Location
Hilton Waikoloa Village, Hawaii
Event Website
http://hicss.hawaii.edu/
Start Date
1-3-2018
End Date
1-6-2018
Description
Data literacy is the ability to use data productively and to think about it in a critically reflective way. However, can its complexity really be broken down to only this? Data literacy is one of the most important skills in the 21st century for organizations, employees, and citizens. We present a data literacy maturity model (DLMM) that was developed in the context of non-governmental organizations (NGOs). Based on the development of a preliminary maturity model, action design research (ADR) is used to develop the model throughout three iteration phases. The main contribution is a data literacy maturity grid that describes 11 data literacy competencies on four competence levels that is complemented by a self-assessment tool. The proposed maturity model should enhance the understanding of the required skills that are needed to kick off data projects, identify strengths and gaps, and thus empower to plan future data practices in accordance with predefined goals.
Doing Good with Data: Development of a Maturity Model for Data Literacy in Non-governmental Organizations
Hilton Waikoloa Village, Hawaii
Data literacy is the ability to use data productively and to think about it in a critically reflective way. However, can its complexity really be broken down to only this? Data literacy is one of the most important skills in the 21st century for organizations, employees, and citizens. We present a data literacy maturity model (DLMM) that was developed in the context of non-governmental organizations (NGOs). Based on the development of a preliminary maturity model, action design research (ADR) is used to develop the model throughout three iteration phases. The main contribution is a data literacy maturity grid that describes 11 data literacy competencies on four competence levels that is complemented by a self-assessment tool. The proposed maturity model should enhance the understanding of the required skills that are needed to kick off data projects, identify strengths and gaps, and thus empower to plan future data practices in accordance with predefined goals.
https://aisel.aisnet.org/hicss-51/os/org_issues_in_business_intelligence/3