Research Article
Reuse of Wikimedia Commons Cultural Heritage
Elizabeth Kelly, C.A., D.A.S.
Digital Programs Coordinator
Loyola University
New Orleans, Louisiana, United States
of America
Email: ejkelly@loyno.edu
Received: 23 Apr. 2019 Accepted: 25 May 2019
2019 Kelly. This is an Open Access article
distributed under the terms of the Creative Commons‐Attribution‐Noncommercial‐Share Alike License 4.0
International (http://creativecommons.org/licenses/by-nc-sa/4.0/),
which permits unrestricted use, distribution, and reproduction in any medium, provided
the original work is properly attributed, not used for commercial purposes,
and, if transformed, the resulting work is redistributed under the same or
similar license to this one.
DOI: 10.18438/eblip29575
Abstract
Objective – Cultural
heritage institutions with digital images on Wikimedia Commons want to know if
and how those images are being reused. This study attempts to gauge the impact
of digital cultural heritage images from Wikimedia Commons by using Reverse
Image Lookup (RIL) to determine the quantity and content of different types of
reuse, barriers to using RIL to assess reuse, and whether reused digital
cultural heritage images from Wikimedia Commons include licensing information.
Methods – 171 digital
cultural heritage Wikimedia Commons images from 51 cultural heritage
institutions were searched using the Google images “Search by image” tool to
find instances of reuse. Content analysis of the digital cultural heritage
images and the context in which they were reused was conducted to apply broad
content categories. Reuse within Wikimedia Foundation projects was also
recorded.
Results – A total of
1,533 reuse instances found via Google images and Wikimedia Commons’ file usage
reports were analyzed. Over half of reuse occurred within Wikimedia projects or
wiki aggregator and mirror sites. Notable People, people, historic events, and
buildings and locations were the most widely reused topics of digital cultural
heritage both within Wikimedia projects and beyond, while social, media
gallery, news, and education websites were the most likely places to find reuse
outside of wiki projects. However, the content of reused images varied slightly
depending on the website type on which they were found. Very few instances of reuse
included licensing information, and those that did often were incorrect. Reuse
of cultural heritage images from Wikimedia Commons was either done without
added context or content, as in the case of media galleries, or was done in
ways that did not distort or mischaracterize the images being reused.
Conclusion – Cultural heritage institutions can use this research to focus
digitization and digital content marketing efforts in order to optimize reuse
by the types of websites and users that best meet their institution’s mission.
Institutions that fear reuse without attribution have reason for concern as the
practice of reusing both Creative Commons and public domain media without
rights statements is widespread. More research needs to be conducted to determine
if notability of institution or collection affects likelihood of reuse, as
preliminary results show a weak correlation between number of images searched
and number of images reused per institution. RIL technology is a reliable
method of finding image reuse but is a labour-intensive process that may best
be conducted for selected images and specific assessment campaigns. Finally,
the reused content and context categories developed here may contribute to a
standardized set of codes for assessing digital cultural heritage reuse.
Introduction
Cultural heritage institutions with digital
This study
attempts to gauge the impact that digital cultural heritage
Media Reuse Studies
Media reuse research is still a relatively new field
without standard or widely accepted definitions of use and reuse. The Digital
Library Federation Assessment Interest Group (DLF-AIG) Content Reuse working
group completed a 1-year Institute of Museum and Library Services (IMLS) grant
in 2018 to evaluate the needs and functions of a digital library reuse toolkit,
and in doing so also researched digital library stakeholder interpretations of
use and reuse. While refined definitions of use and reuse by the group are
forthcoming, at this time and for the purposes of this paper reuse will be
defined as “how often and in what ways digital library materials are utilized
and repurposed” and in what contexts (O’Gara et al., 2018). Collection
curators, digital librarians, and archivists find value in assessing the reuse
of their digital collections in order to show the collection’s reach and to
determine who uses collections. This data can then be used to make decisions
about collection development and digitization priorities as well as to negotiate
increases in staffing and funding.
