Data

We are where the geospatial data and non spatial data are produced, managed and shared according to our quality standards.

Climate Risk Database (CRD)

Recilience Academy’s Climate Risk Database (CRD) is a geospatial data repository that supports research, education and planning, such as disaster-risk management practices. The rich repository of datasets consists of open-access data from industrial training, Tanzania Urban Resilience Program projects, and third parties.

CRD is built on open-solution platform of Geonode, hosted at the University of Turku Geonode.

We curate Climate Risk Database, a open-access repository with a collection of geospatial data on urban resilience and disaster risk management in Tanzania

Data curation skills

We develop and conduct training for the next generation and professional experts to enhance their practical skills and academic understanding of urban challenges. We provide contact learning and online courses for University experts, government officials, University students and other professionals interested in improving their digital data skills.

We also develop digital geospatial data quality and management skills of young professionals and students in universities and partner organizations.

Tools

We have collected a repository of useful open-access tools and practices with instructions for geospatial data management. Most of the tools are available through QGIS software, that anyone can download without fees. You can use the tools for data editing, quality assessment and other management practices.

We maintain a list of useful open-access tools suitable for digital data collection, management and analysis. We train students with these tools in the industrial training and courses at Tanzanian universities.

Data Visualisation Challenge

The visualisation competition is for university students interested in developing their digital data visualisation skills. Students learn together and work in groups to create powerful data visualisation solutions for the needs of real world.

In their work, students use data that is shared in Climate Risk Database.

We organize annually Data Visualization Challenge, which gathers enthusiastic students from Tanzanian universities to compete in teams and pitch for their best geospatial data visualization solution.

Data quality standards

Climate Risk Database (CRD) of the Tanzania Resilience Academy shares open datasets related to urban resilience in Tanzania. All datasets shared via CRD follow the data quality standards identified and described on this page. By defining data quality standards, we can assure that the data has high-quality accessibility and usability for the urban resilience community and Tanzania Urban Resilience Program partners.

Here below, you find descriptions of our data quality standards, and instructions on how to reach them in your work.

Click one of the standard themes, and more information pops up. On the left are listed the standards related to that theme, and an explanation what they mean. On the right are practical instructions, documents and examples to support your work.

Metadata Standards

What is metadata?
Metadata provides valuable information about the data. Metadata holds information of what the data is about, when it was created, by whom, how can it be used, and so on. Metadata is the key source of information to data users, and thus we require that metadata is created for all datasets published in Climate Risk Database.

Standard for data provider

More info about this standard ...

Follow the Metadata instructions provided by us when creating the metadata for your dataset. Fill in carefully at least all compulsory fields of the metadata template. The more metadata you provide, the merrier for future users of the data!

Resources to support your work:

  • Data Provider’s guide
  • Metadata template
  • Metadata instructions

 

Standard for data managers

More info about this standard ...
  • Do quality check for the metadata by following the Quality control instructions.
  • Check that metadata is filled when data set is uploaded to CRD.
  • Make sure we receive the filled metadata sheet also in Excel-file format and store it to our metadata repository.

Resources to support your work:

  • Data Manager’s guide
  • Quality control instructions
  • Quality report template

Standard for Platform developers

More info about this standard ...

Make sure Climate Risk Database provides functioning way to fill in or upload metadata. Technical solution of the Metadata Wizard should clearly show which metadata fields are compulsory.

Geometric quality standards

What does geometric quality mean?
Geometric quality refers to the good connectivity, accuracy and precision of spatial representation of a geospatial data set. The objects of the data set should represent real-world objects accurately, and the precision of vector objects or raster cells should be suitable for the case. Good connectivity refers to the connectivity rules of vector data sets’ geometries: for example, polygons must be complete and no gaps between them are tolerated.

Standard for data provider

How to reach to this standard? ...

Get familiar with the good practices of creating spatial data and apply them in your case. For example, create a vector dataset with line-type objects that represents a road network so that all of the lines are connected to each other – just like roads are in the real world.
Check the quality of the finished geometries of vector data with specific tools available in GIS software (see resources).
Write about the creation of the geometrics and about the quality of them to the metadata.

Standard for data managers

More about how to reach the standard?

A)
Run quality check for the geometries of data sets according to the Quality control instructions.

Resources to support your work:
Data Manager’s guide
Quality control instructions
Quality report template
Tool: Geometry checker too, QGIS

Attribute quality standards

A) Attributes and values of data sets reflect the real-world accurately.
B) Attribute tables of vector data sets are complete and consistent.
C) All compulsory attribute metadata is filled according to our instructions and provided together with the data set.

What does attribute quality mean?
Attribute information describes the thematic features of a geometrical object, such as polygon or raster cell, and is provided in tabular format. The collected attribute values must represent the real world reliably. In a high-quality dataset attribute information is relevant, well collected, and valid both in space and time. Attribute tables should not have gaps, and the content in them must be consistent thoroughly. We also require that metadata of attributes are provided together with all datasets published in Climate Risk Database.

