Add dataset documentation

README.md

@@ -1,151 +1,65 @@
 ---
 language: en
-license: mit
-size_categories:
-- 100k<n<1M
-task_categories:
-- anomaly-detection
-pretty_name: HDFS Blocks Encoded and Tokenized with Train/Val/Test Splits
 tags:
 - log-analysis
 - hdfs
 - anomaly-detection
+license: mit
 ---
 
-# Dataset Card for HDFS Blocks Encoded and Tokenized with Train/Val/Test Splits
-
-<!-- Provide a quick summary of the dataset. -->
-
-
-
-## Dataset Details
-
-### Dataset Description
-
-<!-- Provide a longer summary of what this dataset is. -->
-
-
-
-- **Curated by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Language(s) (NLP):** en
-- **License:** mit
-
-### Dataset Sources [optional]
-
-<!-- Provide the basic links for the dataset. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-
-## Uses
-
-<!-- Address questions around how the dataset is intended to be used. -->
-
-### Direct Use
-
-<!-- This section describes suitable use cases for the dataset. -->
-
-[More Information Needed]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
-
-[More Information Needed]
-
-## Dataset Structure
-
-<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
-
-[More Information Needed]
-
-## Dataset Creation
-
-### Curation Rationale
-
-<!-- Motivation for the creation of this dataset. -->
-
-[More Information Needed]
-
-### Source Data
-
-<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
-
-#### Data Collection and Processing
-
-<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
-
-[More Information Needed]
-
-#### Who are the source data producers?
-
-<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
-
-[More Information Needed]
-
-### Annotations [optional]
-
-<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
-
-#### Annotation process
-
-<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
-
-[More Information Needed]
-
-#### Who are the annotators?
-
-<!-- This section describes the people or systems who created the annotations. -->
-
-[More Information Needed]
-
-#### Personal and Sensitive Information
-
-<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
-
-[More Information Needed]
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
-
-### Recommendations
-
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+# HDFS Logs Train/Val/Test Splits
 
-Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
+This dataset contains preprocessed HDFS log sequences split into train, validation, and test sets for anomaly detection tasks.
 
-## Citation [optional]
+## Dataset Description
 
-<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
+The dataset is derived from the HDFS log dataset, which contains system logs from a Hadoop Distributed File System (HDFS).
+Each sequence represents a block of log messages, labeled as either normal or anomalous. The dataset has been preprocessed
+using the Drain algorithm to extract structured fields and identify event types. 
 
-**BibTeX:**
+### Data Fields
 
-[More Information Needed]
+- `block_id`: Unique identifier for each HDFS block, used to group log messages into blocks
+- `event_encoded`: The preprocessed log sequence with event IDs and parameters
+- `tokenized_block`: The tokenized log sequence, used for training
+- `label`: Classification label ('Normal' or 'Anomaly')
 
-**APA:**
+### Data Splits
 
-[More Information Needed]
+- Training set: 460,049 sequences (80%)
+- Validation set: 57,506 sequences (10%)
+- Test set: 57,506 sequences (10%)
 
-## Glossary [optional]
+The splits are stratified by the Label field to maintain class distribution across splits.
 
-<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
+## Source Data
 
-[More Information Needed]
+Original data source: https://zenodo.org/records/8196385/files/HDFS_v1.zip?download=1
 
-## More Information [optional]
+## Preprocessing
 
-[More Information Needed]
+The logs have been preprocessed to:
+1. Extract structured fields (timestamp, component, etc.)
+2. Identify and standardize event types
+3. Remove block IDs from parameter lists to prevent data leakage
+4. Add special tokens for event type separation
 
-## Dataset Card Authors [optional]
+## Intended Uses
 
-[More Information Needed]
+This dataset is designed for:
+- Training log anomaly detection models
+- Evaluating log sequence prediction models
+- Benchmarking different approaches to log-based anomaly detection
 
-## Dataset Card Contact
+## Citation
 
-[More Information Needed]
+If you use this dataset, please cite the original HDFS paper:
+```bibtex
+@inproceedings{xu2009detecting,
+  title={Detecting large-scale system problems by mining console logs},
+  author={Xu, Wei and Huang, Ling and Fox, Armando and Patterson, David and Jordan, Michael I},
+  booktitle={Proceedings of the ACM SIGOPS 22nd symposium on Operating systems principles},
+  pages={117--132},
+  year={2009}
+}
+```