-28 15:06:38.780629", "2025-03-28 15:06:38.780711", "2025-03-28 15:06:38.787334", "2025-03-28 15:06:38.787542", "2025-03-28 15:06:38.787649", 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"2025-03-28 15:06:38.792941", "2025-03-28 15:06:38.793067", "2025-03-28 15:06:38.793184", "2025-03-28 15:06:38.793297", "2025-03-28 15:06:38.793411", "2025-03-28 15:06:38.793530", "2025-03-28 15:06:38.794149", "2025-03-28 15:06:38.794280", "2025-03-28 15:06:38.794400", "2025-03-28 15:06:38.843223", "2025-03-28 15:06:38.847767", "2025-03-28 15:06:38.856256", "2025-03-28 15:06:38.857266"], "run_id": "scopes-001"}

latentscope/jobs/98dc1b33-3a82-4184-b9e2-178a20c13921.json

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+{"id": "98dc1b33-3a82-4184-b9e2-178a20c13921", "dataset": "ls-datavis-misunderstood", "job_name": "download-dataset", "command": "ls-download-dataset \"enjalot/ls-datavis-misunderstood\" \"ls-datavis-misunderstood\" \"/Users/enjalot/latent-scope-demo\"", "status": "completed", "last_update": "2025-03-28 15:05:25.202958", "progress": ["get key /Users/enjalot/code/latent-scope", "Warning: directory /Users/enjalot/latent-scope-demo/ls-datavis-misunderstood already exists", "/Users/enjalot/code/latent-scope/testenv/lib/python3.12/site-packages/huggingface_hub/file_download.py:1212: UserWarning: `local_dir_use_symlinks` parameter is deprecated and will be ignored. The process to download files to a local folder has been updated and do not rely on symlinks anymore. You only need to pass a destination folder as`local_dir`.", "For more details, check out https://huggingface.co/docs/huggingface_hub/main/en/guides/download#download-files-to-local-folder.", "warnings.warn(", "", "Fetching 185 files:   0%|          | 0/185 [00:00<?, ?it/s]", "Fetching 185 files:   1%|          | 1/185 [00:00<00:35,  5.15it/s]", "Fetching 185 files:   3%|\u258e         | 5/185 [00:00<00:10, 16.79it/s]", "Fetching 185 files:   4%|\u258d         | 7/185 [00:00<00:18,  9.67it/s]", "Fetching 185 files:  14%|\u2588\u258d        | 26/185 [00:01<00:06, 26.25it/s]", "Fetching 185 files:  23%|\u2588\u2588\u258e       | 43/185 [00:01<00:04, 34.17it/s]", "Fetching 185 files:  25%|\u2588\u2588\u258c       | 47/185 [00:02<00:05, 23.06it/s]", "Fetching 185 files:  36%|\u2588\u2588\u2588\u258c      | 66/185 [00:02<00:03, 35.65it/s]", "Fetching 185 files:  49%|\u2588\u2588\u2588\u2588\u258a     | 90/185 [00:02<00:02, 39.60it/s]", "Fetching 185 files:  51%|\u2588\u2588\u2588\u2588\u2588\u258f    | 95/185 [00:03<00:03, 29.67it/s]", "Fetching 185 files:  69%|\u2588\u2588\u2588\u2588\u2588\u2588\u258a   | 127/185 [00:03<00:01, 54.36it/s]", "Fetching 185 files:  74%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258e  | 136/185 [00:03<00:01, 44.97it/s]", "Fetching 185 files:  83%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258e | 154/185 [00:04<00:00, 49.83it/s]", "Fetching 185 files:  89%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258a | 164/185 [00:04<00:00, 45.53it/s]", "Fetching 