Crowdsourcing and digital heritage

Many heritage institutions have a certain experience with crowds providing for finances, information, labor, or ideas in a small scale through the long history of working with volunteers. Adopting a crowdsourcing approach as we now know it involves a larger number of respondents at a much higher speed. For this, constraints to adopt a crowd approach include issues of validating contributions (Ridge, 2013) or the fear of undermining the authority of heritage experts who want to protect a certain exclusivity of the sector (Abbing, 2019). Further, while digital networked technology promises to facilitate referencing by linking to primary data (including heritage collections), the challenges of dealing with the nature of heritage data, characterized by being fuzzy, heterogeneous, uncertain, and interpretative, have not been solved (Blanke et al., 2012).

The issue of multiple objectives may also be identified. While for-profit firms may call the crowd to lower costs of production or reduce risk of product uncertainty as in the case of the creative industries (Dalia Chiesa & Handke, 2020), heritage institutions may seek to engage consumers. Heritage services are often driven by multiple goals, including the preservation and development of cultural heritage, advancing education, providing entertainment, or increasing welfare (Towse, 2019), all of which may be pursued during a crowdsourcing project. Similarly, consumers may want to engage with heritage content for various reasons. Participants in heritage crowdsourcing are motivated to take part in a history- and archaeology-related project; to learn about the subject; to connect with the institution; to develop skills, for fun, out of curiosity; to help out; to contribute to knowledge production; and to learn more about a personal cultural background (related to identity forming) (Bonacchi et al., 2019).

Involving the crowd is inherent to intangible heritage and most forms of culture. In the visual arts, Spencer Turnick can serve as prime example of volunteers contributing as models for a group photograph, including the 18,000 nudes posing at Mexico City’s central square.¹⁰ A film example can be found in Peter Jackson’s call of 20,000 volunteers to contribute to the sound of the org armies in the Lord of the Rings: Two Towers (Prpic et al., 2015). The fashion firm ModCloth has launched several crowdsourcing projects in exchange for discounted purchases, including calling the crowd to contribute images modeling clothes, to suggests clothes based on body types, to vote the best drafts to be produced as final designs, and to provide sketched ideas for new designs, which were in turn voted by the same crowd and adapted into the following season (Estelles-Arolas & Gonzalez-Ladron-De-Guevara, 2012). Creative industries crowdsourcing regularly involve larger crowds for content generation, ratings, and new ideas, which do not compare to most heritage crowdsourcing projects, receiving support from a few hundred individuals and rarely surpassing the five thousand (Carletti et al., 2013).

An overview of projects in the heritage field that tap into the crowd using digital technologies has not yet been inventoried and has only recently attracted broad attention (for an overview of a selection of projects from the early 2010s, see Ria, 2014). A few projects with large consortia have been financed by public money in the last decade. Examples include 3D-ICONS, a three-year project for the documentation of archaeological monuments and historic buildings to feed Europeana;¹¹ The Scottish Ten, a project to document five international heritage sites to help with their conservation and management;¹² or the Million Image Database, a repository of heritage images to document the past and to explore the use of 3D imagery.¹³

Crowdsourcing projects specific to advance digital collections of heritage institutions, the GLAMs, have emerged to explore alternative sources of labor, and sometimes funds, for the digitization production process. A recent European survey estimated that museums spend a yearly median €10,000 (mean €111,000) in digital activities and allocate an average of five paid staff and two volunteers toward digital collection activities. Management (e.g., licenses, online services) make up about 40% of the structural costs, digital preservation and archiving make up about 35% of the costs, and the rest is allocated toward user outreach, usage analysis, and editorial work. Eighty-nine percent of the budget is internally generated, and so far, it has been estimated that 31% of museum collections have been digitized (Nauta et al., 2017).

Invariably, availability of online collections increases their use, yet production and proper online publication remain a challenge. To give an example: one large city archive has 32 kilometers of materials, which would represent about 224 million scans (there are roughly 7,000 scans per meter). At an output of 10,000 scans per week, which is quite an impressive mass digitization process, it would take the archive 431 years to digitize

Crowdsourcing 107 their entire collection. Digitization started in 2001 and continues to improve, speeding up the process to about two million scans per year, or 20,000 scans per week, or 30 scans per minute. This included 6,000 scans requested by 1,260 different consumers (scan on demand program). Since 2001, the archive has digitized six million scans (Holtman & Van Zeeland, 2019). However, digitized material can only be accessed when its contents can be searched for and identified; a digital image in itself is not enough. The city archive decided to call the crowd to support the identification of important information, such as dates, names, places, and type of document. With a grant of €150,000 from the Mondriaan Foundation, the Amsterdam City Archive collaborated with a software partner, Picturae, to develop the crowdsourcing software, which is currently used by many more heritage institutions to annotate digital collections. To ensure quality, every document data element is entered twice (SAA, 2013). The archive commissioned the creation of an online program called Many Hands (Vele Handen) to coordinate crowdsourced annotations and in the first 1.5 years, over 1.6 million objects were identified with name, birth place, and date of birth twice, representing a full-time staff working for a period of over 18 years (SAA, 2013).¹⁴ While the onsite access to the archives has decreased by 66% in the past ten years, online access continues to increase (from zero to 18,000 yearly requests in the same period) (Duran, 2019).

Besides tapping into the crowd to advance the digitization of collections by providing financial resources or labor to enhance existing collections, crowdsourcing projects can support public engagement and can lead to developing new collections: for instance, to document history as a form of intangible heritage (Carletti et al., 2013). The main crowdsourcing forms in the heritage field are crowdfunding (acquiring funds to finance a project), idea generation projects (for new products and services), aggregated input projects (generally to speed digitization projects, some of which through micro-tasks), and open collaboration projects (for instance to populate a digital collection). We follow with a discussion of each with examples (summarized in Table 7.2).

Table 7.2 Typology of crowdsourcing in heritage projects