While digital library stakeholders find a great deal of
value in assessing the reuse of their collections, they also find it very
difficult to do. A survey administered by the DLF-AIG Content Reuse IMLS project
team found that only 40% of respondents were gathering reuse data, usually from
social media metrics or citation analysis (O’Gara et al., 2018).
There is also tension between cultural heritage
organizations’ missions to provide access and a desire to maintain control over
collections. Sometimes there are valid and commendable reasons for wishing to
restrict access or mediate use and reuse of digital collections. Digital
content misuse and cultural appropriation are concerns for digital library
stakeholders (O’Gara et al., 2018).
Ethnographic archives, especially those that document the history and cultures
of marginalized populations, prove challenging to determine meaningful impact
beyond simple quantitative metrics such as clicks, likes, and downloads (Punzalan et al.,
2018). Other times, however, archives unnecessarily attempt to control reuse of
their online holdings via restrictive or unclear rights statements (Dryden,
2014).
While published literature about media reuse is still
somewhat limited, the existing scholarship primarily focuses on use and reuse
of specific archival and digital collections, reuse of generalized collections
by scholars within specific areas of study, and reuse of specific types of
media. These studies are often undertaken with the purpose of improving the
services and technological infrastructure that make library and archival
collections reusable by researchers. Studies involving focus groups,
observational research, and citation analyses have evaluated the reuse of
archival images by historians, archaeologists, architects, and artists
(Beaudoin, 2014; Harris & Hepburn, 2013). Additional researchers, after
creating or using digital media collections in their own work, have advocated
for the creation of open-licensed digital collections of geology and film in
order to enhance the research process for students and scholars alike
(O’Sullivan, 2017; Rygel, 2013).
The reuse of digital cultural heritage media on social
media platforms has received increasing attention in the scholarly literature
over the course of the last decade. As noted in one study, “our data indicate
that everyday users are repurposing digital content in ways that are meaningful
to them, and they are acknowledging and fulfilling personal interests. These
users are also sharing this content through a variety of environments on the
Web, including popular social media platforms, blogs, and personal Web sites”
(Reilly & Thompson, 2017). Social media platforms like Pinterest, which
allow users to curate personal collections of images, blog posts, and other
media from the web, have an “archival shape” due to their infrastructure that
captures the provenance, or original source, of the item, making such platforms
rich for analysis by media reuse researchers (Summers, 2019). Examples of
cultural heritage media reuse could include images downloaded from digital
library collections and uploaded onto a Pinterest Pinboard, as well as those
reproduced in commercial projects like artwork or included in official
government reports (Thompson & Reilly, 2017). Reuse of digital cultural
heritage media on Wikimedia Commons, Wikipedia, and other Wikimedia Foundation
projects has also received scholarly attention in the last year (Kelly, 2018;
Morley, 2018).
One of the most widely documented methods for evaluating
digital image reuse involves RIL services such as Google images or TinEye, in which an image is either uploaded or an
originating URL is input to the search platform and then duplicates and similar
images are found online. RIL studies have been performed on images from NASA,
academic digital libraries, the Library of Congress, and the British National
Gallery (Kelly, 2015; Kirton & Terras, 2013; Kousha et al.,
2010; Reilly & Thompson, 2014; Reilly & Thompson, 2017). In all of
these studies, after duplicate images were found online, the context and
purpose in which the images were reused was analyzed in order to determine who
uses digital cultural heritage images and for what objective.
Cultural Heritage,
Wikimedia, and Impact
A ready-made platform for sharing digital cultural
heritage media and encouraging reuse can be found in Wikimedia Commons
(commons.wikimedia.org), the Wikimedia Foundation’s repository for photographs,
artwork, video, sound, diagrams, and more. Many cultural heritage institutions
have developed programs to upload their digital media to Wikimedia Commons and
enhance Wikipedia articles with links to their collections and finding aids in
order to increase traffic to their websites and repositories, typically with
impressive results (Kelly, 2018). Digital cultural heritage media is added to
Wikimedia Commons in a few ways:
●
Cultural heritage
institutions upload media from their own existing digital collections;
●
Cultural heritage
institutions upload media directly to the Commons, especially in the case of
smaller institutions without existing digital repositories;
●
Cultural heritage
institutions and users upload media to other repositories or websites, such as
Flickr and the Internet Archive, that are then crawled by bots and added to the
Commons;
●
Users upload media
from cultural heritage institution digital collections;
●
Users make their
own digital reproductions of cultural heritage collections (for example,
photographing a painting in a museum, or a document in an archive) and then
upload them to the Commons.
