Banca de DEFESA: Ingrid Palma Araujo

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
STUDENT : Ingrid Palma Araujo
DATE: 05/08/2022
TIME: 14:00
LOCAL: Videoconferência no Teams
TITLE:

Decision Support Model to Evaluate Open Government Data from the Electricity Sector

KEY WORDS:

Open Data Evaluation Model, AHP-TOPSIS-2N, (Linked) Open Government Data, Open Energy, Multicriteria Decision Support Model.

PAGES: 146
BIG AREA: Ciências Exatas e da Terra
AREA: Ciência da Computação
SUBÁREA: Metodologia e Técnicas da Computação
SUMMARY:

Making more assertive and efficient decisions in the face of scarce public resources while considering all potential alternatives has become one of the most common problems for managers responsible for open government data. Open data ecosystems around the world are introducing guidelines and targets with a focus on electric power, given the growing awareness of topics such as the water crisis, climate change, renewable resources, and initiatives to increase energy efficiency2 . Moreover, the subjectivity and imprecision in the process of opening data from this sector can make this task even more complex, especially when there are no specific measures to support decision-making. Thus, this study proposes to simplify and automate this process, combining two different methods of decision support through multicriteria analysis in a model capable of assessing and prioritizing risk criteria in the context of Open Data, presenting the results via iterative online dashboards developed in R3 . The methodology followed combines the AHP and TOPSIS-2N methods, creating a ranking of the open governmental dataset of the electricity sector in light of the risk criteria evaluated by the proposed model. The AHP technique was used to specify and normalize the importance of each criterion, considering the consistency aspects of the decision matrix. The next step was to apply the TOPSIS-2N method to sort and prioritize these datasets. The results present the datasets that should be improved concerning the respective metadata and the prioritized topics to make the decision-making for the management of these bases more agile and assertive. Different types of metadata are used to measure the 5 identified risk criteria. The proposed model is useful not only for managers responsible for decisions involving the contribution of resources to improve the datasets already available but also to prioritize the most relevant topics for data opening. Open data related to power sector planning (BD46 and BD45) and energy tax (BD47) stood outon the top of the model, inferring potential added value generated by these bases.

BANKING MEMBERS:
Externo à Instituição - PATRICIO ESTEBAN RAMIREZ CORREA
Presidente - 1817613 - ANA CARLA BITTENCOURT REIS
Interno - 1114843 - ARI MELO MARIANO