Update README.md

README.md

@@ -53,29 +53,29 @@ size_categories:
 
 ## Dataset Description
 
-- **Homepage:** [International Urban Energy Exchange (UEX) Research Centre](https://www.polyu.edu.hk/iuex/)
-- **Repository:** [UEXdo/Public_Datasets](https://huggingface.co/datasets/UEXdo/Public_Datasets)
-- **Paper:** N/A
-- **Leaderboard:** N/A
-- **Point of Contact:** [UEX Research Centre](https://www.polyu.edu.hk/iuex/)
+- Homepage: [International Urban Energy Exchange (UEX) Research Centre](https://www.polyu.edu.hk/iuex/)
+- Repository: [UEXdo/Public_Datasets](https://huggingface.co/datasets/UEXdo/Public_Datasets)
+- Paper: N/A
+- Leaderboard: N/A
+- Point of Contact: [UEX Research Centre](https://www.polyu.edu.hk/iuex/)
 
 ### Dataset Summary
 
-The **UEX Open Datasets Database** is a curated collection of metadata for open datasets published in top-tier academic journals (*Nature*, *Science*, and *Cell* series) from 2020 to the present. It is maintained by the **International Urban Energy Exchange (UEX) Research Centre** at The Hong Kong Polytechnic University (PolyU).
+The UEX Open Datasets Database is a curated collection of metadata for open datasets published in top-tier academic journals (*Nature*, *Science*, and *Cell* series) from 2020 to the present. It is maintained by the International Urban Energy Exchange (UEX) Research Centre at The Hong Kong Polytechnic University (PolyU).
 
 The database is specifically designed to support research in urban energy and environmental challenges, accelerating the transition to urban carbon neutrality. It categorizes over 2,000 dataset records into four core research directions aligned with the UEX Centre's laboratories:
 
-1. 🌱 **CleanTech**: Novel Low/Zero Carbon Technologies
-2. ⚡ **FLEXERGY**: Demand Response & New Mobilities & Urban Planning
-3. 🤖 **DigiEnergy**: AI & Data Science for Urban Energy Systems
-4. 💹 **EnergiTrade**: Carbon Trading & New Business Models
+1. 🌱 CleanTech: Novel Low/Zero Carbon Technologies
+2. ⚡ FLEXERGY: Demand Response & New Mobilities & Urban Planning
+3. 🤖 DigiEnergy: AI & Data Science for Urban Energy Systems
+4. 💹 EnergiTrade: Carbon Trading & New Business Models
 
 ### Supported Tasks and Leaderboards
 
 This dataset is primarily intended for:
-- **Literature Review & Meta-Analysis**: Discovering high-quality open datasets in specific urban energy domains.
-- **Data Discovery**: Finding raw data for training machine learning models in energy forecasting, climate modeling, and materials science.
-- **Trend Analysis**: Analyzing research trends in carbon neutrality and urban energy systems across top-tier journals.
+- Literature Review & Meta-Analysis: Discovering high-quality open datasets in specific urban energy domains.
+- Data Discovery: Finding raw data for training machine learning models in energy forecasting, climate modeling, and materials science.
+- Trend Analysis: Analyzing research trends in carbon neutrality and urban energy systems across top-tier journals.
 
