The INSPIRE directive was passed in 2007 to facilitate easy exchange of environmental and spatial information. Its purpose is to make data from different sources easily accessible to stakeholders to boost data-driven decision-making. INSPIRE offers high-quality data and a solid foundation to build data-driven processes on. Now, the value offered by the INSPIRE directive is being recognized by private organizations outside of the EU.
Minerva Intelligence Inc applies auditable and explainable AI to complex geoscience problems, ranging from geohazard assessment to mineral target identification to climate law impact. To get the best possible results, Minerva harnesses INSPIRE standards to improve the quality of its AI models.
In one of their projects, Minerva created a freely accessible map of Yukon Mineral Targets. It allows users to identify claimed and unclaimed mineral targets in the Yukon region. Minerva’s software evaluates the best mineral targets based on comparisons of targets with their best-matching mineral deposit models. Each target is assigned a score based on the degree of the match, and the targets with the highest score are displayed. An in-depth report of the scoring mechanism for each target is also available. The report explains how the comparison was done and how the score of each target was determined. These explanations provide a better understanding of the reasoning behind the AI’s decision-making in a simple and concise manner. It gives users information about what they need to investigate when conducting follow-up work on each target.
To improve the results of the AI model and apply it to data from different regions, global terminologies were needed. These terminologies would ensure that the model used in this situation could be reapplied to other similar situations. Standardized terminologies would ensure a high-quality database and improve the results of the AI model. It was also hard to find a specification that would be broadly applicable, since most data specifications are narrow and are built with a specific goal in mind.
To this end, the INSPIRE Geology data format was used for the bedrock geology layer. INSPIRE is an EU-wide standard that provides common terminologies for 44 countries with different types of data. This wide range ensured that the terminologies used in developing parts of this map could also be used for other purposes. The state-of-the-art terminology provided by INSPIRE formed a high-quality basis for the AI’s operations. It facilitated a better analysis of information.
Open standards such as INSPIRE create opportunities for collaboration. They create consistency in the storage of data to keep multiple stakeholders in sync. They consolidate data quality to ensure less risks in data processing. Ultimately, they lead to more better data-processing, be it in the private sector or the public sector.
Data standardization, however, can pose a challenge. It is hard to achieve without the right tools and knowledge. It is reported that most organizations spend up to 70% of their time only on data standardization tasks.
hale connect was used to deliver the data and the map shown above. It allowed Minerva to design and publish data that was INSPIRE compliant through a secure methodology that guaranteed high data quality. Through the introduction of a standardised and easily available dataset, Minerva enhanced the results of its AI model and made its predictions more accurate. Since global terminolgies were used, the model could also be used for different regions without having to re-train or re-build the model.
Our toolset effectively helps you to deal with the complexities of standardisation, such as metadata generation and validation, data transformation and the publishing and viewing of services. We’ve already helped over 80 organizations comply with standards such as INSPIRE and XPlanung through our products and services, and we want to keep make standardization easily accessible. Do you want to know how your BI or AI application can benefit from easily accessible, standardized, harmonised data? Send a message to info@wetransform.to, and we can set up a free webinar to guide you through the process!
The INSPIRE directive was passed in 2007 to facilitate easy exchange of environmental and spatial information. Its purpose is to make data from different sources easily accessible to stakeholders to boost data-driven decision-making. INSPIRE offers high-quality data and a solid foundation to build data-driven processes on. Now, the value offered by the INSPIRE directive is being recognized by private organizations outside of the EU.
Minerva Intelligence Inc applies auditable and explainable AI to complex geoscience problems, ranging from geohazard assessment to mineral target identification to climate law impact. To get the best possible results, Minerva harnesses INSPIRE standards to improve the quality of its AI models.
