Create_linkset.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import the necessary files\n",
    "\n",
    "# The DAS dataset\n",
    "das = pd.ExcelFile('das.xlsx')\n",
    "\n",
    "# The results of matching BGB shipvoyages to DAS ship IDs (see separate script 'BGB-voyages to DAS ship IDs')\n",
    "daslinks = pd.ExcelFile('Matching_results.xlsx')\n",
    "daslinkset = daslinks.parse('Matches')\n",
    "dasships = das.parse('ship')\n",
    "\n",
    "# The results of matching GZB musterings to DAS ship IDs (see separate script 'Remaining BGB and GZM ships')\n",
    "zeemons = pd.read_pickle('zeemons.pkl')\n",
    "\n",
    "# The preliminary linkset of BGB and GZM ships that were not matched to a DAS ship (see separate script 'Remaining BGB and GZM ships')\n",
    "prel_linkset = pd.read_pickle('prel_linkset.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>shipID</th>\n",
       "      <th>voyTonnageMin</th>\n",
       "      <th>voyTonnageMax</th>\n",
       "      <th>voyTypeOfShipID</th>\n",
       "      <th>voyBuilt</th>\n",
       "      <th>voyBuiltRemark</th>\n",
       "      <th>voyBuiltY</th>\n",
       "      <th>voyYardYardID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>DAS_ship0001</td>\n",
       "      <td>600.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1724</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1724.0</td>\n",
       "      <td>DAS_yard006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>DAS_ship0002</td>\n",
       "      <td>880.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1762</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1762.0</td>\n",
       "      <td>DAS_yard001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>DAS_ship0003</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DAS_type031</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DAS_yard001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>DAS_ship0004</td>\n",
       "      <td>600.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1722</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1722.0</td>\n",
       "      <td>DAS_yard001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>DAS_ship0005</td>\n",
       "      <td>300.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DAS_yard001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1850</th>\n",
       "      <td>DAS_ship1852</td>\n",
       "      <td>90.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DAS_type031</td>\n",
       "      <td>1690</td>\n",
       "      <td>built in Indies</td>\n",
       "      <td>1690.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1851</th>\n",
       "      <td>DAS_ship1853</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>hired</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1852</th>\n",
       "      <td>DAS_ship1854</td>\n",
       "      <td>850.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1745</td>\n",
       "      <td>bought (Originally the TOEVALLIGHEID  was a Fr...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1853</th>\n",
       "      <td>DAS_ship1855</td>\n",
       "      <td>525.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1735</td>\n",
       "      <td>built in Indies</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1854</th>\n",
       "      <td>DAS_ship1856</td>\n",
       "      <td>600.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DAS_type016</td>\n",
       "      <td>1772</td>\n",
       "      <td>bought in China</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1855 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            shipID  voyTonnageMin  voyTonnageMax voyTypeOfShipID voyBuilt  \\\n",
       "0     DAS_ship0001          600.0            NaN             NaN     1724   \n",
       "1     DAS_ship0002          880.0            NaN             NaN     1762   \n",
       "2     DAS_ship0003            NaN            NaN     DAS_type031      NaN   \n",
       "3     DAS_ship0004          600.0            NaN             NaN     1722   \n",
       "4     DAS_ship0005          300.0            NaN             NaN      NaN   \n",
       "...            ...            ...            ...             ...      ...   \n",
       "1850  DAS_ship1852           90.0            NaN     DAS_type031     1690   \n",
       "1851  DAS_ship1853            NaN            NaN             NaN      NaN   \n",
       "1852  DAS_ship1854          850.0            NaN             NaN     1745   \n",
       "1853  DAS_ship1855          525.0            NaN             NaN     1735   \n",
       "1854  DAS_ship1856          600.0            NaN     DAS_type016     1772   \n",
       "\n",
       "                                         voyBuiltRemark  voyBuiltY  \\\n",