Wikimedia Commons provides user guidelines on how to
reuse media from the Commons on Wikimedia platforms as well as outside of the
Wikimedia landscape (Commons:First
steps/Reuse, 2019; Commons:Reusing content, 2018; Commons:Simple media reuse guide, 2018). But just as
digital library stakeholders struggle to assess reuse of the media in their own
repositories, Wikipedia editors and authors, or Wikipedians,
struggle to assess reuse of projects, articles, and media from Wikimedia
Foundation programs. Denny Vrandečić points out that
readily available use metrics do not always show what is valuable or important,
and instead “we should focus on measuring how much knowledge we allow every
human to share in, instead of number of articles or active editors” (2014).
Another Wikipedian argues that "The sum of human
knowledge" is not the same concept as "the sum of what everyone is
googling today" and that reach, importance, diversity and content gaps,
uniqueness, and quality are all necessary primary measures of impact for the
Wikimedia movement (User:The land, 2018). The
Wikimedia Foundation “Supporting Commons contribution by GLAM institutions”
research project (GLAM standing for Galleries, Libraries, Archives, and
Museums) noted that for cultural heritage organizations, “donating media to
Commons is a means to an end. GLAM organizations and the volunteers who work
with them want to know the media they upload is being used, and to be able to
evaluate the impact of their donations against institutional goals” (Research:Supporting Commons
contribution, 2018).
Research Questions
This study attempts to answer the following questions
with the hopes of providing concrete strategies for assessing collection reuse
to cultural heritage institutions:
- What is the
content of cultural heritage images found in Wikimedia Commons?
- What content
gets reused most often, and where?
- Do reused
cultural heritage images from Wikimedia Commons carry license or attribution
information with
Research Methods
A list of cultural heritage repositories, including
museums, historical associations, and academic archives, among others, was
generated from the archival discovery tool ArchiveGrid,
and a random number generator was used to pull a sample of 66 institutions from
the list for inclusion in this study. Searches were conducted over a two-week
period for
A total of 308
Wikimedia Commons includes wiki reuse information on the
record page for uploaded media; the number of instances of reuse, both on
Wikimedia Commons and on other wikis, was noted for each object (see Figure 1).
Figure
1
Screenshot
of Wikimedia Commons file usage for “Hume Spring (c.1900) owned by Frank Hume
(pictured far right).jpg” (https://commons.wikimedia.org/wiki/File:Hume_Spring_(c.1900)_owned_by_Frank_Hume_(pictured_far_right).jpg).
_owned_by_Frank_Hume_(pictured_far_right).jpg){kind=link}
Then each
Figure
2
Screenshot of Google images result with multiple sizes.
