---
# System prepended metadata

title: Data Curator
tags: [method, datascape toolkit, toolkit]

---

# Data Curator


Summary
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**Background of method**: The term curation originated as part of museum practice. The various curation roles in a museum relate to two types of practice. These are 1) the identification, procurement and management activities related to the museum collection 2) the selection, organization and presentation of museum objects for display as part of an exhibition. Typical curation activities include:
**IDENTIFY, PROCURE AND MANAGE:**
* **Collection:** Idenitfy and collect museum objects
* **Archiving:** Collecting and storing information related to the object.
* **Preservation:** Anticipate and precent damage to objects.

**SELECT, ORGANISE AND PRESENT**
* **Sensemaking and story constrcution:** create stories about objects and create overarching storylines that relates objects together
* **Present:** present objects in a physcial or virtual space in a way that reflects the museum story, specifying where objects are placed, how they are positioned in space and how people may interact with the objects.
* **Storytelling:** convey story to visitors, e.g thgrough audio tours, informatoin panels, tourguides.
* **Visitor experience:** visitors may experience the museum story in different ways and this may be influenced by a number of factors, such as which order they visit items in, their background knowledge and cultural background.

All of the above are concepts that can also be applied to the act of curating data, in order to convey something about it towards the general public. Data can be collected, archived, preserved, made sense of and presented through stories. When people interact with data, they also bring questions, background knowledge and culture to its interpretation. There have been a number of data curation principles defined also by looking at existing literature around data visualisation and data literacy. The principles are:

1.	Data should be visualised as simply as possible to make it easier to read
2.	Data curation should be as relevant to the audience as possible, personalizing the data if possible 
3.	Storytelling can be used to frame the experiences with the data and guide the points of interaction 
4.	It is possible to affect empathy towards an issue by curating the data 
5.	Start from a representative snapshot of a small part of data from where the audience can expand out, rather than starting with the whole data set and focusing in
6.	Give worked examples of data inquiries and prompt ways to expand upon this towards own interests
7.	Engage people with a data set that they didn’t personally collect by encouraging them to collect their own data and add to it
8.	Provide support for how to ask good questions from data, rather than specific skills for data analysis which vary depending on the context
9.	Combine creative with practical activities

These principles have been used to co-creatively inspire the creation of a set of suggestions for curating data to be used within a co-creation setting or within a participatory story (e.g. [Data Drama method](https://hackmd.io/@datascape/Sy7wbIzvj))


# **Using curator cards**

**Overview**
* Time:  60 minutes
* Purpose: to identify a strategy for curating a dataset for a particular context
* Participants: data storytellers
* Difficulty for facilitators: 1 
* Difficulty for participants: 5 stars 
* Materials you'll need: a set of data curator cards and the dataset/data story that is being told


Description
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The data curator cards are intended to either be used by people who are trying to convey data to a general audience and are deciding the best approach to make the experience engaging and also relatively easy and fun. The curator cards list the following possible approaches:

1.	**Comic strip**: Make a comic strip about the dataset
2.	**Historian:** build a chronological timeline out of a dataset
3.	**Investigation**: start with one core ‘clue’ piece of data and curate data around it
4.	**Mini experiment**: conduct a mini experiment by collecting and analysing data
5.	**News article**: make a news article out of datasets, possibly as a 'reporter from the future'
6.	**Roleplay**: have a Q&A with an ‘expert’ and invite audience questions


![](https://parcos-project.eu/wp-content/uploads/2022/11/Picture1.png)![](https://parcos-project.eu/wp-content/uploads/2022/11/Picture2.png)

Example of a curator card


Once a method is chosen, then there are two possibilities 1) the approach is applied by one or more practitioners, who curate the data and story according to the selected principles and then embed it into a co-cration activity for others to quBoth of these approaches are elaborated for 'comic strip' in the section on [Data Comics](https://hackmd.io/@datascape/SydzZQxBj).

Preparation
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1. Download and print the curator cards from [here](https://parcos-project.eu/wp-content/uploads/2022/11/curator-cards.docx)

Running a session - part 1
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**Steps**
1. Discuss in small groups the data story that is being presented - reflecting on the intended audience and media through which the story will be communicated
2. Pick one of the curator cards and brainstorm how that method might be applied to the data story and how suitable it is
3. Repeat for each card
4. Brainstorm alternative approaches that do not appear on the cards


**Method originators:** Annika Wolff, Natasha Tylosky, Tanvir Hasan


**Further Reading**
[Exploring design principles for data literacy activities to support children’s inquiries from complex data ](https://oro.open.ac.uk/59762/1/IJHCS_accepted.pdf)

###### tags: `datascape toolkit` `toolkit`  `method`
