Mid-term Evaluation (40 marks)

Deadline: 28 Feb 2025

Presentations: 2 March 2025

Note: Failing to complete the presentation will result in 0 marks for this portion of the mid-term evaluation.

Failure to submit within the deadline will result in a deduction of 5 marks.

Task:

Select a research paper from a Q1 or Q2 journal that focuses on a spatial or spatio-temporal application. You will read, analyze, and present the paper, ensuring the following aspects are covered:

Introduction (2 Marks)

Clearly summarize the research problem and objectives.

Explain the significance of the study in the broader context of spatial or spatio-temporal analysis.

Methodology (10 Marks)

Describe the techniques and models used in the study.

Explain why these methods were chosen and their advantages.

Data (5 Marks)

Provide details about the dataset used in the study.

If the dataset is not publicly available, construct a simulated dataset to illustrate key concepts.

Replication of Results (10 Marks)

Attempt to reproduce the key findings using the provided or simulated dataset. Present and interpret your results.

Suggestions for Improvement (3 Marks)

Identify potential weaknesses or limitations in the study. Suggest alternative methods, additional analyses, or improvements in data collection.

Limitations (2 Marks)

Discuss the challenges or constraints associated with the study’s approach. Reflect on the broader implications of these limitations.

Q and A (8 marks)

Recommendation:

Choose a paper that includes a dataset to facilitate replication.

If a dataset is unavailable, construct a simulated dataset to demonstrate key ideas.

Your analysis should be concise, well-structured, and supported by visualizations or code where appropriate.

You should submit/present following documets

  1. Presentation document

  2. Time for presentation: 10 min. (The total presentation time is strictly limited to 10 minutes. Only the points presented within this timeframe will be considered for grading.)

  3. Q and A: 5 min.

  4. Data, Codes and Results corresponds to reproducibility

  5. A copy of your research paper.