Curation
SADIA KHAN
University of South Carolina, USA
IBRAR BHATT
Queen’s University Belfast, UK
Curation is a practice of information gathering, management, and presentation.
Whether carried out manually or computationally, the key feature of curation is the
filtering process by which information is selected and shared. Through this process,
curation intrinsically links information to knowledge and meaning-making. By making
evaluative judgments about the validity and relevance of information, curatorship
transforms information into knowledge based on awareness or belief about what
is justifiably true. Thus, through the filtering process, knowledge can be said to be
a by-product of curation. Because it links information to knowledge creation, the
practice of curation is an important focus of inquiry in the fields of media literacy and
education, as well as within the social sciences. The power of curation to inform and
direct a conversation around a topic is another feature which makes it eminently useful.
Curation and controversy
Traditionally, curation has been the work of museum and library specialists, carefully
and prodigiously selecting relevant materials to develop collections. Today, everyday
acts of curation can look like selectively sharing content online, creating and maintaining a profile on any of the various social network platforms, and searching and
compiling information for reporting. In each case, acts of information management
create or add to a narrative around a topic. Curation describes the practices of
harnessing preexisting content, transforming it through the application of criteria
which assess and promote belief, and then directing the resultant packet of filtered
information to a new audience.
In addition to library and media studies, online practices of curation have been discussed within the fields of information theory, literacy studies, and computer science.
Curation’s relevance across multiple fields stems from its particular characteristic of
being able to tell a story through the choice of carefully selected and presented artifacts,
the compilation of which collectively conveys meaning and knowledge not contained
in the individual pieces of a collection. In this way, curation is an act of knowledge
creation – the creation of a narrative which justifies its own relevance. The by-product
of this as “created knowledge” makes curation a powerful tool, and also a topic of
controversy. It also brings to bear the difference between human and computational
The International Encyclopedia of Media Literacy. Renee Hobbs and Paul Mihailidis (Editors-in-Chief),
Gianna Cappello, Maria Ranieri, and Benjamin Thevenin (Associate Editors).
© 2019 John Wiley & Sons, Inc. Published 2019 by John Wiley & Sons, Inc.
DOI: 10.1002/9781118978238.ieml0047
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forms of curation. Indeed, from these two modes of curation arise variances and
disruptions in how curation is utilized and applied.
While they both perform the same task, manual (human) curation and computational (algorithmic) curation have different strengths, weaknesses, and consequences.
Computers and algorithms manage, filter, and report data more efficiently and
thoroughly than humans can do manually. On the other hand, human processing
offers impressionistic judgment, which is a defining factor of manual curation. In both
cases, the reporting of filtered and selected information creates a unique narrative with
its own meaning and its own reality.
Variations of curation, however, can not only look different, but also carry different
implications. At its best, curation can have the effect of a masterful presentation which
is well sourced and infused with creativity, utility, and meaning. It can present itself
through products like innovative and life-saving research aided by a collaborative effort
of scholars whose work is converged in a scientific report. Conversely, some forms of
curation can create polarizing “bubbles” in which the only information one receives
is filtered according to specific criteria set by the very consumers and/or producers of
that information. In this scenario, the resultant “echo chamber” inevitably amplifies
certain narratives while silencing others through the recirculation of partisan information – limiting the opportunity for a person to encounter conflicting views. Examples
include Facebook friends’ lists and Twitter feeds in which disagreeable information
can be purged through “unfollow” and “block” options. Similarly, algorithmically
determined newsfeeds decide on the information which is presented to a user based
on personal habits, preferences, and usages. In both cases, filtered bubbles are created
and maintained through a set of decisions and actions. The difference is in the nature
of the filtering mechanisms.
Since curation is about information management, it becomes important to question
who manages these filters. This question is critical because inherent in the filtering
process are things like subjective evaluation, purpose, editorialization, summary,
reduction, and approximation. A curated packet of information that results from this
process is, therefore, imbued with these determinations.
To be a curator of information, awareness and discernment of the mediating factors
is imperative – as is the ability to discriminate between sources and gauge authenticity
and validity. Indeed, this is a critical requirement for the effective management and
assessment of the troves of data available online, and also a requirement for detecting
ineffectiveness and misguidance in what has been called “pre-curated” data (Bhatt,
2017) – or data which has already been filtered with some particular justification
parameters.
