{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": [
     "remove-cell"
    ]
   },
   "outputs": [],
   "source": [
    "from IPython.display import YouTubeVideo, VimeoVideo, IFrame"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Concepts\n",
    "\n",
    "Here's where it all starts. In this section we introduce the course and what Geographic Data Science is. We top it up with a few (optional) further readings for the interested and curious mind."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## This course\n",
    "\n",
    "Let us start from the beginning, here is a snapshot of what this course is about! In the following clip, you will find out about the philosophy behind the course, how the content is structured, and why this is all designed like this. And, also, a little bit about the assessment..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```{sidebar} Slides\n",
    "\n",
    "The slides used in the clip are available at:\n",
    "\n",
    "- <a href=\"../slides/block_A_i.html\"> `[HTML]` </a>\n",
    "- <a href=\"../slides/pdf/block_A_i.pdf\"> `[PDF]` </a>\n",
    "\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": [
     "remove-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"500\"\n",
       "            height=\"300\"\n",
       "            src=\"https://liverpool.instructuremedia.com/embed/45750aa3-f777-4431-8752-019f9f431eb7\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x7f2f89709810>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "IFrame(\"https://liverpool.instructuremedia.com/embed/45750aa3-f777-4431-8752-019f9f431eb7\",\n",
    "       width=500,\n",
    "       height=300\n",
    "      )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The video also mentions a clip about the digitalisation of our activities. If you want to watch it outside the slides, expand below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": [
     "remove-input",
     "hide-output"
    ]
   },
   "outputs": [
    {
     "data": {
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       "        ></iframe>\n",
       "        "
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   "source": [
    "## What is *Geographic Data Science*?\n",
    "\n",
    "Once it is clearer how this course is going to run, let's dive right into why this course is necessary. The following clip is taken from a keynote response by Dani Arribas-Bel at the first [Spatial Data Science Conference](https://carto.com/spatial-data-conference/2017/), organised by [CARTO](https://carto.com/) and held in Brooklyn in 2017. The talk provides a bit of background and context, which will hopefully help you understand a bit better what Geographic Data Science is."
   ]
  },
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   "cell_type": "markdown",
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   "source": [
    "```{sidebar} Slides\n",
    "\n",
    "The slides used in the clip are available at:\n",
    "\n",
    "- <a href=\"../slides/block_A_ii.html\"> `[HTML]` </a>\n",
    "- <a href=\"../slides/pdf/block_A_ii.pdf\"> `[PDF]` </a>\n",
    "\n",
    "```"
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   "source": [
    "## Further readings"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To get a better picture, the following readings complement the overview provided above very well:\n",
    "\n",
    "```{margin} Bonus\n",
    "The chapter is available free online [`HTML`](http://shop.oreilly.com/product/0636920028529.do) | [`PDF`](http://cdn.oreillystatic.com/oreilly/booksamplers/9781449358655_sampler.pdf)\n",
    "```\n",
    "1. The introductory chapter to \"Doing Data Science\" {cite}`schutt2013doing`, by Cathy O'Neil and Rachel Schutt is general overview of why we needed Data Science and where if came from. \n",
    "1. A slightly more technical historical perspective on where Data Science came from and where it might go can be found in David Donoho's recent overview {cite}`donoho201750`.\n",
    "1. A geographic take on Data Science, proposing more interaction between Geography and Data Science {cite}`singleton2019geographic`."
   ]
  }
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