This document provides an overview of a preconference day at the RSA 2019 conference in Toronto, including presentations on mapping projects and tools like OpenRefine, TimelineJS, Palladio, and CARTO. It then provides detailed instructions on how to use OpenRefine for cleaning data, transforming values, enriching data by retrieving information from external sources like Wikidata, and exporting cleaned data. It also gives an overview of several timeline tools and an example of creating a timeline in TimelineJS using data from a Botticelli spreadsheet.

1. RSA 2019, Toronto
Preconference day
March 16, 2019
11AM-1PM

2. Programm
 11-11:05 -- Introduction to the session and
presenters
 PRESENTATION OF PROJECTS
 11:05-11:20 – Jodi: Mapping Titan, Mapping
Paintings
 11:20-11:35 – Catherine: Mapping Sculpture
 PRESENTATION OF TOOLS
 11:35-12:05 – Angela: OpenRefine, TimelineJS
 12:05-12:35 – Catherine: Palladio, CARTO
 Hands-on

4. OpenRefine
 Cleaning up messy data from a
spreadsheet
 Spelling errors
 Uniform data
 Removing whitespace
 Splitting columns
 Enriching data from external sources
 Etc.
You won’t be analysing your data one by one, but
in groups and sets. Therefore the application is
suitable for very large data sets.

5. OpenRefine
 Apart from cleaning data, you can also
use Open Refine for different purposes
 Word counts in sets
 Combine sheets
 Enriching reconciled data with Open Refine:
Import data from Wikidata or VIAF

6. OpenRefine
 Free, open source software
 Works best with Google Chrome (less with Safari and
Explorer)
 Written in Java. Requires Java JRE
 Works with Interactive Data Transformation tools (IDTs),
which allows to change a big data set at one time. It is
similar to a spreadsheet, but has more functionalities.
 Works as a destop application. It does not store your
data. Save them! It may be used in several tabs
contemporaneously.
 The .exe file opens a terminal window as web application,
where the little server is running. It needs to remain open.
Runs offline through the terminal window.

7. OpenRefine
 Chose a project and upload it.
 Rename project (save it later, Open Refine does not save
or store automatically!!)
 Use code UTF-8
 Configure your data: You will be shown a preview of your
data. In the lower blue field, make sure “Parse data as” is
set to “CSV / TSV / separator-based files”. Where it says
character encoding, click in the blank field next to it and
select UTF-8 from the pop-up window of encodings. Make
sure the first row with your column headers is recognized
as headers (boldfaced) and not as your data. If it is not
automatically recognized, check the click box for “Parse
next ‘1’ line(s) as column headers”. Since our exercise file
is a CSV, activate the radio button “commas (CSV)” as the
separator.

8. OpenRefine – basic clean
up
 Text facet -> cluster
 Get rid of whitespace: «Edit cells» -> «Common
transforms» -> «Trim leading and trailing whitespace» /
«Collapse consecutive whitespace»
 Divide columns: «Edit column» -> «Split into several
columns…»
 Reorder columns
 Cluster: «Edit cells» -> «Cluster and edit…» (only works
for entire clusters to be merged, no selection possible)
 Replace: Edit cells -> replace
 Undo/redo: step by step index in the menu
 Cancelling: Text facet –> chose what to eliminate and
place a star –> back to facet by star –> true –> under all –
facet by star –> remove all matching rows

9. OpenRefine - transform
 Exchange values: Edit cells -> transform ->
GREL language -> transform the value
 Replace: value.replace(‘xx’, ‘x’)
 Add characters to a column: “prefix” + value
 Cleaning up a date to show only the year:
datePart(value,'year')
 GREL : General Refine Expression Language on
GitHub
https://github.com/OpenRefine/OpenRefine/wiki/Gen
eral-Refine-Expression-Language

10. OpenRefine – example from
Wikipedia – Italian artists
 Download table from Wikipedia
 You want to separate names and years
 Add column based on this column
 Edit cells -> replace (to change the brakets into a colon, to be
used later as idenfier)
 Edit column – split into several columns (use colon as identifier)
 Replace ) by null
 Value + «, « + cells(«mycell»).value
 Person separate: edit column – add column based on this
column – value.split(« «)[1]
○ 1= last name / 0= first name
 Add last name, first name together: value + «, « +
cells[«Firstname»].value
 Another option: Split cells: Choose ‘Edit cells’, ‘Split multi-
valued cells’, entering ‘|’ as the value separator.