The defining factors of curation
The use of information communications technologies (ICTs) has become ubiquitous in
everyday life. As the amount of information on any topic immediately available to us
has grown exponentially, and as we increasingly conduct our affairs online, much of the
data that inform our life, behavior, and decisions are mediated by computers and the
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Internet. The consequences of this relate to curation; as such, curation has now come to
encompass multitudinous and increasing forms of data-managing behavior. Curation
as a term has therefore evolved to describe what is often done in digital environments
and online in social, personal, educational, and commercial spaces.
This has been examined and documented in each of these areas through the study
of such things as “remix” practices in music production, sharing content on social
media, and writing and literacy in education. Each of these varied tasks involves
curation outlined as: (i) problematizing an issue or topic; (ii) anthologizing and
aggregating information relevant to a topic and enlisting filters to manage it; (iii)
applying subjective, editorial discretion to appeal to and reach a target audience; (iv)
adding value to preexisting content by contributing new or extended meaning and/or
create a new narrative; and (v) presenting that data in the appropriately determined
platform (Bhatt, 2017, p. 120).
Noticeably, computational and human curation are concurrent practices. While content aggregation manifests largely as algorithmically managed data, with little or no
value placed on truth, accuracy, and morality, the remainder of the task lies in the hands
of human curators who have a distinct role in making meanings out of the voluminous amounts of information that would overwhelm us otherwise. This discriminating
behavior is about adding value, making meaning, and inspiring novelty. It is at the heart
of content curation.
Indeed, the notion of meaning-making as a preeminent characteristic of curation is
echoed widely. It is the factor that is most influential in making curation transformative.
Adding meaning or expanding a narrative on a subject extends the relevance of that
idea, that act of creativity, or that literacy event into the future, creating a new narrative,
and, in a sense, a new reality.
This process of recombining preexisting content to fabricate new content has also
been dubbed as “remix” and has been scrutinized for its paradoxically sequacious and
innovative nature (Gunkel, 2016). In their investigation into the remixing practices of
Internet bloggers and fanfiction writing, Lankshear and Knobel (2015) highlight the
myriad social practices and conceptions of engaging in meaning-making which are
enacted by searching, filtering, combining, repurposing, narrating, and sharing. These
practices of creative decoding and encoding of information lend important insights into
curation as a latent form of digital literacy.
Bhatt (2017), working in the field of literacy and education, documented practices
of curation during his investigation into strategies of how college students searched
for information, drew from previous texts, and handled a multitude of textual sources
during their writing tasks. Mihailidis and Cohen (2013) and Barton (2017) also found
similar practices in different contexts.
Mihailidis and Cohen investigated the online practices of students as they filtered
and aggregated online information. Highlighting the need for students to be analytical
and critical in their online life, they suggest a new set of pedagogical approaches which
promote critical thinking and information filtering skills, and are centered around
curation practices. Also examining curation as a digital literacy practice, Barton
explored curation as part of social tagging in the photo-sharing site Flickr. Specific to
how users utilized the tagging feature, he found that curation practices created a story
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not told by the pictures themselves, and not predicted by the site’s designers. All three
of these investigations reveal users/curators as active meaning-makers and agents of
change.
Curators as agents of change
Curation is a subjective and inherently ideological process in which curators select
existing objects to construct their own “truths.” Through this production, curation
becomes a creative expression of re-representation by which a curator can represent
anything from empirical facts to information about oneself in a contextualized way.
Embedded in the narrative that is created are the values of the narrator. In doing this, a
narrator becomes the de facto author over a composition of voices, and by developing
and employing skills which enable agency (Potter & Gilje, 2015), (s)he can also become
an agent of change.
Barton’s study of tagging practices on Flickr (mentioned above) is illustrative of
this – showing how users of a platform perform curation practices agentively. By
strategically recreating their online photo-narratives in order to demand change on the
social media platform, users acted in a manner which was at odds with the intentions
of the site’s developers. Curation practices, therefore, are something that can allow
power to be distributed a certain way. This potential is magnified when considering
that the Internet itself is curated by millions of individual users making individual
choices, effectively binding them together through shared practices.