       "0                                                   NaN     1724.0   \n",
       "1                                                   NaN     1762.0   \n",
       "2                                                   NaN        NaN   \n",
       "3                                                   NaN     1722.0   \n",
       "4                                                   NaN        NaN   \n",
       "...                                                 ...        ...   \n",
       "1850                                    built in Indies     1690.0   \n",
       "1851                                              hired        NaN   \n",
       "1852  bought (Originally the TOEVALLIGHEID  was a Fr...        NaN   \n",
       "1853                                    built in Indies        NaN   \n",
       "1854                                    bought in China        NaN   \n",
       "\n",
       "     voyYardYardID  \n",
       "0      DAS_yard006  \n",
       "1      DAS_yard001  \n",
       "2      DAS_yard001  \n",
       "3      DAS_yard001  \n",
       "4      DAS_yard001  \n",
       "...            ...  \n",
       "1850           NaN  \n",
       "1851           NaN  \n",
       "1852           NaN  \n",
       "1853           NaN  \n",
       "1854           NaN  \n",
       "\n",
       "[1855 rows x 8 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dasships"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a list with DAS ship IDs and corresponding BGB shipvoyages\n",
    "matching_dict = {}\n",
    "\n",
    "# Loop over all unique DAS ships\n",
    "for ship in dasships.index:\n",
    "    das_id = dasships.loc[ship, 'shipID']\n",
    "    das_name = dasships.loc[ship, 'shipID']\n",
    "    \n",
    "    # Create entry in dict for this DAS ship\n",
    "    matching_dict[das_id] = {}\n",
    "    \n",
    "    # Lookup matches in BGB and for each match the rule on which the match is based (see original script)\n",
    "    matches = daslinkset['BGB Shipvoyage ID'].loc[daslinkset['DAS shipname ID'] == das_id]\n",
    "    rules = daslinkset['Matched based on rule'].loc[daslinkset['DAS shipname ID'] == das_id]\n",
    "    \n",
    "    # Create entry for keeping BGB links for this DAS ship\n",
    "    matching_dict[das_id]['BGB'] = []\n",
    "    \n",
    "    # Append all BGB matches to dict (with corresponding rules in brackets)\n",
    "    for match in zip(matches, rules):\n",
    "        matching_dict[das_id]['BGB'].append(str(match[0]) + \" (\" + str(match[1]) + \")\")\n",
    "        \n",
    "    # And do the same for the GZM (loopup matches and append them to dict)\n",
    "    gzm_match = zeemons['GZM SHIP ID'].loc[zeemons['DAS SHIP ID'] == das_id]\n",
    "    matching_dict[das_id]['GZM'] = []\n",
    "    for gzm in gzm_match:\n",
    "        matching_dict[das_id]['GZM'].append(gzm)\n",
    "\n",
    "# Store results in dataframe\n",
    "allmatches = pd.DataFrame.from_dict(matching_dict, orient='index')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert linkset to use GLOB ship IDs\n",
    "complete_linkset = {}\n",
    "\n",
    "for match in allmatches.index:\n",
    "    \n",
    "    # Construct GLOB ship ID\n",
    "    glob_id = str(match)\n",
    "    glob_id = glob_id[-4:]\n",
    "    glob_id = int(glob_id)\n",
    "    \n",
    "    complete_linkset[glob_id] = {}\n",
    "    # Set GZM links\n",
    "    complete_linkset[glob_id]['GZM'] = []\n",
    "    for gzmlink in allmatches.loc[match, 'GZM']:\n",
    "        complete_linkset[glob_id]['GZM'].append(gzmlink)\n",
    "    \n",
    "    # Set BGB links\n",
    "    complete_linkset[glob_id]['BGB'] = []\n",
    "    for bgblink in allmatches.loc[match, 'BGB']:\n",
    "        complete_linkset[glob_id]['BGB'].append(bgblink)\n",
    "\n",
    "# Store results in a dataframe        \n",
    "newmatches = pd.DataFrame.from_dict(complete_linkset, orient='index')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Merge the results with the preliminary linkset from a previous script (see separate script 'Remaining BGB and GZM ships')\n",
    "# The preliminary set excluded ships with a DAS match (which we have now added)\n",
    "\n",
    "# Create an empty list to hold the links\n",
    "linklist = []\n",
    "\n",
    "# Loop over every ship in our linkset\n",
    "for globship in newmatches.index:\n",
    "        gzmlinks = newmatches.loc[globship, 'GZM']\n",
    "        bgblinks = newmatches.loc[globship, 'BGB']\n",
    "        linklist.append([globship, ';'.join(str(i) for i in gzmlinks), ';'.join(str(i) for i in bgblinks)])\n",
    "\n",
    "# Make a Dataframe\n",
    "das_linkset = pd.DataFrame.from_records(linklist, columns=['GLOB SHIP ID', 'GZM SHIP IDS', 'BGB SHIPVOYAGES'])   \n",