In one of their projects, Minerva created a freely accessible map of Yukon Mineral Targets. It allows users to identify claimed and unclaimed mineral targets in the Yukon region. Minerva’s software evaluates the best mineral targets based on comparisons of targets with their best-matching mineral deposit models. Each target is assigned a score based on the degree of the match, and the targets with the highest score are displayed. An in-depth report of the scoring mechanism for each target is also available. The report explains how the comparison was done and how the score of each target was determined. These explanations provide a better understanding of the reasoning behind the AI’s decision-making in a simple and concise manner. It gives users information about what they need to investigate when conducting follow-up work on each target.
To improve the results of the AI model and apply it to data from different regions, global terminologies were needed. These terminologies would ensure that the model used in this situation could be reapplied to other similar situations. Standardized terminologies would ensure a high-quality database and improve the results of the AI model. It was also hard to find a specification that would be broadly applicable, since most data specifications are narrow and are built with a specific goal in mind.
To this end, the INSPIRE Geology data format was used for the bedrock geology layer. INSPIRE is an EU-wide standard that provides common terminologies for 44 countries with different types of data. This wide range ensured that the terminologies used in developing parts of this map could also be used for other purposes. The state-of-the-art terminology provided by INSPIRE formed a high-quality basis for the AI’s operations. It facilitated a better analysis of information.
Open standards such as INSPIRE create opportunities for collaboration. They create consistency in the storage of data to keep multiple stakeholders in sync. They consolidate data quality to ensure less risks in data processing. Ultimately, they lead to more better data-processing, be it in the private sector or the public sector.
Data standardization, however, can pose a challenge. It is hard to achieve without the right tools and knowledge. It is reported that most organizations spend up to 70% of their time only on data standardization tasks.
hale connect was used to deliver the data and the map shown above. It allowed Minerva to design and publish data that was INSPIRE compliant through a secure methodology that guaranteed high data quality. Through the introduction of a standardised and easily available dataset, Minerva enhanced the results of its AI model and made its predictions more accurate. Since global terminolgies were used, the model could also be used for different regions without having to re-train or re-build the model.
Our toolset effectively helps you to deal with the complexities of standardisation, such as metadata generation and validation, data transformation and the publishing and viewing of services. We’ve already helped over 80 organizations comply with standards such as INSPIRE and XPlanung through our products and services, and we want to keep make standardization easily accessible. Do you want to know how your BI or AI application can benefit from easily accessible, standardized, harmonised data? Send a message to info@wetransform.to, and we can set up a free webinar to guide you through the process!
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Man-made CO2 emissions are a key contributor to global climate change. A large portion of these emissions are generated by freight transport. Water and rail transport are more efficient than road transport in terms of CO2 emissions. Currently, however, Road transport accounts for 75% of freight transport in Europe.
We challenge you to use the wide range of available data to explore the efficiency of intermodal freight transport in Europe. This includes optimizing road, waterway and railway utilization based on factors such as Estimated Time of Arrival (ETA) confidence, risk, cost and CO2 emissions.
For the whole month of September, we will provide you with the resources and support so that you can develop demo routing software that identifies and visualises the most efficient intermodal transport.
When you have developed your software, describe it in a short report. Provide a short video or a demo link. Based on these submissions, the organisers will choose the finalists who get a chance to present their solution at the Inspire Helsinki 2019 event, where the final winner will be decided.
Participants stand a chance to win the following prizes:
- All finalists:
- Free trip to Helsinki for the final event for one team member
- First Place:
- Free trip to INSPIRE 2020 in Dubrovnik for one team member
- High-Quality electric scooters for up to five team members (500 € value each)
- Second Place:
- Sport headphones for up to five team members (100 € value each)
More details can be found here.
Important dates and deadlines:
- Webinar for challenge introduction: July 14th, 2019
- Deadline for registration: August 16th 2019. You can find the registration form here.
- Deadline for written submission of team results: September 30th, 2019
- Inspire Helsinki 2019 event: October 22nd to 24th, 2019
Man-made CO2 emissions are a key contributor to global climate change. A large portion of these emissions are generated by freight transport. Water and rail transport are more efficient than road transport in terms of CO2 emissions. Currently, however, Road transport accounts for 75% of freight transport in Europe.
