Task Design for Indonesian Cultural Heritage Data Collection with Crowdsourcing

The existence of cultural heritage (CH) data repository is very important for the preservation and supporting industries related to CH, such as the tourism industry and the creative industry. Since culture belongs to all humans, it can be said that all humans have CH objects or knowledge or experiences that can be shared and collected so that they can be studied, utilized, and developed by the wider community. Recently, it has been known one method called crowdsourcing, which can reach large numbers of people through an internet connection and successfully doing projects together. With these characteristics, crowdsourcing can be used to collect Indonesian CH (ICH) data from people throughout Indonesia and even around the world, who store objects, knowledge, and experiences related to ICH. One important aspect of building a crowdsourcing system is task design. Good tasks are ones that can attract the crowd to participate. Many techniques and methods have been offered by researchers to create a successful task. In this ICH data collection system, 2 goals must be achieved: the collection of data and at the same time the data is organized so that it can be easily retrieved. Besides these 2 goals, the task design must also consider that the available crowd has different backgrounds, such as age, education level, expertise, and digital literacy level. This paper focuses on designing tasks for ICH data collection. Tasks are produced by following a five-step methodology, from identifying the data that has to be collected until designing the workflow of each task. The result is the contribute-edit-verify tasks, grouping based on the complexity of the tasks and the skills required by the task or the skills possessed by the crowd. Both methodology and a contribute-edit-verify group of task can also be applied to other domains that require data collection such as flora and fauna data collection, health data collection for disease management, education data collection, etc.