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+{
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+ "cells": [
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+ {
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+ "cell_type": "markdown",
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+ "id": "b6e6fa62",
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+ "metadata": {},
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+ "source": [
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+ "# ワークフロー機能トップページ\n",
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+ "\n",
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+ "研究プロセスで生じる研究者のタスクを半機械的に実行支援します。 \n",
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+ "ワークフロー機能では、研究プロセスを研究準備、実験期、実験終了後というフェーズに大別し、それぞれのフェーズの特徴に沿ったタスクの実行支援を用意しています。 \n",
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+ "また、個々のタスクの実行支援は、Jupyter Notebook形式で機械的に実行可能な手順書として記述されているため、柔軟に手順を修正いただけます。 \n"
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+ ]
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+ },
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+ {
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+ "cell_type": "markdown",
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+ "id": "ab1b456b",
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+ "metadata": {},
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+ "source": [
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+ "## ワークフロー機能の使い方\n",
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+ "\n",
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+ "「0.ワークフロー機能を実行するための準備をする」を最初に実行したあと、研究準備フェーズから実験期フェーズ、実験終了後フェーズの順に必要なワークフローを実行してください。 \n",
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+ "0フェーズを実行した後は、お好きなタイミングでワークフロー機能を中断可能です。再度ワークフロー機能を利用する際は、研究リポジトリのREADME.mdにあるリンクをクリックしてください。 \n",
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+ "また、全てのワークフローを実行する必要はありません。 \n",
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+ "「フェーズの概要」を確認後、セルを実行してワークフロー図を作成してください。 "
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+ ]
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+ },
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+ {
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+ "cell_type": "markdown",
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+ "id": "4b5bd2b2",
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+ "metadata": {},
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+ "source": [
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+ "## フェーズの概要"
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+ ]
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+ },
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+ {
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+ "cell_type": "markdown",
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+ "id": "d27970ec",
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+ "metadata": {},
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+ "source": [
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+ "### 0. ワークフロー機能を実行するための準備をする\n",
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+ "\n",
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+ "次のフェーズに進む前に必ず実行する必要があります。 \n",
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+ "ワークフロー機能を使うのが初めての場合は、「初期セットアップを行う」、「起動毎に必要な準備を行う」の順に実行してください。 \n",
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+ "2回目以降でワークフロー機能にREADMEのリンクからではなく、以下のmaDMP実行環境への遷移ボタンから遷移した場合は、ワークフロー機能を実行する前に「起動毎に必要な準備を行う」を実行してください。 \n",
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+ "![maDMP実行ボタン](https://raw.githubusercontent.com/NII-DG/workflow-template/main/images/maDMP実行ボタン.png)"
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+ ]
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+ },
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+ {
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+ "cell_type": "markdown",
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+ "id": "65dbb0c0",
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+ "metadata": {},
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+ "source": [
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+ "### 1. 研究準備フェーズ\n",
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+ "\n",
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+ "研究準備フェーズでは実験前の準備をサポートします。"
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+ ]
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+ },
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+ {
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+ "cell_type": "markdown",
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+ "id": "7883887f",
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+ "metadata": {},
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+ "source": [
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+ "### 2. 実験フェーズ\n",
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+ "\n",