 ### Languages
 
@@ -89,13 +89,13 @@ A typical instance in the dataset represents a single academic paper that publis
 
 ```json
 {
-  "title": "UrbanEV: An Open Benchmark Dataset for Urban Electric Vehicle Charging",
+  "title": "UrbanEV: An Open Benchmark Dataset for Urban Electric Vehicle Charging Demand Prediction",
   "doi": "10.1038/s41597-025-04874-4",
   "url": "https://doi.org/10.1038/s41597-025-04874-4",
   "journal": "Scientific Data",
   "year": 2025,
-  "authors": "Smith, J.; Doe, A.",
-  "abstract": "We present UrbanEV, a comprehensive dataset of electric vehicle charging sessions...",
+  "authors": "Li, H.; Qu, H.; Tan, X.; You, L.;Zhu, R.; Fan, W.",
+  "abstract": "The recent surge in electric vehicles (EVs), driven by a collective push to enhance global environmental sustainability, has underscored the significance of exploring EV charging prediction....",
   "direction": "FLEXERGY",
   "subcategory": "Electric Vehicles & Mobility"
 }
@@ -127,13 +127,13 @@ The transition to carbon-neutral cities requires vast amounts of high-quality da
 
 #### Initial Data Collection and Normalization
 
-Data was collected programmatically using the **CrossRef API**. The collection process targeted specific ISSNs of 13 journals across three major publishers:
+Data was collected programmatically using the CrossRef API. The collection process targeted specific ISSNs of 13 journals across three major publishers:
 
-- **Nature Portfolio**: *Scientific Data*, *Nature Energy*, *Nature Sustainability*, *Nature Communications*, *Nature Climate Change*, *npj Clean Energy*, *Nature Cities*, *Scientific Reports*
-- **Cell Press**: *Joule*, *One Earth*, *Cell Reports Sustainability*, *iScience*
-- **AAAS**: *Science Advances*
+- Nature Portfolio: *Scientific Data*, *Nature Energy*, *Nature Sustainability*, *Nature Communications*, *Nature Climate Change*, *npj Clean Energy*, *Nature Cities*, *Scientific Reports*
+- Cell Press: *Joule*, *One Earth*, *Cell Reports Sustainability*, *iScience*
+- AAAS: *Science Advances*
 
-The search was restricted to publications from **2020 to the present** that contain keywords related to energy, carbon, climate, and urban systems.
+The search was restricted to publications from 2020 to the present that contain keywords related to energy, carbon, climate, and urban systems.
 
 #### Classification Methodology
 
@@ -155,19 +155,19 @@ By centralizing access to high-quality datasets on renewable energy, carbon trad
 
 ### Discussion of Biases
 
-- **Source Bias**: The dataset only includes papers from selected high-impact journals (Nature, Science, Cell series). It does not cover datasets published in specialized domain journals (e.g., IEEE, Elsevier energy journals) or standalone data repositories without an accompanying paper.
-- **Language Bias**: The search and classification rely entirely on English keywords, excluding datasets published in other languages.
-- **Classification Limitations**: The automated keyword-based classification may occasionally misclassify papers, especially those spanning multiple interdisciplinary domains.
+- Source Bias: The dataset only includes papers from selected high-impact journals (Nature, Science, Cell series). It does not cover datasets published in specialized domain journals (e.g., IEEE, Elsevier energy journals) or standalone data repositories without an accompanying paper.
+- Language Bias: The search and classification rely entirely on English keywords, excluding datasets published in other languages.
+- Classification Limitations: The automated keyword-based classification may occasionally misclassify papers, especially those spanning multiple interdisciplinary domains.
 
 ## Additional Information
 
 ### Dataset Curators
 
-This dataset was curated by the **International Urban Energy Exchange (UEX) Research Centre** at The Hong Kong Polytechnic University.
+This dataset was curated by the International Urban Energy Exchange (UEX) Research Centre at The Hong Kong Polytechnic University.
 
 ### Licensing Information
 
-The metadata in this repository is released under the **Creative Commons Attribution 4.0 International (CC BY 4.0)** license. 
+The metadata in this repository is released under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. 
 
 *Note: The actual datasets linked within this database are subject to their own respective licenses as defined by the original authors and publishers.*
 
@@ -176,10 +176,10 @@ The metadata in this repository is released under the **Creative Commons Attribu
 If you use this database in your research, please cite it as follows:
 
 ```bibtex
-@misc{uex_open_datasets_2024,
+@misc{uex_open_datasets_2026,
   title        = {{UEX Open Datasets Database: Curated Open Datasets for Urban Energy Research}},
-  author       = {{International Urban Energy Exchange Research Centre, PolyU}},
-  year         = {2024},
+  author       = {{International Centre of Urban Energy Nexus (UEX), PolyU}},
+  year         = {2026},
   howpublished = {\url{https://huggingface.co/datasets/UEXdo/Public_Datasets}},
   note         = {The Hong Kong Polytechnic University}
 }