Certainly, curation has the potential to be powerful. Millions of users coalescing
around a narrative can effect change. This has been seen in social activism movements
like the Occupy Movement, the Arab Spring, and other forms of political populism
where a narrative is crafted, editorialized, shared, and continuously re-crafted – giving
it a new reality when interpreted and acted upon by others.
But not all curation is the same. Where there is re-representation, there can be misrepresentation. And the difference can be as significant as the difference between knowledge creation versus a repeated circulation of misinformation and proliferation of ignorance. The former represents novelty, creativity, and innovation and is arguably the
future of learning and scholarship; the latter, through the aggregation of people within
increasingly partisan networks, has consistently been dubbed by the World Economic
Forum as one of the main threats to human society and modern civilization (2013,
2018).
Discernment
The ability to transform ideas existing as data floating on the Internet into emergent
concepts under the authorship of a curator is certainly significant, and it is aided and
made more complex by the broadness of the Internet and the accessibility of its information. But effective curation requires thought and analysis applied through shrewd
discernment, particularly at the aggregation and editorialization phases. There is simply
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too much information for humans alone to successfully harness. As such, the mediation
of traditional stewardship (e.g., librarians, teachers, and even parents) has now had to
give way to the work of computational curators.
Information searching now requires computer processors, search engines, and other
tools of information management. Additionally, the Internet largely employs machine
learning to organize itself and make things easier to find. While this delegation of
curation work to machines is essential, its self-regulatory management has important
implications. One consequence is that management filters can act as pre-curators
(Bhatt, 2017). Search algorithms greatly affect the information we see and choose, and
for that reason, search and social media executives hold the secrets to their algorithms
tightly. Using data that is pre-curated according to algorithmic predictions about what
we are looking for, or what others want us to see, think, or buy (into), will ultimately
change the outcome of curation. More precisely, computational curation such as this
affects the decisions and recommendations individuals, employers, and governments
make for themselves and society. While this particular kind of curation is considered
by many as more objective due to its mathematical formulation, those formulations are
in themselves intrinsically biased by those who create the algorithms. These concerns
are most often the subject of a nascent field known as critical algorithm studies (see
Further reading), which investigates algorithms as social actors and objects of inquiry.
Algorithms now have increasing power over our lives due to their efficient
information-harnessing and decision-making capabilities, but with an objectivity level
that is questionable at best. For example, in 2009, a US school system applied an algorithmic teacher assessment tool which measured students’ progress and calculated the
extent to which their educational progress (or decline) was attributable to individual
teachers. The teachers with the lowest calculated scores were fired each year, regardless
of any positive evaluations and testimonials that they had received elsewhere. This
demonstrates one of many ethical concerns with reliance on computational data
management.
Equally important is the way computer algorithms promote and “sponsor” information based on corporate revenue maximization. Online search information is seen by
many as objective and is then utilized in compiling investigative or academic reports.
This has consequences. The facade of objectivity is important to recognize and it
becomes important to ask: Who benefits when algorithms rank information? What
role does the promotion or limiting of information have on decision-making, and
why does it matter? Information theorists such as Clay Shirky, Tristan Harris, Luciano
Floridi, and Frank Pasquale all point to the same thing: that credibility and authority
are increasingly conveyed algorithmically.
Mindfulness of this exogenous arbitration is crucial for an effective human
curator. This requires the ability to identify sources and filter information discriminately. But this is a skill set that has not had universal adoption; neither has it been
applied with sufficient proficiency – leaving users susceptible to misguidance online.
A 2016 executive summary research study conducted by Stanford University entitled
Evaluating Information: The Cornerstone of Civic Online Reasoning found that even
students at this highly selective university were largely unsuccessful in differentiating
a reliable and factual website from a propagandist one (Wineburg & McGrew, 2016).
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The investigation saw similar findings across the educational spectrum, from middle
school to college. What this suggests is that so-called digital nativism is not a predictor
of judicious computer use.
Relevant to this problem is the field of study known as “agnotology” (Proctor, 2008).
