diff --git a/Upload_dataverse.ipynb b/Upload_dataverse.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..ad4d37fda7f87cc3137ab5bb456137ee3b3b7a91
--- /dev/null
+++ b/Upload_dataverse.ipynb
@@ -0,0 +1,263 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "ff1fd295",
+   "metadata": {},
+   "source": [
+    "### Script for upload data from LiMoNet"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 288,
+   "id": "5402e405",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'utf-8'"
+      ]
+     },
+     "execution_count": 288,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from dataverse import Connection\n",
+    "import numpy as np\n",
+    "import sys\n",
+    "import os\n",
+    "import dataverse\n",
+    "from lxml import etree\n",
+    "import json\n",
+    "import glob\n",
+    "\n",
+    "%matplotlib inline\n",
+    "sys.getdefaultencoding()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 289,
+   "id": "fbc872a5",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "env: API_TOKEN=0a1616ce-fbe8-44f7-955f-d095f1061617\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Token from repository\n",
+    "\n",
+    "%env API_TOKEN=0a1616ce-fbe8-44f7-955f-d095f1061617 "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 290,
+   "id": "bf5ecb80",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "API_TOKEN = os.environ['API_TOKEN']\n",
+    "host = 'dataverse.redclara.net'                  # All clients >4.0 are supported\n",
+    "# Conexión a repositorio\n",
+    "connection = Connection(host, API_TOKEN)\n",
+    "# Selección de dataverse a user\n",
+    "dataverse_id = connection.get_dataverse('limonet')  # Dataverse id"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 291,
+   "id": "9e50bd8b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Metadata\n",
+    "# https://docs.python.org/3/library/xml.etree.elementtree.html\n",
+    "# https://www.tutorialspoint.com/python3/python_xml_processing.htm\n",
+    "# https://lxml.de/2.0/parsing.html\n",
+    "# https://github.com/IQSS/dataverse-client-python\n",
+    "\n",
+    "description = 'This repository contains lightning data files recorded by LiMoNet at Bucaramanga, Colombia.'\n",
+    "creator = 'Peña, Jesús'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 292,
+   "id": "1bc2b3ec",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "OperationFailedError",
+     "evalue": "This dataset could not be added.",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mOperationFailedError\u001b[0m                      Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-292-6691b1c12b86>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# Create dataset\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mdataset_id\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdataverse\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mDataverse\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcreate_dataset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdataverse_id\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'LM_2021_04_05'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdescription\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcreator\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[0;32m~/src/dataverse/dataverse/dataverse.py\u001b[0m in \u001b[0;36mcreate_dataset\u001b[0;34m(self, title, description, creator, **kwargs)\u001b[0m\n\u001b[1;32m     98\u001b[0m         )\n\u001b[1;32m     99\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 100\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_add_dataset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdataset\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    101\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mdataset\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    102\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/src/dataverse/dataverse/dataverse.py\u001b[0m in \u001b[0;36m_add_dataset\u001b[0;34m(self, dataset)\u001b[0m\n\u001b[1;32m    111\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    112\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mresp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstatus_code\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;36m201\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 113\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mOperationFailedError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'This dataset could not be added.'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    114\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    115\u001b[0m         \u001b[0mdataset\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdataverse\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mOperationFailedError\u001b[0m: This dataset could not be added."
+     ]
+    }
+   ],
+   "source": [
+    "# Create dataset\n",
+    "\n",
+    "dataset_id = dataverse.Dataverse.create_dataset(dataverse_id, 'LM_2021_04_05', description, creator)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "527fd60d",
+   "metadata": {},
+   "source": [
+    "Los campos del archivo .json tienen palabras claves que se pueden encontrar aquí:\n",
+    "\n",
+    "https://guides.dataverse.org/en/4.18.1/_downloads/dataset-create-new-all-default-fields.json\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 273,
+   "id": "41773832",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Modify metadata fields: title and dates\n",
+    "\n",
+    "date = '2021-10-28'\n",
+    "title = 'LM_2021_04_01'\n",
+    "\n",