    "\n",
    "# Merge the preliminary linkset and the new linkset to form the final linkset\n",
    "linkset = pd.concat([das_linkset, prel_linkset], ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add links to DAS IDs\n",
    "linkset['DAS ID'] = None\n",
    "\n",
    "for ship in linkset.index:\n",
    "    glob_id = int(linkset.loc[ship, 'GLOB SHIP ID'])\n",
    "    \n",
    "    if glob_id < 1857:\n",
    "        das_id = 'DAS_ship' + str(glob_id).zfill(4)\n",
    "        linkset.loc[ship, 'DAS ID'] = das_id\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GLOB SHIP ID</th>\n",
       "      <th>GZM SHIP IDS</th>\n",
       "      <th>BGB SHIPVOYAGES</th>\n",
       "      <th>DAS ID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2903;2996;3344;3381;3457;3863;3881;4024</td>\n",
       "      <td>7574 (2);7754 (2);7770 (2);7804 (2);7881 (2);7...</td>\n",
       "      <td>DAS_ship0001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>4662</td>\n",
       "      <td>3699 (1);3943 (1);4024 (2);4225 (2);4273 (1);4...</td>\n",
       "      <td>DAS_ship0002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>DAS_ship0003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2704;2952</td>\n",
       "      <td>13772 (1);14137 (2);14520 (2);15347 (1);15446 ...</td>\n",
       "      <td>DAS_ship0004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>DAS_ship0005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2851</th>\n",
       "      <td>2853</td>\n",
       "      <td></td>\n",
       "      <td>18537;18543</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2852</th>\n",
       "      <td>2854</td>\n",
       "      <td>1302</td>\n",
       "      <td></td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2853</th>\n",
       "      <td>2855</td>\n",
       "      <td>3403</td>\n",
       "      <td></td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2854</th>\n",
       "      <td>2856</td>\n",
       "      <td>419;496;887;1034;1139;1279</td>\n",
       "      <td></td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2855</th>\n",
       "      <td>2857</td>\n",
       "      <td>344</td>\n",
       "      <td></td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2856 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      GLOB SHIP ID                             GZM SHIP IDS  \\\n",
       "0                1  2903;2996;3344;3381;3457;3863;3881;4024   \n",
       "1                2                                     4662   \n",
       "2                3                                            \n",
       "3                4                                2704;2952   \n",
       "4                5                                            \n",
       "...            ...                                      ...   \n",
       "2851          2853                                            \n",
       "2852          2854                                     1302   \n",
       "2853          2855                                     3403   \n",
       "2854          2856               419;496;887;1034;1139;1279   \n",
       "2855          2857                                      344   \n",
       "\n",
       "                                        BGB SHIPVOYAGES        DAS ID  \n",
       "0     7574 (2);7754 (2);7770 (2);7804 (2);7881 (2);7...  DAS_ship0001  \n",
       "1     3699 (1);3943 (1);4024 (2);4225 (2);4273 (1);4...  DAS_ship0002  \n",
       "2                                                        DAS_ship0003  \n",
       "3     13772 (1);14137 (2);14520 (2);15347 (1);15446 ...  DAS_ship0004  \n",
       "4                                                        DAS_ship0005  \n",
       "...                                                 ...           ...  \n",
       "2851                                        18537;18543          None  \n",
       "2852                                                             None  \n",
       "2853                                                             None  \n",
       "2854                                                             None  \n",
       "2855                                                             None  \n",
       "\n",
       "[2856 rows x 4 columns]"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "linkset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import necessary modules for serializing to RDF linkset\n",
    "import rdflib\n",
    "from rdflib import Graph, Namespace, RDF, RDFS, URIRef, Literal, BNode, OWL, XSD, FOAF, PROV\n",
    "from rdflib.resource import Resource"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define namespaces to be used in linkset\n",