We challenge you to use the wide range of available data to explore the efficiency of intermodal freight transport in Europe. This includes optimizing road, waterway and railway utilization based on factors such as Estimated Time of Arrival (ETA) confidence, risk, cost and CO2 emissions.
For the whole month of September, we will provide you with the resources and support so that you can develop demo routing software that identifies and visualises the most efficient intermodal transport.
When you have developed your software, describe it in a short report. Provide a short video or a demo link. Based on these submissions, the organisers will choose the finalists who get a chance to present their solution at the Inspire Helsinki 2019 event, where the final winner will be decided.
Participants stand a chance to win the following prizes:
- All finalists:
- Free trip to Helsinki for the final event for one team member
- First Place:
- Free trip to INSPIRE 2020 in Dubrovnik for one team member
- High-Quality electric scooters for up to five team members (500 € value each)
- Second Place:
- Sport headphones for up to five team members (100 € value each)
More details can be found here.
Important dates and deadlines:
- Webinar for challenge introduction: July 14th, 2019
- Deadline for registration: August 16th 2019. You can find the registration form here.
- Deadline for written submission of team results: September 30th, 2019
- Inspire Helsinki 2019 event: October 22nd to 24th, 2019
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We’ve brought in more features over the previous month to make your experience with hale»connect even better! Here’s what’s new:
Raster data publishing
hale»connect now supports the upload and publishing of .PNG and .GeoTIFF raster files. This enables you to include your raster data while publishing XPlanung and INSPIRE Land Use data. You can find this option in the “View Services” section in themes. Check out the new raster workflow document in our help section.
New Map View
hale»connect has a new map view based on Open Street Map and Leaflet. You can add your own WMS base map via the layer widget. You can also configure a default basemap configuration for your organization in the organization settings. Check out the documentation sections for more information.
Deactivate Users
Administrators can now deactivate and reactivate users. Learn more here.
Autofill rule to populate dataset name
In the metadata section of a theme, users can now add an autofill rule to populate the dataset name. This enables users to select a dataset attribute, or other value, to generate the dataset name. Check out the metadata configuration option here.
Include attachments in atom feed
Haleconnect offers a new setting in the download services section of a theme. The new toggle switch “Include attachment links in Predefined Dataset download services” enables users to download attachments uploaded with their dataset directly from the atom feed. The documentation for this feature can be found here.
Attachment handling
There are now multiple ways to upload attachments on haleconnect. For customers interested in uploading XPlanung data which includes attachments, it is now possible to upload attachment during dataset creation. More information on this update can be found here.
If you have any questions, comments or concerns, don’t hesitate to contact us at info@wetransform.to
We’ve brought in more features over the previous month to make your experience with hale»connect even better! Here’s what’s new:
Raster data publishing
hale»connect now supports the upload and publishing of .PNG and .GeoTIFF raster files. This enables you to include your raster data while publishing XPlanung and INSPIRE Land Use data. You can find this option in the “View Services” section in themes. Check out the new raster workflow document in our help section.
New Map View
hale»connect has a new map view based on Open Street Map and Leaflet. You can add your own WMS base map via the layer widget. You can also configure a default basemap configuration for your organization in the organization settings. Check out the documentation sections for more information.
Deactivate Users
Administrators can now deactivate and reactivate users. Learn more here.
Autofill rule to populate dataset name
In the metadata section of a theme, users can now add an autofill rule to populate the dataset name. This enables users to select a dataset attribute, or other value, to generate the dataset name. Check out the metadata configuration option here.
Include attachments in atom feed
Haleconnect offers a new setting in the download services section of a theme. The new toggle switch “Include attachment links in Predefined Dataset download services” enables users to download attachments uploaded with their dataset directly from the atom feed. The documentation for this feature can be found here.