185 files:  94%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258d| 174/185 [00:04<00:00, 51.41it/s]", "Fetching 185 files:  99%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2589| 184/185 [00:04<00:00, 56.65it/s]", "Fetching 185 files: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 185/185 [00:04<00:00, 39.80it/s]", "Successfully downloaded latentscope files to: /Users/enjalot/latent-scope-demo/ls-datavis-misunderstood"], "times": ["2025-03-28 15:05:20.074602", "2025-03-28 15:05:20.075231", "2025-03-28 15:05:20.502918", "2025-03-28 15:05:20.503118", "2025-03-28 15:05:20.503319", "2025-03-28 15:05:20.505610", "2025-03-28 15:05:20.700007", "2025-03-28 15:05:20.844096", "2025-03-28 15:05:21.195081", "2025-03-28 15:05:21.677322", "2025-03-28 15:05:22.034212", "2025-03-28 15:05:22.532665", "2025-03-28 15:05:22.775788", "2025-03-28 15:05:23.307541", "2025-03-28 15:05:23.775293", "2025-03-28 15:05:23.931075", "2025-03-28 15:05:24.293185", "2025-03-28 15:05:24.576686", "2025-03-28 15:05:24.867892", "2025-03-28 15:05:24.978370", "2025-03-28 15:05:25.100434", "2025-03-28 15:05:25.154005", "2025-03-28 15:05:25.154468", "2025-03-28 15:05:25.202948"]}

latentscope/lancedb/scopes-001.lance/_indices/5ab6253c-5c48-42d3-b01f-8bfd2e4a7036/bitmap_page_lookup.lance

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latentscope/lancedb/scopes-001.lance/_indices/6dc61e99-9838-4f6f-aec4-fcf754edaa78/index.idx

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latentscope/scopes/scopes-001-input.parquet

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latentscope/scopes/scopes-001.json

@@ -4,7 +4,7 @@
   "embedding_id": "embedding-001",
   "umap_id": "umap-001",
   "cluster_id": "cluster-001",
-  "cluster_labels_id": "cluster-001-labels-001",
+  "cluster_labels_id": "cluster-001-labels-010",
   "label": "Data Visualization Misunderstood",
   "description": "700 free responses from a survey about Data Visualization.",
   "sae_id": "sae-001",
@@ -77,21 +77,17 @@
     "n_noise": 120
   },
   "cluster_labels": {
-    "id": "cluster-001-labels-001",
+    "id": "cluster-001-labels-010",
     "cluster_id": "cluster-001",
-    "model_id": "nltk-top-words",
+    "model_id": "openai-gpt-4o-mini",
     "text_column": "answer",
     "samples": 10,
     "context": "",
-    "system_prompt": {
-      "role": "system",
-      "content": "You're job is to summarize lists of items with a short label of no more than 4 words. The items are part of a cluster and the label will be used to distinguish this cluster from others, so pay attention to what makes this group of similar items distinct.\n\nThe user will submit a list of items in the format:\n<ListItem>...</ListItem>\n<ListItem>...</ListItem>\n...\n\nYou should choose a label that best summarizes the theme of the list so that someone browsing the labels will have a good idea of what is in the list. \nDo not use punctuation, Do not explain yourself, respond with only a few words that summarize the list."