    "LINKSETS = Namespace(\"https://data.globalise.huygens.knaw.nl/id/linksets/\")\n",
    "SHIP = Namespace(\"https://data.globalise.huygens.knaw.nl/id/ship/\")\n",
    "GZM_SHIP = Namespace(\"https://data.globalise.huygens.knaw.nl/id/gzm/ship/\")\n",
    "BGB_SHIP = Namespace(\"https://data.globalise.huygens.knaw.nl/id/bgb/ship/\")\n",
    "DAS_SHIP = Namespace(\"https://data.globalise.huygens.knaw.nl/id/das/ship/\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create an empty graph\n",
    "g = Graph(identifier=LINKSETS.enrich_from_das + \"/\")\n",
    "\n",
    "# Loop over every ship in our linkset\n",
    "for globship in linkset.index:\n",
    "    glob_ship_id = linkset.loc[globship, 'GLOB SHIP ID']\n",
    "    gzm_ids = linkset.loc[globship, 'GZM SHIP IDS']\n",
    "    bgb_ids = linkset.loc[globship, 'BGB SHIPVOYAGES']\n",
    "    das_id = linkset.loc[globship, 'DAS ID']\n",
    "    \n",
    "    # Create GLOB ID resource\n",
    "    glob_ship_uri = URIRef(SHIP + str(glob_ship_id)) \n",
    "    \n",
    "    # If the ship has a DAS ID, add it to the graph\n",
    "    if das_id:\n",
    "        das_ship_uri = URIRef(DAS_SHIP + str(das_id))\n",
    "        g.add((das_ship_uri, OWL.sameAs, glob_ship_uri))    \n",
    "\n",
    "    # Add the links to GZM ships\n",
    "    for gzm_id in gzm_ids.split(';'):\n",
    "        if gzm_id:\n",
    "            gzm_ship_uri = URIRef(GZM_SHIP + str(gzm_id))\n",
    "            g.add((gzm_ship_uri, OWL.sameAs, glob_ship_uri))\n",
    "\n",
    "            # Add provenance information on this assertion (it comes from a previous script)\n",
    "            statement_id = BNode()       \n",
    "            g.add((statement_id, RDF.type, RDF.Statement))\n",
    "            g.add((statement_id, RDF.subject, gzm_ship_uri))\n",
    "            g.add((statement_id, RDF.predicate, OWL.sameAs))\n",
    "            g.add((statement_id, RDF.object, glob_ship_uri))\n",
    "        g.add((statement_id, PROV.wasDerivedFrom, URIRef(\"https://github.com/globalise-huygens/enrich_from_das/blob/4c34d29560ab644c1aa1a029ca640446aff92dcc/Remaining%20BGB%20and%20GZM%20ships.ipynb\")))      \n",
    "    \n",
    "    # Add the links to BGB ships\n",
    "    for bgb_id in bgb_ids.split(';'):\n",
    "        if bgb_id:\n",
    "            rule = 0\n",
    "            \n",
    "            # If the link contains brackets, it includes info on the rule based on which the link was made (see previous script)\n",
    "            # If so, we want to include this rule in the provenance information\n",
    "            if '(' in bgb_id:\n",
    "                temp = bgb_id.split(' (')\n",
    "                bgb_id = temp[0]\n",
    "                rule = temp[1].rstrip(')')\n",
    "\n",
    "            bgb_ship_uri = URIRef(BGB_SHIP + str(bgb_id))\n",
    "            g.add((bgb_ship_uri, OWL.sameAs, glob_ship_uri))\n",
    "\n",
    "            # Add provenance information on this assertion (it comes from a previous script)\n",
    "            statement_id = BNode()       \n",
    "            g.add((statement_id, RDF.type, RDF.Statement))\n",
    "            g.add((statement_id, RDF.subject, bgb_ship_uri))\n",
    "            g.add((statement_id, RDF.predicate, OWL.sameAs))\n",
    "            g.add((statement_id, RDF.object, glob_ship_uri))\n",
    "\n",
    "            # Add the provenance based on the applied rule (see above and see the script linked in the URI below)\n",
    "            if rule == '1':\n",
    "                g.add((statement_id, PROV.wasDerivedFrom, URIRef(\"https://github.com/globalise-huygens/enrich_from_das/blob/4c34d29560ab644c1aa1a029ca640446aff92dcc/BGB-voyages%20to%20DAS%20ship%20IDs.ipynb#rule_1\")))   \n",
    "            if rule == '2':\n",
    "                g.add((statement_id, PROV.wasDerivedFrom, URIRef(\"https://github.com/globalise-huygens/enrich_from_das/blob/4c34d29560ab644c1aa1a029ca640446aff92dcc/BGB-voyages%20to%20DAS%20ship%20IDs.ipynb#rule_2\")))\n",
    "            else:\n",
    "                g.add((statement_id, PROV.wasDerivedFrom, URIRef(\"https://github.com/globalise-huygens/enrich_from_das/blob/4c34d29560ab644c1aa1a029ca640446aff92dcc/BGB-voyages%20to%20DAS%20ship%20IDs.ipynb\")))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Graph identifier=https://data.globalise.huygens.knaw.nl/id/linksets/enrich_from_das/ (<class 'rdflib.graph.Graph'>)>"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Serialize to trig\n",
    "g.bind(\"ship\", SHIP)\n",
    "g.bind(\"gzm_ship\", GZM_SHIP)\n",
    "g.bind(\"bgb_ship\", BGB_SHIP)\n",
    "g.bind(\"das_ship\", DAS_SHIP)\n",
    "\n",
    "g.serialize(destination=\"enrich_from_das.trig\", format=\"trig\")"
   ]
  }
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