After a review of the initial information presented in the 2016 Mexico submissions for the GODI, submitters from civil society - Sergio Araiza- and responsibles of the open data initiative in México - Enrique Zapata-, got together to dialogue, analyze and perfect the information presented in these first submissions.
This is an example of the value and benefits that the Index can bring to get civil society, citizens and government together to discuss opportunity areas for open data in the country, understand different views regarding a single issue, and agree on next steps and actions to continue working towards a robust and strengthened ecosystem in Mexico.
After these analyses, we would like to kindly request the GODI to take into account the following clarifications
Weather Forecast
Include seven new datasets:
Open Data Portal, Max Temperature: datos.gob.mx/busca/dataset/temperatura-maxima-excel
Open Data Portal, Average Temperature: datos.gob.mx/busca/dataset/temperatura-promedio-excel
Open Data Portal, Wind Speed: datos.gob.mx/busca/dataset/direccion-y-rapidez-del-viento-por-estacion
Open Data Portal, Wind Direction: datos.gob.mx/busca/dataset/direccion-y-rapidez-del-viento-por-estacion
Open Data Portal, Precipitation Amount: datos.gob.mx/busca/dataset/precipitacion-actual-y-acumulada-por-estacion
National Weather Service Portal, Precipitation Probability (96h): smn.cna.gob.mx/es/pronosticos/pronosticossubmenu/pronostico-extendido-a-96-horas
Open Data Portal, Precipitation Forecast (7d): datos.gob.mx/busca/dataset/hidrometeorologia
Question B7, change to ‘Yes’, data is openly licensed with the MX Open License: datos.gob.mx/libreusomx
Question B8, include formats: XML, GRADS, GIF, TXT, CSV, HTML
Dear @Enrique_Zapata
thank you so much for flagging this. I’ll review the submission accordingly again, and will get back in case I have further questions. This feedback is very helpful.
Best
Danny
Dear @Enrique_Zapata,
Thanks again for your help on the review. I reviewed the Mexican weather data again. I accessed all sources you mentioned above. Unfortunately, the Global Open Data Index covers a specific type of weather data that is not fully included in the seven datasets you link to (see our data characteristics).
This data does not qualify as a reference for the Global Open Data Index for the following reasons: Either it does not represent modeled forecast data (but observational data), or it is not technically accessible (as in the case of the SOAP API you link to). In the case of the weather warning data, required data such as wind at speed below 50mph and wind direction are missing.
My detailed explanations:
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Your proposed datasets of temperature extremes and averages contain historical data, whilst the Global open Data Index assesses modeled forecast data. The provided data is therefore not considered for the assessment.
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Wind speed and direction, available at datos.gob.mx/busca/dataset/direccion-y-rapidez-del-viento-por-estacion, could not be retrieved. When the reviewer tried to connect to the API, the connection to the SOAP services was not secure and not available in the moment of review. Therefore the content of the data could not be verified, which is why we could not consider the data for our review.
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One of your links presents a downloadable pdf that shows forecasts for the current day and the following three days (smn.cna.gob.mx/es/pronosticos/pronosticossubmenu/pronostico-extendido-a-96-horas). It presents weather forecasts (and warnings) for temperature extremes, precipitation amount, and strong winds (wind speed above 50 mph). This pdf contains neither wind directions, nor winds at speed lower than 50 mph. Therefore it does not qualify as a reference dataset for the review.
The reference dataset for the review:
The review takes following dataset as reference, because it meets all requirements as defined by the Index, including wind speed and direction. You can access the dataset at: http://smn.cna.gob.mx/es/pronostico-del-tiempo-por-municipios. The content is not downloadable, and there is no copyright note on the website that would explain whether the data is openly licensed. Therefore the data is considered not to be openly licensed.
When does a dataset become a “reference dataset”?
There are two ways that a dataset can become a reference.