+    "with open(\"metadata_limonet.json\", 'r') as f:\n",
+    "    json_data = json.load(f)\n",
+    "    json_data['metadataBlocks']['citation']['fields'][3]['value'][0]['dsDescriptionDate']['value']= date\n",
+    "    json_data['metadataBlocks']['citation']['fields'][8]['value']= date\n",
+    "    json_data['metadataBlocks']['citation']['fields'][0]['value']= title\n",
+    "    \n",
+    "with open('metadata_limonet.json', 'w') as f:\n",
+    "    json.dump(json_data, f, indent = 2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 274,
+   "id": "398d4deb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "metadata_file = open(\"metadata_limonet.json\",)\n",
+    " \n",
+    "# returns JSON object as a dictionary\n",
+    "metadata = json.load(metadata_file)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 275,
+   "id": "84b4fd7e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Get metadata\n",
+    "dataset_id.update_metadata(metadata)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 280,
+   "id": "33845dfe",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Lightning/Lighting_2021_04_01_20_27.dat\n",
+      "Lightning/Lighting_2021_04_01_19_41.dat\n",
+      "Lightning/Lighting_2021_04_01_19_37.dat\n",
+      "Lightning/Lighting_2021_04_01_19_23.dat\n",
+      "Lightning/Lighting_2021_04_01_18_52.dat\n",
+      "Lightning/Lighting_2021_04_01_19_31.dat\n",
+      "Lightning/Lighting_2021_04_01_19_44.dat\n",
+      "Data uploaded\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Upload data\n",
+    "# ej: dataset_id.upload_filepath('Lightning/Lighting_2021_04_01_18_52.dat')\n",
+    "\n",
+    "files = glob.glob(\"Lightning/Lighting_2021_04_01*.dat\")\n",
+    "M = len(files)\n",
+    "\n",
+    "for i in range(M):\n",
+    "    \n",
+    "    print (files[i])\n",
+    "    dataset_id.upload_filepath(files[i])\n",
+    "    \n",
+    "print ('Data uploaded')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "891dfa50",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# tree = etree.parse(\"metadata_limonet.xml\")\n",
+    "# xslt_root = etree.parse(\"xml2json.xslt\")\n",
+    "# transform = etree.XSLT(xslt_root)\n",
+    "\n",
+    "# result = transform(tree)\n",
+    "# json_load = json.loads(str(result))\n",
+    "# json_dump = json.dumps(json_load, indent=2)\n",
+    "\n",
+    "# print(json_dump)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "68e76018",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# print file metadata\n",
+    "dataset_id.get_metadata()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Upload_dataverse_automatic.ipynb b/Upload_dataverse_automatic.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..c6cdc6946a8e814d0b52ab2bc57afeb21b6eea51
--- /dev/null
+++ b/Upload_dataverse_automatic.ipynb
@@ -0,0 +1,316 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "ff1fd295",
+   "metadata": {},
+   "source": [
+    "# Script for automatically uploading LiMoNet data to a Dataverse repository"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "750b30d8",
+   "metadata": {},
+   "source": [
+    "This script uploads data collected by the LiMoNet (Lightning Monitoring Network) to a Dataverse repository. The code firstly load the python packages needed for the connection to dataverse, load metadata from a **.json** file and search data files in a folder. We define some functions: **create_dataset**, **modify_metadata**, **load_metadata** and **upload_data**. For more information, some references are listed along the script.\n",
+    "\n",
+    "Author: J. Peña-Rodríguez\n",
+    "2021"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "5402e405",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'utf-8'"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from dataverse import Connection\n",
+    "import numpy as np\n",
+    "import sys\n",
+    "import os\n",
+    "import dataverse\n",
+    "from lxml import etree\n",
+    "import json\n",
+    "import glob\n",
+    "import datetime\n",
+    "\n",
+    "%matplotlib inline\n",
+    "sys.getdefaultencoding()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "de9b2c88",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def progressbar(it, prefix=\"\", size=60, file=sys.stdout):\n",
+    "    \n",
+    "    # Progress bar animation\n",
+    "    count = len(it)\n",
+    "    def show(j):\n",
+    "        x = int(size*j/count)\n",
+    "        file.write(\"%s[%s%s] %i/%i\\r\" % (prefix, \"#\"*x, \".\"*(size-x), j, count))\n",
+    "        file.flush()        \n",
+    "    show(0)\n",
+    "    for i, item in enumerate(it):\n",
+    "        yield item\n",
+    "        show(i+1)\n",
+    "    file.write(\"\\n\")\n",
+    "    file.flush()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "9e50bd8b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def create_dataset(dataset_name):\n",
+    "    \n",
+    "    # Metadata\n",
+    "    # https://docs.python.org/3/library/xml.etree.elementtree.html\n",
+    "    # https://www.tutorialspoint.com/python3/python_xml_processing.htm\n",
+    "    # https://lxml.de/2.0/parsing.html\n",
+    "    # https://github.com/IQSS/dataverse-client-python\n",
+    "\n",
+    "    description = 'This repository contains lightning data files recorded by LiMoNet at Bucaramanga, Colombia.'\n",
+    "    creator = 'Peña, Jesús'\n",
+    "    \n",
+    "    # Create dataset\n",
+    "\n",
+    "    dataset_id = dataverse.Dataverse.create_dataset(dataverse_id, dataset_name, description, creator)\n",
+    "    return dataset_id"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5c527720",