-    },
-    "max_tokens": 127818
+    "max_tokens": -1
   },
   "cluster_labels_lookup": [
     {
-      "label": "dataviz data Dataviz",
+      "label": "Challenges in Data Visualization",
       "description": "This is cluster 0 with 18 items.",
       "hull": [
         739,
@@ -103,7 +99,7 @@
       "cluster": 0
     },
     {
-      "label": "dashboard takes time",
+      "label": "Dashboard Design Challenges",
       "description": "This is cluster 1 with 17 items.",
       "hull": [
         230,
@@ -116,7 +112,7 @@
       "cluster": 1
     },
     {
-      "label": "question good Question",
+      "label": "Question Quality Concerns",
       "description": "This is cluster 2 with 6 items.",
       "hull": [
         656,
@@ -128,7 +124,7 @@
       "cluster": 2
     },
     {
-      "label": "data time much",
+      "label": "Data Cleaning Challenges",
       "description": "This is cluster 3 with 16 items.",
       "hull": [
         710,
@@ -142,7 +138,7 @@
       "cluster": 3
     },
     {
-      "label": "Nothing thing unprofetional",
+      "label": "Emphasis on Simplicity",
       "description": "This is cluster 4 with 11 items.",
       "hull": [
         668,
@@ -156,7 +152,7 @@
       "cluster": 4
     },
     {
-      "label": "Na None normally",
+      "label": "Response Confusion",
       "description": "This is cluster 5 with 22 items.",
       "hull": [
         352,
@@ -170,7 +166,7 @@
       "cluster": 5
     },
     {
-      "label": "viz time takes",
+      "label": "Time and Effort in Visualization",
       "description": "This is cluster 6 with 16 items.",
       "hull": [
         444,
@@ -183,7 +179,7 @@
       "cluster": 6
     },
     {
-      "label": "magic takes requires",
+      "label": "Not Magic Requires Effort",
       "description": "This is cluster 7 with 5 items.",
       "hull": [
         155,
@@ -194,7 +190,7 @@
       "cluster": 7
     },
     {
-      "label": "data viz Data",
+      "label": "Data Visualization Challenges",
       "description": "This is cluster 8 with 13 items.",
       "hull": [
         468,
@@ -205,7 +201,7 @@
       "cluster": 8
     },
     {
-      "label": "data viz important",
+      "label": "Perceptions of Data Visualization",
       "description": "This is cluster 9 with 9 items.",
       "hull": [
         202,
@@ -219,7 +215,7 @@
       "cluster": 9
     },
     {
-      "label": "data viz takes",
+      "label": "Time Investment in Data Viz",
       "description": "This is cluster 10 with 5 items.",
       "hull": [
         153,
@@ -231,7 +227,7 @@
       "cluster": 10
     },
     {
-      "label": "data much work",
+      "label": "Data Challenges and Limitations",
       "description": "This is cluster 11 with 8 items.",
       "hull": [
         251,
@@ -243,7 +239,7 @@
       "cluster": 11
     },
     {
-      "label": "data time Data",
+      "label": "Data Preparation Challenges",
       "description": "This is cluster 12 with 6 items.",
       "hull": [
         151,
@@ -254,7 +250,7 @@
       "cluster": 12
     },
     {
-      "label": "data effort time",
+      "label": "Data Preparation Efforts",
       "description": "This is cluster 13 with 6 items.",
       "hull": [
         590,
@@ -265,7 +261,7 @@
       "cluster": 13
     },
     {
-      "label": "storytelling aspect importance",
+      "label": "Storytelling and Accessibility",
       "description": "This is cluster 14 with 7 items.",
       "hull": [
         58,
@@ -277,7 +273,7 @@
       "cluster": 14
     },
     {
-      "label": "easy much time",
+      "label": "Time and Effort Investment",
       "description": "This is cluster 15 with 5 items.",
       "hull": [
         250,
@@ -289,7 +285,7 @@
       "cluster": 15
     },
     {
-      "label": "takes much complexity",
+      "label": "Complexity and Time Constraints",
       "description": "This is cluster 16 with 10 items.",
       "hull": [
         356,
@@ -302,7 +298,7 @@
       "cluster": 16
     },
     {
-      "label": "required time expertise",
+      "label": "Skill and Effort Challenges",
       "description": "This is cluster 17 with 6 items.",
       "hull": [
         374,
@@ -315,7 +311,7 @@
       "cluster": 17
     },