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All required data characteristics (wind speed, wind direction, temperature average or extremes, precipitation amount and probability) are split across different files. The reviewer cannot base the review on one single file, but has to take all available files into consideration. Each question, such as “is the data available for free” must be answered with reference to these files. If some files are available for free, but others are not, the reviewer would state that the data is not available for free. The rationale behind this approach: the Global Open Data Index assesses data categories as a whole. Every question we ask needs to apply to all required data elements.
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All required data are contained in one data file or data format (be it a webpage, a pdf file, a csv sheet or alike). If there are several files containing all required data characteristics, a reviewer will refer to the dataset for which most questions can be answered with “Yes”.
In your case, we could have accepted the link to the pdf file including forecasts, to acknowledge that this data is downloadable. Yet, since the pdf did not include all required data, we could not take the pdf as a reference point.
It is important that GODI is rigid with the dataset descriptions and refers to common datasets, that form our unit of analysis. This enables us to compare open data publication across countries. We are open to discuss our current dataset descriptions and gather your feedback how to improve them.
All the best
Danny
Comment in response to the reviewers comment: 'The review takes following dataset as reference, because it meets the dataset requirements: http://smn.cna.gob.mx/es/pronostico-del-tiempo-por-municipios. The content is not downloadable, and there is no copyright note on the website that would explain whether the data is openly licensed. ’
The dataset is available as open data in Datos Abiertos de México - Pronósticos del tiempo por municipios
This API is openly licensed and meets all the requirements asked by the GODI.
Dear @Enrique_Zapata
thanks so much for your feedback. We will follow up on your input and will get back to you in the coming days.
All the best
Danny
In the context of the GODI public dialogue phase, and its objective to discuss the GODI preliminary results in an open dialogue, on May 25th, 2017, Ania Calderón - Executive Director of the Open Data Charter, Oscar Montiel - International Community Coordinator of Open Knowledge International, Sergio Araiza - SocialTIC y Escuela de Datos and Enrique Zapata - General Director of Open Data in Mexico, gathered in a joint Hang Out to:
• Discuss the preliminary results for Mexico,
• Analyze the pertinence of these preliminary reviews and the existence of requested datasets in open formats, and
• Agree on submitting joint comments to be taken into account
After this exercise this group would like to kindly request the reviewers to take into account the following clarifications to the ‘Weather forecast’ dataset in its ‘openly licensed’, ‘open and machine readable formats’ and ‘downloadable at once’ dimensions, based on the following comments:
- The right dataset for weather forecast can be found here: Datos Abiertos de México - Pronósticos del tiempo por municipios
- This dataset is the data source of the system consulted by the reviewer and judged as complete, the only difference is that the reviewer seemed to have acceded to the ‘citizen consultation platform’ of the Mexican Water Commission, and not to the data related to this platform and that can be consulted in datos.gob.mx
We thank the reviewers for their time and willingness to take into account the work done jointly by civil society and government to perfect the GODI and increase its value for the open data community.
1 Like
Dear @Enrique_Zapata,
Thank you very much for your work and involvement in this year’s Index. We checked the new resource and confirm that it now includes all the required data. We can confirm that it is openly licensed, in open formats, and downloadable at once.
Yet, as I can see the data was created on March 21, 6 days after closing our review. We do not change the score of this category because we do not consider any datasources for assessment that have been uploaded after March 15.
We value the efforts Mexico put into adapting and updating its data and will note the updates in our review comments so that every user knows about the availability of the data, and how it can be used.
Best wishes
Danny
Hi @dannylammerhirt please be advised that on datos.gob.mx the CKAN creation date does not reflect the actual date when the resource was first added:
Because we use Adela ( adela.datos.gob.mx ), a middleman that we rely on so that mexican organizations do not enter their data directly into CKAN. Whenever we sync the data from the organization into CKAN, this dates are flushed, as you can see on the following graph where I’m plotting the number of resources by ckan creation date, most of our resources report a very recent CKAN creation date. (for instance, as of today, this same dataset states that it was created yesterday)
As the Pronosticos del tiempo por municipios dataset has been online for a long time, I’d like to ask you to consider it for the assessment.
Cheers
Andres