+   "metadata": {},
+   "source": [
+    "Los campos del archivo .json tienen palabras claves que se pueden encontrar aquí:\n",
+    "\n",
+    "https://guides.dataverse.org/en/4.18.1/_downloads/dataset-create-new-all-default-fields.json\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "83d72718",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def modify_metadata(dataset_name, date):\n",
+    "    \n",
+    "    # Modify the metadata file metadata_limonet.json\n",
+    "    # Modified metadata fields: title and dates\n",
+    "    # All the fields can be midified depending on your necessity\n",
+    "\n",
+    "    date = date\n",
+    "    title = dataset_name\n",
+    "\n",
+    "    with open(\"metadata_limonet.json\", 'r') as f:\n",
+    "        json_data = json.load(f)\n",
+    "        json_data['metadataBlocks']['citation']['fields'][3]['value'][0]['dsDescriptionDate']['value']= date\n",
+    "        json_data['metadataBlocks']['citation']['fields'][8]['value']= date\n",
+    "        json_data['metadataBlocks']['citation']['fields'][0]['value']= title\n",
+    "\n",
+    "    with open('metadata_limonet.json', 'w') as f:\n",
+    "        json.dump(json_data, f, indent = 2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "98f30841",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def load_metadata(dataset_id):\n",
+    "\n",
+    "    # Update the repository metadata\n",
+    "    \n",
+    "    metadata_file = open(\"metadata_limonet.json\",)\n",
+    "\n",
+    "    # Returns JSON object as a dictionary\n",
+    "    metadata = json.load(metadata_file)\n",
+    "    # Get metadata\n",
+    "    dataset_id.update_metadata(metadata)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "3e2ffe24",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def upload_data(dataset_id, day):\n",
+    "    \n",
+    "    # Upload data\n",
+    "    # ej: dataset_id.upload_filepath('Lightning/Lighting_2021_04_01_18_52.dat')\n",
+    "\n",
+    "    files = sorted(glob.glob(\"Lightning/Lighting_\" + day + \"*.dat\")) # Sort datafiles\n",
+    "    M = len(files)\n",
+    "\n",
+    "    for i in progressbar(range(M), \"Uploading: \", 50):\n",
+    "\n",
+    "        dataset_id.upload_filepath(files[i])\n",
+    "\n",
+    "    print ('\\nData uploaded\\n')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "16a19fd8",
+   "metadata": {},
+   "source": [
+    "## Upload data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "283b362e",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "env: API_TOKEN=0a1616ce-fbe8-44f7-955f-d095f1061617\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Token from repository\n",
+    "\n",
+    "%env API_TOKEN=0a1616ce-fbe8-44f7-955f-d095f1061617 "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "8d8bc25f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "API_TOKEN = os.environ['API_TOKEN']\n",
+    "host = 'dataverse.redclara.net'                  # All clients >4.0 are supported\n",
+    "# Conexión a repositorio\n",
+    "connection = Connection(host, API_TOKEN)\n",
+    "# Selección de dataverse a user\n",
+    "dataverse_id = connection.get_dataverse('limonet')  # Dataverse id"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "a437ef59",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Files: Lightning/Lighting_2021_11_11*.dat Dataset: LM_2021_11_11 Date: 2021-11-17\n",
+      "Uploading: [##################################################] 1/1\n",
+      "\n",
+      "Data uploaded\n",
+      "\n",
+      "Files: Lightning/Lighting_2021_11_13*.dat Dataset: LM_2021_11_13 Date: 2021-11-17\n",
+      "Uploading: [##################################################] 19/19\n",
+      "\n",
+      "Data uploaded\n",
+      "\n",
+      "Files: Lightning/Lighting_2021_11_14*.dat Dataset: LM_2021_11_14 Date: 2021-11-17\n",
+      "Uploading: [##################################################] 28/28\n",
+      "\n",
+      "Data uploaded\n",
+      "\n",
+      "Files: Lightning/Lighting_2021_11_15*.dat Dataset: LM_2021_11_15 Date: 2021-11-17\n",
+      "Uploading: [##################################################] 45/45\n",
+      "\n",
+      "Data uploaded\n",
+      "\n",
+      "Files: Lightning/Lighting_2021_11_16*.dat Dataset: LM_2021_11_16 Date: 2021-11-17\n",
+      "Uploading: [##################################################] 1/1\n",
+      "\n",
+      "Data uploaded\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "year = '2021'\n",
+    "month = '11'\n",
+    "\n",
+    "now = datetime.datetime.now()\n",
+    "upload_date = (\"%s-%s-%s\" % (now.year, now.month, now.day))\n",
+    "\n",
+    "for i in range(11,17):\n",
+    "    day = str(i).zfill(2)\n",
+    "    file_date = (\"%s_%s_%s\" % (year, month, day))\n",
+    "    file_name = (\"Lightning/Lighting_%s*.dat\" % file_date)\n",
+    "    \n",
+    "\n",
+    "    files = glob.glob(file_name)\n",
+    "    M = len(files)\n",
+    "\n",
+    "    if files != []:  # Check files existence\n",
+    "        \n",
+    "        dataset_name = (\"LM_%s\" % file_date)\n",
+    "        print (\"Files: %s Dataset: %s Date: %s\" % (file_name, dataset_name, upload_date))\n",
+    "        \n",
+    "        dataset_id = create_dataset(dataset_name)\n",
+    "        modify_metadata(dataset_name, upload_date)\n",
+    "        load_metadata(dataset_id)\n",
+    "        upload_data(dataset_id, file_date)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "53fa4cfc",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}