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+ "実験フェーズでは実験の開始から、複数の実験の再現性の確認などをサポートします。<br>まずは、「実験を開始する」から実験を作成してください。複数の実験の終了後、再現性を確認したいタイミングで「モニタリングを実施する」を実行してください。"
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+ ]
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+ },
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+ {
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+ "cell_type": "markdown",
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+ "id": "4e056777",
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+ "metadata": {},
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+ "source": [
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+ "### 3 実験終了後フェーズ\n",
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+ "\n",
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+ "実験終了後フェーズでは研究成果の公開をサポートします。"
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+ ]
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+ },
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+ {
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+ "cell_type": "markdown",
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+ "id": "2401f89e",
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+ "metadata": {},
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+ "source": [
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+ "## ワークフロー図を作成する\n",
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+ "\n",
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+ "以下のセルを実行してワークフロー図を作成できます。 \n",
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+ "すでに実行したワークフローを確認したい場合は再度実行してください。"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 1,
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+ "frozen": true
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+ }
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+ },
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+ "outputs": [
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+ " group {\n",
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+ " orientation = portrait;\n",
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+ " color = "#ffeed9";\n",
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+ " "0. prepare_for_workflow"[label = "0. ワークフロー機能の実行準備", fontsize = 14];\n",
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+ " "base_required_every_time"[fontsize = 14];\n",
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+ " }\n",
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+ " }\n",
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+ "\n",
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+ " group {\n",
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+ " orientation = portrait;\n",
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+ " color = "#fcdcb1";\n",
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+ " "1. preparation_phase"[label = "1. 研究準備フェーズ", fontsize = 14];\n",
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+ " "base_setup_data_analysis_tools";\n",
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+ " "base_work_with_GakuNinRDM";\n",
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+ " }\n",
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+ " }\n",
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+ "\n",
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+ " group {\n",
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+ " shape = line;\n",
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+ " style = none;\n",
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+ " group {\n",
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+ " orientation = portrait;\n",
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+ " color = "#ffd6a1";\n",
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+ " "2. experimental_phase"[label = "2. 実験フェーズ", fontsize = 14];\n",
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+ " "base_launch_an_experiment";\n",
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+ " "dummy"[shape=none, width=1, height=1];\n",
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+ " "base_monitor_data_size";\n",
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+ " "base_monitor_dataset_structure";\n",
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+ " "base_monitor_reproducibility";\n",
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+ " }\n",
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+ " }\n",
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+ " group {\n",
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+ " group {\n",
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+ " orientation = portrait;\n",
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+ " color = "#ffb95c";\n",
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+ " "3. after_experiments_phase"[label = "3 実験終了後フェーズ", fontsize = 14];\n",
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+ " "base_publish"[fontsize = 14];\n",
