Translation: Library Carpentry OpenRefine Episode 2

[joelnitta]

Translation: Library Carpentry OpenRefine Episode 2

Original lesson: https://librarycarpentry.org/lc-open-refine/02-importing-data/index.html

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i18n/po/lc-open-refine.ja.po

Lines 617 to 706 in bb59a56

	#: lc-open-refine/_episodes/02-importing-data.md:1
	# Front Matter
	msgid "---\n"
	"title: \"Importing data into OpenRefine\"\n"
	"teaching: 10\n"
	"exercises: 5\n"
	"questions:\n"
	"- \"How do I get data into OpenRefine?\"\n"
	"objectives:\n"
	"- \"Successfully import data into OpenRefine\"\n"
	"keypoints:\n"
	"- \"Use the `Create Project` option to import data\"\n"
	"- \"You can control how data imports using options on the import screen\"\n"
	"- \"Several files types may be imported into OpenRefine.\"\n"
	"---"
	msgstr ""
	#: lc-open-refine/_episodes/02-importing-data.md:15
	# header
	msgid "## Importing data"
	msgstr ""
	#: lc-open-refine/_episodes/02-importing-data.md:17
	msgid ">## What kinds of data files can I import?\n"
	">There are several options for getting your data set into OpenRefine. You can upload or import files in a variety of formats including:\n"
	">\n"
	">* TSV (tab-separated values)\n"
	">* CSV (comma-separated values)\n"
	">* Excel\n"
	">* JSON (javascript object notation)\n"
	">* XML\n"
	">* Google Spreadsheet"
	msgstr ""
	#: lc-open-refine/_episodes/02-importing-data.md:26
	#: lc-open-refine/_episodes/03-working-with-data.md:113
	#: lc-open-refine/_episodes/10-data-transformation.md:29
	# SC/DC Template label
	msgid "{: .callout}"
	msgstr ""
	#: lc-open-refine/_episodes/02-importing-data.md:28
	msgid ">## Create your first OpenRefine project (using provided data)\n"
	">\n"
	"> To import the data for the exercise below, follow the instructions in [Setup](https://librarycarpentry.github.io/lc-open-refine/setup.html) to download the data and run OpenRefine. *NOTE: If OpenRefine does not open in a browser window, open your browser and type the address <http://127.0.0.1:3333/> to take you to the OpenRefine interface.*\n"
	">\n"
	">1. Once OpenRefine is launched in your browser, click `Create Project` from the left hand menu and select `Get data from This Computer`\n"
	">2. Click `Choose Files` (or 'Browse', depending on your setup) and locate the file which you have downloaded called `doaj-article-sample.csv`\n"
	">3. Click `Next >>` - the next screen (see below) gives you options to ensure the data is imported into OpenRefine correctly. The options vary depending on the type of data you are importing.\n"
	">4. Click in the `Character encoding` box and set it to `UTF-8`. This ensures that OpenRefine correctly interprets the imported data as UTF-8 encoded. If you don't select this you may find that some special characters (e.g. smart quotation marks) are not displayed correctly.\n"
	">5. Ensure the first row is used to create the column headings by checking the box `Parse next 1 line(s) as column headers`\n"
	">6. OpenRefine will automatically select \"Use character\" to enclose cells containing column separators as this will place data in one cell where the values are enclosed in quotes from the source dataset\n"
	">7. From OpenRefine 3.4 onwards there is an option to Trim leading & trailing whitespace from strings when importing separator-based files. Keeping this checked will ensure that values like `English` and `English `, which differ by a single trailing space, are not treated as different values after the import\n"
	">8. Make sure the `Parse cell text into numbers, dates, ...` box is not checked, so OpenRefine doesn't try to automatically detect numbers as it may cause errors such as confusion between date formats (e.g. DD/MM/YYYY vs MM/DD/YYYY)\n"
	">9. The Project Name box in the upper right corner will default to the title of your imported file. Click in the `Project Name` box to give your project a different name, if desired.\n"
	">10. Once you are happy click the `Create Project >>` button at the top right of the screen. This will create the project and open it for you. Projects are saved as you work on them, there is no need to save copies as you go along.\n"
	"> \n"
	"> "
	msgstr ""
	#: lc-open-refine/_episodes/02-importing-data.md:44
	#: lc-open-refine/_episodes/04-faceting-and-filtering.md:42
	#: lc-open-refine/_episodes/07-introduction-to-transformations.md:47
	#: lc-open-refine/_episodes/08-writing-transformations.md:45
	#: lc-open-refine/_episodes/10-data-transformation.md:42
	#: lc-open-refine/_episodes/10-data-transformation.md:66
	#: lc-open-refine/_episodes/11-using-arrays-transformations.md:79
	# SC/DC Template label
	msgid "{: .checklist}"
	msgstr ""
	#: lc-open-refine/_episodes/02-importing-data.md:46
	msgid "To open an existing project in OpenRefine you can click `Open Project` from the main OpenRefine screen (in the left hand menu). When you click this, you will see a list of the existing projects and can click on a project's name to open it."
	msgstr ""
	#: lc-open-refine/_episodes/02-importing-data.md:48
	# header
	msgid "### Going Further"
	msgstr ""
	#: lc-open-refine/_episodes/02-importing-data.md:49
	# unordered list
	msgid "* Look at the other options on the Import screen - try changing some of these options and see how that changes the Preview and how the data appears after import."
	msgstr ""
	#: lc-open-refine/_episodes/02-importing-data.md:50
	# unordered list
	msgid "* Do you have access to JSON or XML data? If so the first stage of the import process will prompt you to select a 'record path' - that is the parts of the file that will form the data rows in the OpenRefine project."
	msgstr ""