     {
-      "label": "data literacy Data",
+      "label": "Data Literacy Challenges",
       "description": "This is cluster 18 with 7 items.",
       "hull": [
         341,
@@ -326,7 +322,7 @@
       "cluster": 18
     },
     {
-      "label": "limitations tools want",
+      "label": "Tool Limitations and Challenges",
       "description": "This is cluster 19 with 5 items.",
       "hull": [
         702,
@@ -336,7 +332,7 @@
       "cluster": 19
     },
     {
-      "label": "data Data tool",
+      "label": "Data Access and Tool Limitations",
       "description": "This is cluster 20 with 8 items.",
       "hull": [
         505,
@@ -348,7 +344,7 @@
       "cluster": 20
     },
     {
-      "label": "time something amount",
+      "label": "Time and Effort in Creation",
       "description": "This is cluster 21 with 6 items.",
       "hull": [
         8,
@@ -360,7 +356,7 @@
       "cluster": 21
     },
     {
-      "label": "time takes much",
+      "label": "Development Time Factors",
       "description": "This is cluster 22 with 5 items.",
       "hull": [
         127,
@@ -371,7 +367,7 @@
       "cluster": 22
     },
     {
-      "label": "time people important",
+      "label": "Time and Effort Investment",
       "description": "This is cluster 23 with 3 items.",
       "hull": [
         212,
@@ -381,7 +377,7 @@
       "cluster": 23
     },
     {
-      "label": "time create work",
+      "label": "Time and Effort Expectations",
       "description": "This is cluster 24 with 7 items.",
       "hull": [
         403,
@@ -393,7 +389,7 @@
       "cluster": 24
     },
     {
-      "label": "much time takes",
+      "label": "Visualization Development Time",
       "description": "This is cluster 25 with 15 items.",
       "hull": [
         424,
@@ -404,7 +400,7 @@
       "cluster": 25
     },
     {
-      "label": "time takes much",
+      "label": "Effort in Creation",
       "description": "This is cluster 26 with 6 items.",
       "hull": [
         667,
@@ -416,7 +412,7 @@
       "cluster": 26
     },
     {
-      "label": "time takes work",
+      "label": "Collaboration and Complexity",
       "description": "This is cluster 27 with 10 items.",
       "hull": [
         432,
@@ -428,7 +424,7 @@
       "cluster": 27
     },
     {
-      "label": "time takes lot",
+      "label": "Time-consuming Processes",
       "description": "This is cluster 28 with 5 items.",
       "hull": [
         713,
@@ -439,7 +435,7 @@
       "cluster": 28
     },
     {
-      "label": "time takes effort",
+      "label": "Time and Effort Challenges",
       "description": "This is cluster 29 with 46 items.",
       "hull": [
         384,
@@ -455,7 +451,7 @@
       "cluster": 29
     },
     {
-      "label": "data story tell",
+      "label": "data storytelling essentials",
       "description": "This is cluster 30 with 6 items.",
       "hull": [
         284,
@@ -466,7 +462,7 @@
       "cluster": 30
     },
     {
-      "label": "important importance details",
+      "label": "Importance of Understanding Details",
       "description": "This is cluster 31 with 16 items.",
       "hull": [
         690,
@@ -478,7 +474,7 @@
       "cluster": 31
     },
     {
-      "label": "audience important help",
+      "label": "Audience Communication Importance",
       "description": "This is cluster 32 with 12 items.",
       "hull": [
         509,
@@ -491,7 +487,7 @@
       "cluster": 32
     },
     {
-      "label": "Depth understanding bring",
+      "label": "Communication Challenges Insights",
       "description": "This is cluster 33 with 4 items.",
       "hull": [
         609,
@@ -501,7 +497,7 @@
       "cluster": 33
     },
     {
-      "label": "get part knowledge",
+      "label": "Client Understanding Challenges",
       "description": "This is cluster 34 with 16 items.",
       "hull": [
         666,
@@ -514,7 +510,7 @@
       "cluster": 34
     },
     {
-      "label": "think know see",
+      "label": "Lack of Understanding",
       "description": "This is cluster 35 with 15 items.",
       "hull": [
         365,
@@ -529,7 +525,7 @@
       "cluster": 35
     },
     {
-      "label": "data complexity prep",