Standard for data provider

How to reach to this standard? ...

A)
Plan the data acquisition carefully so that relevant attributes are attached to the dataset. Relevant attributes are always case-specific and recognizing them is easier when the goal of the data acquisition process is clear.
Measure the phenomenon you want to record reliably and with proper tools and gadgets.
Tell about the attribute collection process in the metadata.

B)
Fill in your attribute tables carefully and systematically. All values of same attribute should be in same format, and the collection of them must be similar through the collection process, so that you reach the desired consistent result. There should be no gaps in the attribute table.
If some of the objects of your dataset doesn’t have a value in some of the attributes, use the “NA” statement, and explain the meaning and reason of it in the metadata.

C)
Follow the Attribute metadata instructions provided by us when creating the attribute metadata for your vector dataset.
Fill in carefully at least all compulsory fields of the metadata template.
In case of raster data, provide explanation of the values in the metadata, section Supplemental information. And remember, the more attribute metadata you provide, the merrier for future users of the data!

Resources to support your work:
Data Provider’s guide
Attribute metadata template
Attribute metadata instructions

Standard for data managers

More about how to reach the standard?

A) & B)
Check the quality of attributes by following Quality control instructions.

C)
Check the completeness of attribute metadata, follow the Quality control instructions.
Make sure the attribute information is filled in Climate Risk Database.
Also, make sure we receive the attribute metadata in Excel-sheet and store it to our metadata repository.

Resources to support your work:
Data Manager’s guide
Quality control instructions
Quality report template

Standard for developers

More about how to reach the standard?

A)
Make sure Climate Risk Database provides functioning way to fill in or upload attribute metadata

Temporal quality standards

A) All data sets indicate when the data set was produced, and when it was updated (if relevant).

What is temporal quality?
Temporal quality is closely related to the quality of metadata. All relevant temporal aspects should be clearly stated in the metadata, such as the production date or period, updating date and frequency, and nature of temporal attributes, if there are any. These information helps the data users to evaluate the currency of the data, and whether it meets their needs.

Standard for data provider

How to reach to this standard? ...

A)
Follow the metadata instructions when filling in the temporal information of your data set. There are fields for both production and updating aspects.
Of course, take the time-dimension into account when planning your data acquisition, too. Consider, for example, does the time of year affect your field work? Or, what is the duration of measurements, if they are being done multiple times (e.g. measuring temperatures every 12 hours).
If there is a temporal aspect in the observations, those should be stated and explained in the metadata or attribute metadata as well.

Resources to support your work:
Data Provider’s guide
Metadata template
Metadata instructions
Attribute metadata template
Attribute metadata instructions

Standard for data managers

More about how to reach the standard?

A)
Follow the Quality control instructions and check that the metadata fields related to temporal aspects are filled in, and are consistent with each other and rest of the metadata.

Resources to support your work:
Data Manager’s guide
Quality control instructions
Quality report template

Visual quality standards

A) Visualization is appropriate, reliable and comprehensible.

What does visual quality mean?
Visual quality is key attribute in communicating geographic information efficiently and reliably. Visualizations of geospatial data sets is always case-specific, but good practices should always be applied when planning and creating the visualizations. The good practices and guidelines are rather general, and they allow creativity when creating visualizations. Most important factor is not to give any mis-leading or manipulating images of phenomena the data sets represent.

Standard for data provider

How to reach to this standard? ...

A)
Create a visualization for your data set in GIS software, and save the visualization in SLD format.
Use your creativity when doing the visualization, but be true to the dataset.
Use clear symbols and colors, and avoid a mis-leading result.
Upload the visualization to Climate Risk Database together with your data set. Alternatively, ask the Data Managers of CRD to create a visualization for you.
Get to know online training materials regarding data visualization, provided by Resilience Academy and partner Universities. (?)

Resources to support your work:
Data Provider’s guide
Technical instruction of how to do visualization in QGIS and save it in SLD format
Technical instruction of how to do visualization in CRD
[Link to Module 3 online materials, if available?]

Standard for data managers

More about how to reach the standard?

A)
Follow the Quality control instructions and evaluate the visualization of the data set.
If data provider asks us to create the visualization instead, create one in QGIS or in Climate Risk Database, upload it to CRD and attach to the data set in question.

Resources to support your work:
Data Manager’s guide
Quality control instructions
Quality report template
Technical instruction of how to do visualization in QGIS and save it in SLD format
Technical instruction of how to do visualization in CRD

Standard for developers

More about how to reach the standard?

A)
Make sure visualization works correctly in Climate Risk Database.
Provide instructions off how to create visualizations in CRD.

File format standards

A) Data sets are in standardized formats and machine-readable.