Agnotology examines how misinformation and ignorance are culturally produced.
Societal ignorance can manifest through neglecting to discern and discriminate
between sources of information (as Wineburg & McGrew discovered), or as a result
of deliberate and sponsored misrepresentation. An example of the latter includes the
tobacco industry’s marketing campaign to nurture doubt and ignorance about the
detrimental health effects of smoking (Proctor, 2008, pp. 11–18). The proliferation of
“fake,” biased, or propagandist news articles which populate users’ curated newsfeeds
on social media sites is also a subject of concern for those studying agnotology and its
relationship with curation.
Addressing these concerns in a 2010 executive summary to the Aspen Institute on
media literacy, Renee Hobbs voiced a need to promote pedagogical tools to advance
the principles of digital and media literacy, including analytical thinking, evaluation,
and creative meaning-making. An informed society must encourage a kind of media
literacy which fosters critical thinking to allow people to make informed decisions and
avoid culturally induced ignorance through misinformation.
The permutations of the (mis-)use and (mis-)management of information
which arise from a discussion of discernment matter when data floating on the
Internet are transformed into works of curation. While the meaning-making and
knowledge-producing aspects are what give curation its power to create and transform
narratives around online content, the information management or data collection
aspect is equally important. Without prudent filtering of information by its credibility,
misinformation becomes infiltrated into curation work, thereby changing the meaning and knowledge that is produced. As misinformation becomes more pervasive,
discernment and discrimination become increasingly difficult – and more necessary.
Addressing matters of information management necessitates updated skills, yet new
requirements in research practices have not been coherently understood and applied
across different fields. Researchers, institutions, and libraries struggle to delineate
information management practices in the face of complexities added by metadata,
algorithms, analytics, and evolving platforms for learning, teaching, and sharing.
What may be needed are standards for information gathering generally and curation
practices specifically which are commensurate with the kind of media literacy to which
Hobbs refers. The field of library and information science (LIS) has an important part
to play here – although the role of librarianship has been made more complex by the
integration of data science into the traditional understanding of information gathering
and preservation. Some of the implications of this hybridization have been discussed
here in terms of media literacy and agnotology. As such, LIS scholars face the added
task of establishing standards for the training of curation practices.
Efforts to address these issues of standardization and training have emerged from
different contexts – mostly educational – with the goal of defining curation practice and
establishing a reliable set of criteria by which to determine if information has been satisfactorily vetted. These efforts have been propelled by the requirements of government
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and university funding agencies and scholarly societies which judge outcomes by
such things as credibility and reproducibility. However, there is still little coordination
between groups working on this effort, and few LIS programs offer advanced classes
or degrees in curation. This is despite researchers and research organizations voicing a
need for training to deal with the evolving demands of research, the changed landscape
of documentation and publication in the digital environment, and the need to comply
with government requirements for the management of federally funded research data.
The opening this leaves is felt throughout the educational spectrum, leaving researchers
and students of all levels ill-prepared for the digital literacy requirements that curation
demands and furthermore uncertain over what will be required to practice meaningful
curation in the future, given the changes in data and information management.
Conclusion
The key feature that makes curation so consequential is the filtering process that links
information to knowledge. When curators apply subjective and evaluative judgments
about the relevance of information for a deliberate purpose, they create new knowledge.
It is this knowledge production that makes curation relevant across multiple fields and
can position curators as potential agents of change.
To capitalize on the potential for novelty and innovation requires both insight and
skill. Because intermediating data filters and agents are not always transparent, such
as in the case of algorithms, curation can easily and unknowingly be reincarnated as
ignorance. How information is collated and circulated needs to be critically examined
as part of any educationally viable approach to digital and media literacy. A critical
approach is particularly important in learning environments where students are
lauded as having “self-organized” their learning via web and computational sources.
It is also pressing in light of recent research which finds that student web users are
failing to sufficiently differentiate between sources of online information based on
reliability.