For each image, a number of elements were recorded. These
included:
●
Repository Name
●
Search Term
●
Wikimedia Commons
result URL
●
Original Medium of
Reused Media
●
Content of Reused
Media
●
Wikimedia Licensing
●
Reuse URL
●
Reuse Context
(Narrow)
●
Reuse Context
(Broad)
●
Reuse License and
Attribution
●
Reuse License
(Categorized)
●
License
Compatibility
●
Notes
Most of the elements only required simple analysis of
frequency counts. For elements with a greater level of subjectivity, such as
“content of reused media” and “reuse context,” the content analysis method was
used to examine each object, label it, and then categorize the labels into
broader themes. Content analysis is a quantitative research method used to
“examine large amounts of data in a systematic fashion, which helps to identify
and clarify topics of interest” (Drisko & Maschi, 2015, pp. 25). Here, codes or categories were
developed inductively, or without a prior scheme, rather than deductively, as
reuse research is still in its infancy and existing codes and theory are
diverse and not yet synthesized. However, it should be noted that content
analysis of some type was conducted in all of the RIL studies previously
mentioned, so the potential for integrating codes and developing a standard set
for assessing cultural heritage via RIL may be a possibility in the future. In
this study, the websites featuring Wikimedia Commons digital cultural heritage
From 171 digital cultural heritage Wikimedia Commons
Approximately 5% of reuse cases from the total uncleaned
data set, and 51% of the cleaned data set were associated with Wikimedia’s
projects. This includes reuse on other Wikimedia Commons pages like galleries
or featured images; reuse on other Wikimedia projects, like Wikipedia articles
and Wikidata; reuse by wiki mirror sites, or exact
replicas of wiki projects hosted at different URLs; and reuse by wiki aggregators,
or sites that pull content straight from Wikimedia and repurpose it for
readability, content curation, usability, or other reasons (such as Wikiwand and WikiVividly). While
wiki aggregator and mirror results were found through
Google images, they weren’t considered to be true examples of reuse as they
simply copied entire Wikipedia articles or Wikimedia Commons galleries without
providing any additional context or value to the original Wikimedia Commons
object.
Table
1
Reuse Results for Wikimedia Commons Digital Cultural Heritage
|
Wiki
results |
|
|
Result
Type |
Count |
|
wiki |
611 |
|
wiki
aggregator |
158 |
|
wiki mirror
site |
9 |
The subject matter of the digital images analyzed from
Wikimedia Commons was coded, and then Google images results were analyzed to
determine themes in what reusers of digital cultural
heritage
Table
2
Content of Reused Wikimedia Commons Digital Cultural Heritage
|
Reuse
Content (not including wiki reuse) |
Count |
Percent |
|
notable people |
338 |
31% |
|
people |
251 |
23% |
|
historic event |
157 |
15% |
|
buildings and
locations |
103 |
10% |
|
historic
object |
34 |
3% |
|
technology |
33 |
3% |
|
map |
32 |
3% |
|
animals |
32 |
3% |
|
landscape |
25 |
2% |
|
sports |
24 |
2% |
|
other |
56 |
5% |
a “Other” includes fibre art,
flowers and plants, outdoor photography, religious iconography, abstract art,
diploma, currency, literature, and yearbook photos.
Similar results can be found in analyzing just the reuse
of these
Table
3
Content of Reused Wikimedia Commons Digital Cultural Heritage
|
Reuse
Content (wiki only) |
Count |
Percent |
|
notable people |
386 |
36% |
|
people |
159 |
15% |
|
buildings and
locations |
110 |
11% |
|
historic event |
96 |
9% |
|
sports |
52 |
5% |
|
technology |
42 |
4% |
|
animals |
33 |
3% |
|
book cover |
28 |
3% |
|
fiber art |
26 |
2% |
|
currency |
24 |
2% |
|
landscape |
23 |
2% |
|
otherb |
83 |
8% |
b “Other” includes historic
object, outdoor photography, map, advertisement, diaries and personal letters,
literature, flowers and plants, religious iconography, abstract art, bookplate,
diploma, data, and library card.
Finally, for comparison’s sake, the following table shows
the percentage of instances for each reuse content category found within the
initial cleaned data set. This shows a strong correlation between the number of
Table
4
Comparison of Wikimedia Commons
|
Reuse Content
Category |
Occurrences in Data
Set (before reuse analysis) |
Reuse Occurrences (wiki and Google images) |
|
people |
38% |
19% |
|
notable
people |
24% |
34% |
|
buildings
and locations |
7% |
10% |
|
technology |
4% |
4% |
|
sports |
4% |
4% |
|
animals |
4% |
3% |
|
historic
event |
3% |
12% |
|
landscape |
2% |
2% |
|
otherd |
13% |
13% |
c Table’s percentages do not sum
to 100% due to rounding up small percentages,
d “Other” includes outdoor
photography, advertisement, book cover, historic object, map, diaries and
personal letters, literature, religious iconography, data, fibre art, currency,
flowers and plants, abstract art, bookplate, diploma, library card, and yearbook
photos.