+      "label": "Data Preparation Complexity",
       "description": "This is cluster 36 with 6 items.",
       "hull": [
         162,
@@ -540,7 +536,7 @@
       "cluster": 36
     },
     {
-      "label": "think aesthetics visualization",
+      "label": "Aesthetics vs Accuracy",
       "description": "This is cluster 37 with 6 items.",
       "hull": [
         443,
@@ -552,7 +548,7 @@
       "cluster": 37
     },
     {
-      "label": "data time visualization",
+      "label": "Data Preparation Challenges",
       "description": "This is cluster 38 with 9 items.",
       "hull": [
         3,
@@ -563,7 +559,7 @@
       "cluster": 38
     },
     {
-      "label": "design lack appreciation",
+      "label": "Design Misunderstandings and Resistance",
       "description": "This is cluster 39 with 3 items.",
       "hull": [
         672,
@@ -573,7 +569,7 @@
       "cluster": 39
     },
     {
-      "label": "work easy think",
+      "label": "Misconceptions About Effort",
       "description": "This is cluster 40 with 17 items.",
       "hull": [
         527,
@@ -587,7 +583,7 @@
       "cluster": 40
     },
     {
-      "label": "tool complex way",
+      "label": "Effective Communication Insights",
       "description": "This is cluster 41 with 6 items.",
       "hull": [
         329,
@@ -599,7 +595,7 @@
       "cluster": 41
     },
     {
-      "label": "value investment fairly",
+      "label": "Research Importance and Impact",
       "description": "This is cluster 42 with 14 items.",
       "hull": [
         142,
@@ -613,7 +609,7 @@
       "cluster": 42
     },
     {
-      "label": "Excel comfortable tables",
+      "label": "Excel Mindset Limitations",
       "description": "This is cluster 43 with 8 items.",
       "hull": [
         191,
@@ -625,7 +621,7 @@
       "cluster": 43
     },
     {
-      "label": "tables Many Think",
+      "label": "Table Preferences vs Visuals",
       "description": "This is cluster 44 with 4 items.",
       "hull": [
         646,
@@ -636,7 +632,7 @@
       "cluster": 44
     },
     {
-      "label": "think art generally",
+      "label": "Misconceptions about Minimalism",
       "description": "This is cluster 45 with 5 items.",
       "hull": [
         538,
@@ -647,7 +643,7 @@
       "cluster": 45
     },
     {
-      "label": "nice things part",
+      "label": "Creative Value Perception",
       "description": "This is cluster 46 with 11 items.",
       "hull": [
         408,
@@ -661,7 +657,7 @@
       "cluster": 46
     },
     {
-      "label": "chart types feel",
+      "label": "Chart Familiarity Issues",
       "description": "This is cluster 47 with 7 items.",
       "hull": [
         314,
@@ -672,7 +668,7 @@
       "cluster": 47
     },
     {
-      "label": "charts people chart",
+      "label": "Chart Communication Challenges",
       "description": "This is cluster 48 with 19 items.",
       "hull": [
         431,
@@ -686,7 +682,7 @@
       "cluster": 48
     },
     {
-      "label": "one understand simple",
+      "label": "Challenges of Simplification",
       "description": "This is cluster 49 with 10 items.",
       "hull": [
         292,
@@ -697,7 +693,7 @@
       "cluster": 49
     },
     {
-      "label": "ca assume anything",
+      "label": "Code Maintenance Concerns",
       "description": "This is cluster 50 with 4 items.",
       "hull": [
         402,
@@ -707,7 +703,7 @@
       "cluster": 50
     },
     {
-      "label": "people like complicated",
+      "label": "Human-Centric Understanding",
       "description": "This is cluster 51 with 5 items.",
       "hull": [
         410,
@@ -718,7 +714,7 @@
       "cluster": 51
     },
     {
-      "label": "information different require",
+      "label": "Visual Communication Misunderstandings",
       "description": "This is cluster 52 with 11 items.",
       "hull": [
         322,
@@ -732,7 +728,7 @@
       "cluster": 52
     },
     {
-      "label": "great chart Excel",
+      "label": "Visualization and Design Principles",
       "description": "This is cluster 53 with 4 items.",
       "hull": [
         358,
@@ -743,7 +739,7 @@
       "cluster": 53
     },
     {
-      "label": "data visualisation point",