As society grows skeptical of institutions marketing information and perceived to
be biased and operating under agendas, perhaps it is not merely coincidental that over
the last generation, museums have secured an increasing position of trust in society
(Museums Association, 2013). Museums are acknowledged to have a crucial societal
role that is broader than satisfying individual visitors. The role of museums as guardians
of reliable information is due in large part to the role of museum curators as stewards of
information and producers of knowledge. It is this type of stewardship which is relevant
and required in online environments for the management of abundant information and
knowledge production. Indeed, institutions of education, politics, and commerce can
similarly benefit from securing a position of trust through the employment of prudent
and transparent curation practices.
SEE ALSO: Authorship and Participatory Culture; Critical Information Literacy; Data
Literacy; Digital Literacy; Meaning-Making
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References
Barton, D. (2017). The roles of tagging in the online curation of photographs [Special issue].
Discourse, Context & Media, 22, 39–45. doi: 10.1016/j.dcm.2017.06.001
Bhatt, I. (2017). Assignments as controversies: Digital literacy and writing in classroom practice.
Abingdon, England: Routledge.
Gunkel, D.J. (2016). Of remixology: Ethics and aesthetics after remix. Cambridge, MA: MIT Press.
Hobbs, R. (2010). Digital and media literacy: A plan of action. A White Paper on the digital and
media literacy recommendations of the Knight Commission on the information needs of communities in a democracy. Washington, DC: The Aspen Institute.
Lankshear, C., & Knobel, M. (2015). Digital literacy and digital literacies: Policy pedagogy and
research consideration for education. Nordic Journal of Digital Literacy, 9(4), 8–20.
Mihailidis, P., & Cohen, J.N. (2013). Exploring curation as a core competency in digital and media
literacy education. Journal of Interactive Media in Education, 2013(1), 2. doi: 10.5334/2013-02
Museums Association. (2013). The purposes of museums in society: A report prepared by BritainThinks. London, England: Museums Association.
Potter, J., & Gilje, Ø. (Eds.). (2015). Special Issue: E-Learning and Digital Media: Learners Identity
and Curation, 12(2), 123–258. doi: 10.1177/2042753014568150
Proctor, R. (2008). Agnotology: A missing term to describe the cultural production of ignorance
(and its study). In L.L. Schiebinger (Ed.), Agnotology: The making and unmaking of ignorance
(pp. 1–33). Stanford, CA: Stanford University Press.
Stanford History Education Group. (2016). Evaluating information: The cornerstone of civic online
reasoning [Executive Summary Report]. Retrieved from http://sheg.stanford.edu/upload/
V3LessonPlans/Executive%20Summary%2011.21.16.pdf
Wineburg, S., & McGrew, S. (2016, November). Why students can’t google their way to the truth:
Fact checkers and students approach websites differently. Education Week, 36(11), 22–28.
World Economic Forum. (2013). Digital wildfires in a hyperconnected world. Global Risks 2013:
An Initiative of the Risk Response Network. Geneva. Retrieved from http://reports.weforum.
org/global-risks-2013/risk-case-1/digital-wildfires-in-a-hyperconnected-world/
World Economic Forum. (2018). The global risks report 2018. Retrieved from http://www3.
weforum.org/docs/WEF_GRR18_Report.pdf
Further reading
O’Neil, C. (2016). Weapons of math destruction: How big data increases inequality and threatens
democracy. New York, NY: Crown.
Snyder, I.A. (2015). Discourses of “curation” in digital times. In R.H. Jones, A. Chik, & C.A.
Hafner (Eds.), Discourse and digital practices: Doing discourse analysis in the digital age (pp.
209–225). Abingdon, England: Routledge.
Social Media Collective. (2017). Critical algorithm studies: A reading list. Retrieved from https://
socialmediacollective.org/reading-lists/critical-algorithm-studies/
Sadia Khan is a graduate student studying rhetoric and composition in the Department
of English Language and Literature at the University of South Carolina. As a freelance
writer and editor, she has a diverse portfolio which includes work in digital literacy.
Her academic background additionally includes studies in applied economics and third
world development.
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Ibrar Bhatt is a lecturer in education at Queen’s University Belfast. His PhD was completed at the University of Leeds, and his research interests include digital literacy, writing, and how these relate to language education and knowledge production. He is author
of the book Assignments as Controversies. Digital Literacy and Writing in Classroom
Practice (2017).