The original medium of the reused object was also
documented and analyzed. Photographs accounted for nearly three quarters of all
reuse.
Table
5
Original Medium of Reused Images
|
Original
Medium of Reused Media |
Count |
Percent |
|
photograph |
1104 |
72% |
|
two-dimensional
artwork |
139 |
9% |
|
illustration |
56 |
4% |
|
three-dimensional
artwork |
54 |
4% |
|
map |
44 |
3% |
|
ephemera |
42 |
3% |
|
exhibit |
34 |
2% |
|
monograph |
26 |
2% |
|
Othere |
34 |
1% |
e “Other” includes document,
slide, drawing, newspaper, and three-dimensional object.
When looking at reuse outside of wiki products, there are
again clear trends in how and where digital cultural heritage
Table
6
Context of Reuse of Wikimedia Commons Digital Cultural Heritage
|
Google
images reuse context |
Count |
Percent |
|
social |
371 |
49% |
|
media
galleries |
137 |
18% |
|
news |
133 |
18% |
|
education |
80 |
11% |
|
profiles of
people and places |
14 |
2% |
|
commerce |
9 |
1% |
|
events |
5 |
1% |
|
web design and
development |
5 |
1% |
|
tourism |
1 |
0% |
fTable’s
percentages do not sum to 100% due to rounding up small percentages.
Slight variances in what subject matter is most viable
for reuse on what type of websites can be found as well. While
Figure
3
Reuse context of Wikimedia Commons digital cultural heritage content found by
Google Images (excerpt).
Wikimedia provides ample guidelines on how wiki media
should be shared from Wiki platforms, including providing appropriate
attribution if required by the media’s license. Of the sample set analyzed for
this study, a mere 40 results out of a possible 755 non-wiki reuse instances
had any type of license or copyright statement available. And in comparing the
licenses provided in reuse instances, there were significant discrepancies
between these and the licenses on Wikimedia Commons. “Compatible” refers to
instances where the Wikimedia Commons object and the reused object had the
exact same license. The “semi-compatible” designation was used when slight
differences occurred, for example, the Wikimedia Commons license listed CC
BY-SA 3.0, whereas the reused instance noted an updated CC BY-SA 4.0 license.
The remaining “incompatible” results referred to wholly different licenses
being applied, such as Wikimedia Commons marking an image as
Table
7
Compatibility of Reuse Licenses Found by Google Images with Original Wikimedia
Commons License
|
Wikimedia
and non-wiki reuse license compatibility |
|
|
Compatibility
evaluation |
Count |
|
compatible |
24 |
|
incompatible |
8 |
|
semi-compatible |
8 |
Finally, a few other unexpected discoveries emerged in
this analysis. While only 40 reuse instances provided some sort of license, 147
results, or 19% of non-wiki reuse results at least included some sort of
credit, such as the name of the work and the cultural heritage institution that
held it. Of these, 50 credited Wikimedia Commons or Wikipedia in some way, or
linked back to the original image on Wikimedia Commons.
Also, in analyzing the reuse context of the digital
cultural heritage
●
A news article that
uses an unlabeled photo of the 1966 UT Austin Tower shooter Charles Whitman’s
gun to illustrate new laws for gun amnesty in Canada;
●
A blog post that
mislabels an image of Gerald Ford as Richard Nixon;
●
An image of railway
workers laying the last rail of the Union Pacific Railroad in 1869, used to
illustrate minimum wage.