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+ " }\n",
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+ " }\n",
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+ " group {\n",
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+ " orientation = portrait;\n",
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+ " color = "#ffa329";\n",
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+ " "4. after_research"[label = "4. 研究終了後", fontsize = 14];\n",
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+ " "base_finish_research";\n",
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+ " }\n",
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+ " }\n",
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+ " }\n",
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+ "\n",
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+ " "0. prepare_for_workflow" -> "1. preparation_phase" -> "2. experimental_phase" -> "3. after_experiments_phase" -> "4. after_research";\n",
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+ " "base_launch_an_experiment" -> "base_launch_an_experiment";\n",
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+ " "base_launch_an_experiment" -> "dummy"[dir=none];\n",
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+ " "dummy" -> "base_monitor_data_size", "base_monitor_dataset_structure", "base_monitor_reproducibility";\n",
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+ " <text fill=\"rgb(0,0,0)\" font-family=\"sans-serif\" font-size=\"14\" font-style=\"normal\" font-weight=\"normal\" text-anchor=\"middle\" textLength=\"203\" x=\"155.5\" y=\"120\">0. ワークフロー機能の実行準備</text>\n",
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+ " <polygon fill=\"rgb(0,0,0)\" points=\"965,635 961,628 969,628 965,635\" stroke=\"rgb(0,0,0)\"/>\n",
|
|
|
+ " <path d=\"M 155 966 L 155 998\" fill=\"none\" stroke=\"rgb(0,0,0)\"/>\n",
|
|
|
+ " <polygon fill=\"rgb(0,0,0)\" points=\"155,1005 151,998 159,998 155,1005\" stroke=\"rgb(0,0,0)\"/>\n",
|
|
|
+ " <path d=\"M 155 966 L 155 998\" fill=\"none\" stroke=\"rgb(0,0,0)\"/>\n",
|
|
|
+ " <polygon fill=\"rgb(0,0,0)\" points=\"155,1005 151,998 159,998 155,1005\" stroke=\"rgb(0,0,0)\"/>\n",
|
|
|
+ " <rect fill=\"none\" height=\"1131\" stroke=\"rgb(243,152,0)\" stroke-dasharray=\"0 196605\" stroke-width=\"3\" width=\"1050\" x=\"35\" y=\"30\"/>\n",
|
|
|
+ " <rect fill=\"none\" height=\"165\" stroke=\"rgb(243,152,0)\" stroke-dasharray=\"0 196605\" stroke-width=\"3\" width=\"510\" x=\"35\" y=\"30\"/>\n",
|
|
|
+ " <rect fill=\"none\" height=\"165\" stroke=\"rgb(243,152,0)\" stroke-dasharray=\"0 196605\" stroke-width=\"3\" width=\"780\" x=\"35\" y=\"215\"/>\n",
|
|
|
+ " <rect fill=\"none\" height=\"391\" stroke=\"rgb(243,152,0)\" stroke-dasharray=\"0 196605\" stroke-width=\"3\" width=\"1050\" x=\"35\" y=\"400\"/>\n",
|
|
|
+ " <rect fill=\"none\" height=\"165\" stroke=\"rgb(243,152,0)\" stroke-dasharray=\"0 196605\" stroke-width=\"3\" width=\"510\" x=\"35\" y=\"811\"/>\n",
|
|
|
+ " <rect fill=\"none\" height=\"165\" stroke=\"rgb(243,152,0)\" stroke-dasharray=\"0 196605\" stroke-width=\"3\" width=\"510\" x=\"35\" y=\"996\"/>\n",
|
|
|
+ "</svg>"
|
|
|
+ ],
|
|
|
+ "text/plain": [
|
|
|
+ "<IPython.core.display.SVG object>"
|
|
|
+ ]
|
|
|
+ },
|
|
|
+ "execution_count": 1,
|
|
|
+ "metadata": {},
|
|
|
+ "output_type": "execute_result"
|
|
|
+ }
|
|
|
+ ],
|
|
|
+ "source": [
|
|
|
+ "import os\n",
|
|
|
+ "from IPython.display import SVG\n",
|
|
|
+ "\n",
|
|
|
+ "nb_utils_path = os.path.join(os.environ['HOME'], 'WORKFLOW/FLOW/util/scripts/nb_utils.py')\n",
|
|
|
+ "\n",
|
|
|
+ "basic_path = os.path.join(os.environ['HOME'], 'WORKFLOW/images')\n",
|
|
|
+ "basic_path_diag = os.path.join(basic_path, 'notebooks.diag')\n",
|
|
|
+ "basic_path_svg = os.path.join(basic_path, 'notebooks.svg')\n",
|
|
|
+ "\n",
|
|
|
+ "os.chdir(os.environ['HOME'])\n",
|
|
|
+ "!python3 $nb_utils_path $basic_path_diag\n",
|
|
|
+ "\n",
|
|
|
+ "SVG(filename=basic_path_svg)"
|
|
|
+ ]
|
|
|
+ },
|
|
|
+ {
|
|
|
+ "cell_type": "markdown",
|
|
|
+ "id": "6e5b603e",
|
|
|
+ "metadata": {},
|
|
|
+ "source": [
|
|
|
+ "ワークフロー図の左のノードはワークフローのフェーズとその流れを表しており、フェーズの右側にあるノードは個々のワークフローを表しています。 \n",
|
|
|
+ "各ワークフローを実行するには、ワークフローの各ノードのリンクをクリックしてください。"
|
|
|
+ ]
|
|
|
+ },
|
|
|
+ {
|
|
|
+ "cell_type": "markdown",
|
|
|
+ "id": "b0fe6a6d",
|
|
|
+ "metadata": {},
|
|
|
+ "source": [
|
|
|
+ "## データガバナンス機能へ戻る\n",
|
|
|
+ "\n",
|
|
|
+ "以下のセルを実行し、表示されるURLをクリックするとデータガバナンス機能へアクセスできます。"
|
|
|
+ ]
|
|
|
+ },
|
|
|
+ {
|
|
|
+ "cell_type": "code",
|
|
|
+ "execution_count": null,
|
|
|
+ "id": "ace85028",
|
|
|
+ "metadata": {},
|
|
|
+ "outputs": [],
|
|
|
+ "source": [
|
|
|
+ "!git config --get remote.origin.url"
|
|
|
+ ]
|
|
|
+ }
|
|
|
+ ],
|
|
|
+ "metadata": {
|
|
|
+ "kernelspec": {
|
|
|
+ "display_name": "Python 3 (ipykernel)",
|
|
|
+ "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": "3.9.10"
|
|
|
+ }
|
|
|
+ },
|
|
|
+ "nbformat": 4,
|
|
|
+ "nbformat_minor": 5
|
|
|
+}
|