def METHOD_NAME(dest_dir: str) -> None:
    #
    # Load data.
    #
    # Load Nemet (2009) dataset from Garden.
    ds_nemet: catalog.Dataset = paths.load_dependency("nemet_2009")
    tb_nemet = ds_nemet["nemet_2009"].reset_index()
    # Load Farmer & Lafond (2016) dataset from Garden.
    ds_farmer_lafond: catalog.Dataset = paths.load_dependency("farmer_lafond_2016")
    tb_farmer_lafond = ds_farmer_lafond["farmer_lafond_2016"].reset_index()
    # Load IRENA dataset on capacity from Garden.
    ds_irena_capacity: catalog.Dataset = paths.load_dependency("renewable_electricity_capacity")
    tb_irena_capacity = ds_irena_capacity["renewable_electricity_capacity"].reset_index()
    # Load IRENA dataset on cost from Garden.
    ds_irena_cost: catalog.Dataset = paths.load_dependency("renewable_power_generation_costs")
    tb_irena_cost = ds_irena_cost["solar_photovoltaic_module_prices"]
    #
    # Process data.
    #
    # Create a table of cumulative solar photovoltaic capacity, by combining Nemet (2009) and IRENA data.
    cumulative_capacity = prepare_capacity_data(tb_nemet=tb_nemet, tb_irena_capacity=tb_irena_capacity)
    # Create a table of solar photovoltaic cost, by combining Nemet (2009), Farmer & Lafond (2016) and IRENA data.
    cost = prepare_cost_data(tb_nemet=tb_nemet, tb_irena_cost=tb_irena_cost, tb_farmer_lafond=tb_farmer_lafond)
    # Combine capacity and cost data.
    tb_combined = pd.merge(cost, cumulative_capacity, on="year", how="outer")
    # Add column for region.
    tb_combined = tb_combined.assign(**{"country": "World"})
    # Set an appropriate index and sort conveniently.
    tb_combined = tb_combined.set_index(["country", "year"], verify_integrity=True).sort_index()
    #
    # Save outputs.
    #
    # Create a new dataset with the same metadata as meadow
    ds_garden = catalog.Dataset.create_empty(dest_dir)
    # Add combined table of cost and capacity to dataset.
    tb_combined.metadata.short_name = paths.short_name
    ds_garden.add(tb_combined)
    # Update dataset metadata and save dataset.
    ds_garden.update_metadata(paths.metadata_path)
    ds_garden.save()