+      "label": "Data Visualization Challenges",
       "description": "This is cluster 54 with 7 items.",
       "hull": [
         677,
@@ -754,7 +750,7 @@
       "cluster": 54
     },
     {
-      "label": "data visualization format",
+      "label": "Data Preparation Challenges",
       "description": "This is cluster 55 with 5 items.",
       "hull": [
         164,
@@ -765,7 +761,7 @@
       "cluster": 55
     },
     {
-      "label": "data much different",
+      "label": "Effort in Data Visualization",
       "description": "This is cluster 56 with 11 items.",
       "hull": [
         419,
@@ -778,7 +774,7 @@
       "cluster": 56
     },
     {
-      "label": "intuitive learning need",
+      "label": "Learning and Tool Efficiency",
       "description": "This is cluster 57 with 3 items.",
       "hull": [
         183,
@@ -788,7 +784,7 @@
       "cluster": 57
     },
     {
-      "label": "design good goes",
+      "label": "Value of Good Design",
       "description": "This is cluster 58 with 15 items.",
       "hull": [
         649,
@@ -803,7 +799,7 @@
       "cluster": 58
     },
     {
-      "label": "make design best",
+      "label": "Design Process and Expertise",
       "description": "This is cluster 59 with 10 items.",
       "hull": [
         482,
@@ -815,7 +811,7 @@
       "cluster": 59
     },
     {
-      "label": "data tool people",
+      "label": "Data Visualization Challenges",
       "description": "This is cluster 60 with 4 items.",
       "hull": [
         80,
@@ -826,7 +822,7 @@
       "cluster": 60
     },
     {
-      "label": "make people look",
+      "label": "Function over Aesthetics",
       "description": "This is cluster 61 with 7 items.",
       "hull": [
         701,
@@ -839,7 +835,7 @@
       "cluster": 61
     },
     {
-      "label": "design visualization get",
+      "label": "Data Visualization Design",
       "description": "This is cluster 62 with 34 items.",
       "hull": [
         136,
@@ -854,7 +850,7 @@
       "cluster": 62
     },
     {
-      "label": "data viz work",
+      "label": "Data Visualization Challenges",
       "description": "This is cluster 63 with 7 items.",
       "hull": [
         128,
@@ -864,7 +860,7 @@
       "cluster": 63
     },
     {
-      "label": "data understand decisions",
+      "label": "Data Understanding Gaps",
       "description": "This is cluster 64 with 12 items.",
       "hull": [
         82,
@@ -877,7 +873,7 @@
       "cluster": 64
     },
     {
-      "label": "data use understand",
+      "label": "Data-Driven Decision Making",
       "description": "This is cluster 65 with 8 items.",
       "hull": [
         306,
@@ -889,7 +885,7 @@
       "cluster": 65
     },
     {
-      "label": "data people work",
+      "label": "Data Communication Insights",
       "description": "This is cluster 66 with 15 items.",
       "hull": [
         598,
@@ -902,7 +898,7 @@
       "cluster": 66
     },
     {
-      "label": "data visualization visualizations",
+      "label": "Data Visualization Importance",
       "description": "This is cluster 67 with 14 items.",
       "hull": [
         347,
@@ -915,7 +911,7 @@
       "cluster": 67
     },
     {
-      "label": "data visualization ca",
+      "label": "Data Visualization Fundamentals",
       "description": "This is cluster 68 with 13 items.",
       "hull": [
         679,
@@ -928,7 +924,7 @@
       "cluster": 68
     },
     {
-      "label": "data make understand",
+      "label": "Data Visualization Challenges",
       "description": "This is cluster 69 with 10 items.",
       "hull": [
         687,
@@ -940,7 +936,7 @@
       "cluster": 69
     },
     {
-      "label": "data people visualization",
+      "label": "Importance of Data Visualization",
       "description": "This is cluster 70 with 63 items.",
       "hull": [
         56,
@@ -971,6 +967,6 @@
     "deleted",
     "ls_index"
   ],
-  "size": 29826,
-  "timestamp": "2025-02-24 10:18:37"
+  "size": 29880,
+  "timestamp": "2025-03-28 15:06:38"
 }

latentscope/scopes/scopes-001.parquet

@@ -1,3 +1,3 @@
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+oid sha256:bfb5f027d8239fb6514501b9e96806e749e0b93d3210ef06b6f6b34b5c06e1e2
+size 29880