What does file format mean?
Geospatial data sets should be produced, managed and shared in standardized and machine-readable formats, which ensures they can be used and further analyzed in GIS and other software. Machine-readable file format means that computers are able to read the objects and attributes of the
data set. This cannot be done, for example, if the data is stored and shared in image formats, such as JPEG or PNG files (exception with aerial images which are not geocoded). Widely accepted and used file formats for geospatial data are: ESRI shapefile, Zipped shapefile, Geopackage, GeoJSON, or CSV with coordinates (vector data), and GeoTIFF or GZIP (raster data).

Standard for data provider

How to reach to this standard? ...

A)
Store your geospatial data so that the object that has spatial dimension and the attribute information of that object are linked to each other. This is easiest to be done if you manage your data in spatial file format from the very beginning, but storing attribute information together with coordinates to a tabular format (CSV/XLSX) is also an option.

Share your data to us and upload it to Climate Risk Database most preferably as Shapefile or GeoTIFF. Provide the metadata and attribute metadata sheets as Excel-files.

Resources to support your work:
Data Provider’s guide
Data management template

Standard for data managers

More about how to reach the standard?

A)
Follow Quality control instructions and check that the data delivered is in correct format.

Resources to support your work:
Data Manager’s guide
Quality control instructions
Quality report template

Standard for developers

More about how to reach the standard?

A)
Make sure Climate Risk Database allows at least the following formats to be uploaded and viewed on a map: ESRI shapefile, Zipped shapefile, Geopackage, GeoJSON, or CSV with coordinates (vector data), and GeoTIFF or GZIP (raster data).

Provide ways to upload large data sets as well, such as functioning links to Seafile folders.

Accessibility standards

A) Data sets are shared under a license.
B) Data sets are comprehensible.
C) Data sets are easy to find.
D) Data sets are easy to use.

What is accessibility?
Accessibility is an important aspect of data quality, and is connected to the usability of data sets. High accessibility ensures that users knows that data set exists, is able to find it, and ultimately knows how to use it. In Climate Risk Database, accessibility of data sets is enhanced with an open and simple platform, efficient dissemination, licensing all data sets and making them as comprehensible as possible. We highly encourage data providers to license their data under an open license, if only possible.

Standard for data provider

How to reach the standard? ...

A)
Always determine a license for your data set. If your data is available for anyone freely to use, and is so called an open data set, we recommend licenses such as CC0 or CC-BY 4.0. Read more from document Licenses in CRD.

B)
Enhance the comprehensibility of your data set by using English language, naming attributes intuitively, and providing sufficient metadata together with the data set.

 

Resources to support your work:
Data Provider’s guide
Licenses in CRD

Standard for data managers

More about how to reach the standard?

A) & B)
Follow the Quality control instructions and check the licenses and languages of the data set.

C)
Encourage data providers to tell a story behind the data acquisition process, and share it in Climate Risk Database blogs, or other channels.
Every once in a while, create maps or posts to social media channels about the data sets.

Resources to support your work:
Data Manager’s guide
Quality control instructions
Quality report template

Standards for data users

More about how to reach the standard?

D)

  • Make sure all functions of Climate Risk Database are always working correctly, so that the platform is easy and intuitive to use by data users.
  • Provide instruction guides for users, and make sure they are easy to find.

Responsibility standards

A) Acquirement, management and usage of data sets is responsible in all aspects.

What responsibility mean?
Responsible actions in all stages of the data lifecycle ensures the safety individuals (both subjects of the research, as well as the researchers), society, culture, the environment and the data itself. Responsibility is achieved when impacts of actions are carefully thought under the processes, and actions are taken to prevent harmful impacts. Key protocols related to responsibility are, for example, addressing privacy issues, monitoring environmental impacts, returning results to participants and considering how usage of data affects the people related to it.

Standard for data provider

How to reach the standard? ...

A)

  • Responsibility activities are case-specific. Know the good ethical practices of your field.
  • Address privacy issues if you collect data from individuals. If relevant, use the Consent agreement template provided by us.
  • Never publish personal information of the participated individuals: they must not be able to be identified from the data set.
  • Make sure not to harm the individuals, communities or environment that are in (direct or indirect) contact with your data acquisition processes.
  • Store the data securely during the whole process so that information loss is minimized.

Resources to support your work:
Data Provider’s guide
Consent agreement template

Standard for data managers

More about how to reach the standard?

A)
Store the data securely in our repositories, in addition to Climate Risk Database servers.

Resources to support your work:
Data Manager’s guide

Standard for developers

More about how to reach the standard?

A)

  • Follow good ethical practices of your field. Before using the data in research or planning activities, consider what are the possible impacts towards the people, culture and the environment related to your actions.
  • Responsible research returns the results back to the individuals and communities of which the results are related to. Communicate about the results, and make sure they are open and accessible.

Join to us to make use of data

Access to digital data sets is a pre-requisite for understanding risks and developing evidence-based solutions for resilient urban development”

join us to the Climate Risk database

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