Overall, reuse of cultural heritage
By identifying themes in what type of digital cultural
heritage is reused online and where, we can begin to pinpoint possible
strategies for cultural heritage institutions to maximize the impact of
This study also does not attempt to measure the
notability of specific cultural heritage institutions or collections. Previous
scholarship documenting cultural heritage institutions voluntarily donating
digital
The research reported here shows that cultural heritage
institutions have cause for concern about reuse of their collections without
attribution. Only 9% of Creative Commons-licensed
What cultural heritage institutions can begin to do with
this research is to determine where their digitization efforts may have the
most impact and alignment with institutional goals. The DLF-AIG IMLS grant
project found that digital library practitioners had different priorities for
where they hoped their digital resources would be reused; for example, some
institutions might find more value in reuse by nationally-recognized news
organizations, others by students and scholars, still others by community
groups (O’Gara et al., 2018). These
goals will vary depending on the type, size, and mission of the institution the
practitioner represents. By beginning to understand what types of Wikimedia
Commons digital cultural heritage content are reused most often on what types
of websites, practitioners can strategize which of their collections and
objects they should focus on donating to Wikimedia Commons to reach the user
communities they are most interested in connecting with.
Figure
4
Relationship
between number of images searched and number of reuse results per institution.
While great care was taken in developing and analyzing
the codes used for identifying content and context of reuse
This paper contributes to media reuse literature, and to
RIL research in particular by furthering understanding of what content
categories are most likely to be reused and where, both within Wikimedia
Foundation projects and on the wider web. Digital library practitioners should
use the results of this study to develop digitization strategies that
prioritize content attractive to the types of websites where reuse would most
align with their institutional missions. This research also emphasizes the need
for better education and infrastructure related to licensing and rights for
digital content reuse, as reused digital cultural heritage
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Appendix A
List of Cultural Heritage Institutions with Reuse Results
|
Cultural
Heritage Institution |
Total
Reuse |
Wikimedia
Commons |
Google
Image |
|
Alexandria Library |
8 |
7 |
1 |
|
Amon Carter Museum |
49 |
28 |
21 |
|
Arizona State Museum |
41 |
26 |
15 |
|
Austin Public Library
- Austin History Center |
205 |
56 |
149 |
|
Bard College |
12 |
9 |
3 |
|
Barnes Foundation |
16 |
9 |
7 |
|
Central Michigan
University - Clarke Historic Library |
6 |
5 |
1 |
|
Centre College - Grace
Doherty Library |
28 |
27 |
1 |
|
Chula Vista Public
Library |
3 |
3 |
0 |
|
Cincinnati Art Museum |
14 |
6 |
8 |
|
Cleveland Public
Library |
22 |
20 |
2 |
|
College of Charleston |
15 |
11 |
4 |
|
College of Physicians
of Philadelphia |
1 |
1 |
0 |
|
College of William and
Mary |
15 |
12 |
3 |
|
Computer History
Museum |
67 |
41 |
26 |
|
District of Columbia
Public Library |
22 |
10 |
12 |
|
Folger Shakespeare
Library |
16 |
11 |
5 |
|
Forest History Society |
9 |
6 |
3 |
|
Fresno City and County
Historic Society Archives |
6 |
5 |
1 |
|
Georgetown University |
76 |
36 |
40 |
|
Gerald R. Ford Library |
137 |
40 |
97 |
|
Hagley Museum and
Library |
17 |
8 |
9 |
|
Idaho State University |
9 |
9 |
0 |
|
Indiana University |
14 |
5 |
9 |
|
Lamar University |
5 |
4 |
1 |
|
Missouri State
University |
35 |
7 |
28 |
|
National Gallery of
Art |
8 |
1 |
7 |
|
Oakland Museum |
31 |
12 |
19 |
|
Princeton University -
Firestone Library |
13 |
6 |
7 |
|
Richmond Public
Library |
3 |
3 |
0 |
|
Saint Mary's College |
7 |
4 |
3 |
|
Santa Clara University |
6 |
4 |
2 |
|
Seton Hall University |
4 |
4 |
0 |
|
Smithsonian
Institution Archives |
51 |
44 |
7 |
|
Stanford University
Archive |
16 |
14 |
2 |
|
Tennessee State
University |
35 |
11 |
24 |
|
The Henry Ford -
Benson Ford Research Center |
7 |
0 |
7 |
|
Trinity College |
4 |
4 |
0 |
|
University of Denver |
5 |
2 |
3 |
|
University of Idaho |
22 |
