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Evaluating a Conceptual Model for Projects Observatories through a Survey

Published: 26 June 2023 Publication History

Abstract

Context: observatories can be understood as information systems that support observation, providing transparency to a given phenomenon or knowledge area, through the collection, processing, storage and sharing of information. Problem: the typological and application areas diversity of the observatories has given rise to the need to develop models that help in the conceptualization and design of these observatories, respecting the specificities of their application contexts. The Model for Projects Observatories (MPO) was proposed as a conceptual model for observatories developed in the context of projects. However, the initial version of the MPO did not go through a formal evaluation process. Solution: from this scenario, this research aims to evaluate and, consequently, evolve the MPO. IS theory: the MPO was proposed from the sociotechnical approach. Methodology: this research has a descriptive character, and its evaluation was carried out through focus groups. The analysis of the results was carried out with a qualitative approach. Summary of Results: from this evaluation, 35 suggestions for improvements to the model were identified. The implementation of these improvements gave rise to a second version of the model that will be presented in this document. Contributions and Impact in the IS area: the main contribution of this article lies in the evaluation and evolution of the MPO, which understands project observatories as information systems to support observation and transparency in the context of projects.

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Jeferson Kenedy Morais Vieira, Ivaldir Honório de Farias Junior, and Hermano Perrelli de Moura. 2021. Model for Projects Observatories : A Preliminary Study. In XVII Brazilian Symposium on Information Systems (SBSI 2021). ACM, Uberlândia, 8. https://doi.org/10.1145/3466933.3466940
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SBSI '23: Proceedings of the XIX Brazilian Symposium on Information Systems
May 2023
490 pages
Publication rights licensed to ACM. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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Published: 26 June 2023

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  1. datasets
  2. gaze detection
  3. neural networks
  4. text tagging

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