11. OpenRefine for Data
enrichment
(using Linked Open Data)
 Fetch URLs using Refine
 Contruct URL queries to retrieve
information from a simple web API
 Using query services like:
 Wikidata
 Google maps API
 VIAF (Virtual International Authority File)
 etc.

12. Retrieving data from
Wikidata
 You need a column Wikidata_uri
 Create a column Wikidata_id: Edit column –> add
column based on this column –> for the ID extraction
enter value
replace(value,"http://www.wikidata.org/entity/", "")
 On Wikidata_id column: Edit column -> add column
by fetching URLs -> if you want to query birth dates
enter value «P569»
("https://tools.wmflabs.org/openrefine-
wikidata/en/fetch_values?item="+value+"&prop=P56
9") -> name column «date_of_birth_Wikidata». The
result is in JSON.
 Clean data by -> edit cells -> transform -> for value
enter forEach(value.parseJson().values,v,v).join(";")
 Cleaning up a date to show only the year:
datePart(value,'year')

13. Retrieving data from
Wikidata
 Reconcile (how simple is this!!)
 Chose source – Wikidata (in case include
other columns too)
 Start reconciling – record will be
automatically linked to Wikidata (some rest
has to be done manually)
 Use values as identifiers

14. OpenRefine - export
 At the end: export your data set! (Open
Refine does not change your original
data set)
 Single column export -> facet -> chose
facet -> export csv
 Full sheet export -> comma-separated
value
 It is also possible to only export parts of
your sheet.

15. OpenRefine tutorials
 http://openrefine.org/
 https://programminghistorian.org/en/lessons/cleaning
-data-with-openrefine
 https://github.com/miriamposner/get-started-with-
openrefine/blob/master/get-started-with-
openrefine.md
 https://github.com/OpenRefine/OpenRefine/wiki/Doc
umentation-For-Users
 Retrieving data from Wikidata or VIAF
https://medium.com/the-bytegeist-blog/enriching-
reconciled-data-with-openrefine-89b885dcadbb
 There are many more!!

17. Timelines (selection)
 Timeline JS (Northwestern University)
https://news.northwestern.edu/stories/2012
/03/knight-lab-digital-timelines/ (with
examples and spreadsheet)
 Neatline – for Omeka
http://docs.neatline.org/creating-records.html
 Google Timeline
https://www.google.com/maps/timeline?pb
 Office Timelines (for Excel or Powerpoint)
https://templates.office.com/en-
us/Timelines?page=1

18. TimelineJS
With Google Chrome and Google Spreadsheets
 Advantages
 Easy to use for a chronological visualization
 Incorporates maps and images from the web
 Can be incorporated into Websites and
Powerpoints
 Disadvantages
 Limited interactivity
 Only uses images published on the web, not
from own collection

19. TimelineJS
With Google Chrome
 https://timeline.knightlab.com/

 Botticelli spreadsheet:
https://docs.google.com/spreadsheets/d/
1BAg-2_XZM-
Oap1cwQoftBcYjrJYBjXOSNOqdXBwQ
WyY/edit#gid=0
 Botticelli timeline (imbedded link to
website or presentation)

20. Thank you !
Dr. Angela Dressen
Villa I Tatti, The Harvard University Center
for Italian Renaissance Studies / Florenz,
Italy
adressen@itatti.harvard.edu
Discipline Representative for Digital
Humanities at the Renaissance Society of
America (RSA)