15 |
7 |
|
University of
Louisiana at Lafayette |
18 |
3 |
15 |
|
University of Michigan
- Bentley Historic Library |
40 |
29 |
11 |
|
University of
Missouri, Kansas City |
4 |
0 |
4 |
|
University of North
Florida |
34 |
5 |
29 |
|
University of Pittsburgh |
13 |
11 |
2 |
|
University of Puget
Sound |
25 |
22 |
3 |
|
University of Texas at
Austin |
102 |
52 |
50 |
|
Winthrop University |
1 |
0 |
1 |
|
Wisconsin Historic
Society |
43 |
27 |
16 |
|
Yale Beinecke Rare
Book and Manuscript Library |
179 |
93 |
86 |
|
Yale University -
Manuscripts and Archives |
14 |
10 |
4 |
Appendix B
abstract art: fine art lacking recognizable visual
references
advertisement:
animals: non-human biological organisms from the kingdom
Animalia
book cover: the front of a published monograph
bookplate: identification labels used by monograph owners
buildings and locations: architectural structures,
cityscapes, towns, and non-landscape locales
currency: representations of paper or coin money
data: tables and figures used for illustrative purposes
to convey information
diaries and personal letters: manuscript materials such
as personal writings and correspondence
diploma: paper documenting graduation from some level of
education
fibre art: fine art
composed of natural or synthetic components like yarn, thread, and string;
examples include tapestries, rugs, and embroidery
flowers and plants: multicellular organisms from the
kingdom Plantae
historic event: documentation of occurrences with
remarkable significance
historic object: documentation of objects with remarkable
significance
landscape: natural scenery
library card: identification used to access items at a
library
literature: written works, usually published monographs
map: visual depiction of geographic spaces
notable people: individuals identified by name due to
their cultural or historical recognizability on Wikimedia Commons
outdoor photography: camera images of the outdoors
people: primarily unidentified individuals primarily or,
in a few cases, identified because their images came from yearbook scans but
were otherwise not to be found identified elsewhere online
religious iconography: fine art created for the specific
purpose of use in or by religious organizations and individuals
sports: athletic events, spaces, or people associated
with specific athletic activities
technology: machines and systems used for carrying out
technical processes
yearbook photos: images captured for school publications
documenting an academic year
Appendix C
Reuse Context Codes
|
Narrow Codes |
Definition |
|
|
commerce |
art
store DVD reproduction
for purchase trade
catalogue |
websites
whose primary purpose is the sale of commercial products |
|
education |
academic
website dictionary digital
exhibit digital
library eBook encyclopedia Google
Arts & Culture page infographic institution
website on
this day presentation quiz quote
website report research
guide slide
deck timeline tutorial video |
reference
resources such as dictionaries, encyclopedias, research guides, digital
libraries and exhibits, timelines, presentation slides, infographics, “on
this day” websites, and academic websites |
|
events |
event
post movie
listing |
news
or other websites with calendar or public relations-related announcements
about specific events like workshops, classes, performances, and exhibits |
|
media
galleries |
clip
art gallery Flickr media
gallery stock
image gallery |
websites
made up of manually or automatically-generated collections of images |
|
news |
article magazine news
article newsletter press
release |
online
publishing by television, online, radio, and print news organizations, as
well as magazines and other websites for current events |
|
profiles
of people and places |
city
or company profile person
profile |
generalized
biographies or profiles of cities and towns found on specialty topic,
non-educational websites |
|
social |
blog discussion
board Facebook Google
Plus journal message
board pin
board Pinterest reddit song
lyrics annotation site Tweet Twitter
aggregator |
social
networks (Facebook, Pinterest, Twitter), blogs, discussion boards, online
journals, and other web 2.0 websites whose primary purpose is user-generated
content and interaction |
|
tourism |
travel
site |
travel
websites |
|
web
design and development |
keyword
trends |
tools
for website development such as identifying keyword trends for Search Engine
Optimization |