Add overview.csv + dataset-viewer config

README.md

@@ -3,8 +3,16 @@ tags:
 - relbench
 - relational-deep-learning
 pretty_name: RelBench dbinfer datasets
+configs:
+- config_name: overview
+  data_files:
+  - split: databases
+    path: overview.csv
 ---
 
+> 📊 See [`overview.csv`](overview.csv) for a summary of every database — tables, rows, tasks by type, size, domain, license, and source.
+
+
 # RelBench dbinfer datasets
 
 This repository hosts the **dbinfer** family of relational datasets in the RelBench 3.0

overview.csv

@@ -0,0 +1,8 @@
+name,domain,description,num_tables,num_rows,num_tasks,tasks_binary_classification,tasks_multiclass_classification,size_gb,val_timestamp,test_timestamp,license,source_url
+dbinfer-amazon,E-commerce (reviews),"Amazon from the 4DBInfer benchmark: a large product-review dataset linking users, products and reviews, used for rating prediction and user purchase/churn prediction.",3,16073957,3,1,2,5.911,2016-01-03 00:00:00,2016-01-04 00:00:00,see 4DBInfer / original sources,https://github.com/awslabs/multi-table-benchmark
+dbinfer-avs,Retail (Acquire Valued Shoppers),"Acquire Valued Shoppers (AVS) from the 4DBInfer benchmark: a retail dataset of customer transaction histories and promotional offers, used to predict shopper behavior such as offer repeat purchases.",3,349815883,1,1,0,5.563,2013-07-30 00:00:00,2013-07-31 00:00:00,see 4DBInfer / original sources,https://github.com/awslabs/multi-table-benchmark
+dbinfer-diginetica,E-commerce (sessions),"Diginetica from the 4DBInfer benchmark: an e-commerce dataset of user browsing and purchasing sessions over a product catalog (CIKM Cup 2016), used for click-through-rate and purchase prediction.",8,96552556,2,1,1,0.458,2016-11-11 00:00:00,2016-11-12 00:00:00,see 4DBInfer / original sources,https://github.com/awslabs/multi-table-benchmark
+dbinfer-outbrain-small,News / ad clicks,"Outbrain (small) from the 4DBInfer benchmark: a content-recommendation dataset of document page views and promoted-content displays/clicks, used for click-through-rate prediction.",8,2170445,1,1,0,0.062,2016-09-03 00:00:00,2016-09-04 00:00:00,see 4DBInfer / original sources,https://github.com/awslabs/multi-table-benchmark
+dbinfer-retailrocket,E-commerce (sessions),"RetailRocket from the 4DBInfer benchmark: an e-commerce dataset of visitor events (views, add-to-cart, transactions) over an item catalog, used to predict conversion (whether a viewed item is later purchased).",5,23011215,1,1,0,0.49,2015-09-20 00:00:00,2015-09-21 00:00:00,see 4DBInfer / original sources,https://github.com/awslabs/multi-table-benchmark
+dbinfer-seznam,Search / advertising,"Seznam from the 4DBInfer benchmark: a digital-advertising dataset from the Seznam.cz search engine, containing client prepaid-account charges and transactions, used to predict account charging/prepayment behavior.",4,2688678,2,0,2,0.027,2015-10-03 00:00:00,2015-10-04 00:00:00,see 4DBInfer / original sources,https://github.com/awslabs/multi-table-benchmark
+dbinfer-stackexchange,Online Q&A,"StackExchange from the 4DBInfer benchmark: a community-Q&A dataset of users, posts, votes and badges, used to predict user churn and post upvotes.",9,6140680,2,2,0,1.038,2023-09-05 00:00:00,2023-09-06 00:00:00,see 4DBInfer / original sources,https://github.com/awslabs/multi-table-benchmark