Attachment handling
There are now multiple ways to upload attachments on haleconnect. For customers interested in uploading XPlanung data which includes attachments, it is now possible to upload attachment during dataset creation. More information on this update can be found here.
If you have any questions, comments or concerns, don’t hesitate to contact us at info@wetransform.to
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Each data format is made with a specific purpose. The data stored in the format, however, may be consumed by a multitude of different applications and users. Since the data format was designed with certain use cases in mind, it may not be well-suited for other functions. As such, it’s important to bridge the gap between a certain format and the needs of end users who want to work with the data.
To enhance data usability, other formats or encodings can be used to complement the default encoding. In the context of INSPIRE, this can be an alternative encoding, i.e. one that fulfills all requirements of the INSPIRE Implementing Rule and thus be used instead of the default encdoing, or it can be an additional encoding.
The goal of such encodings is to act as a link between the default encoding and a use case that is not addressed sufficiently by the default encoding. There are a few questions that must be answered while chosing or developing an encoding, such as:
- Which kind of themes and use cases are you building the alternative encoding for?
- What model transformation rules need to be applied to match the conceptual model to the capabilities of the format’s logical model?
- How can this encoding be implemented?
Thorsten Reitz, CEO of wetransform, presented a webinar that answered these questions. The webinar also presented GeoJSON alternative encodings that are targeted at making INSPIRE data easily usable.
The default encoding for INSPIRE data is complex GML, which is well suited for the interchange of data. Since it has been made with the purpose of interoperability, it does well in terms of providing easy exchange of complex data. Common web applications and web APIs can perform standard operations on data formats that are not nested, however, and have difficulties doing so with nested data formats such as complex GML. According to the MIG Working group, “While INSPIRE data encoded according to the current schemas can be downloaded and viewed, simple use (visualisation, simple joins, visual overlays, spatial search, …) is difficult in standard GIS clients.”
The webinar described how the GeoJSON encoding can help you gain maximum value from your INSPIRE data by making the data more compatible with GIS clients. The GeoJSON alternative encoding can be used instead of the nested INSPIRE GML data. GeoJSON is designed from the ground up to easily be consumed by web applications and web service APIs, thus providing for a use case that is not well-suited to INSPIRE GML. The webinar also covered the most common issues faced while trying to create an alternative encoding, the structure of GeoJSON encoding rules and model transformation rules. It mentioned how to measure the success of alternative encoding and looked at whether the GeoJSON alternative encoding succeeded in making INSPIRE data more usable in a specific target environment.
You can find a link to the webinar here.
Each data format is made with a specific purpose. The data stored in the format, however, may be consumed by a multitude of different applications and users. Since the data format was designed with certain use cases in mind, it may not be well-suited for other functions. As such, it’s important to bridge the gap between a certain format and the needs of end users who want to work with the data.
To enhance data usability, other formats or encodings can be used to complement the default encoding. In the context of INSPIRE, this can be an alternative encoding, i.e. one that fulfills all requirements of the INSPIRE Implementing Rule and thus be used instead of the default encdoing, or it can be an additional encoding.
The goal of such encodings is to act as a link between the default encoding and a use case that is not addressed sufficiently by the default encoding. There are a few questions that must be answered while chosing or developing an encoding, such as:
- Which kind of themes and use cases are you building the alternative encoding for?
- What model transformation rules need to be applied to match the conceptual model to the capabilities of the format’s logical model?
- How can this encoding be implemented?
Thorsten Reitz, CEO of wetransform, presented a webinar that answered these questions. The webinar also presented GeoJSON alternative encodings that are targeted at making INSPIRE data easily usable.
The default encoding for INSPIRE data is complex GML, which is well suited for the interchange of data. Since it has been made with the purpose of interoperability, it does well in terms of providing easy exchange of complex data. Common web applications and web APIs can perform standard operations on data formats that are not nested, however, and have difficulties doing so with nested data formats such as complex GML. According to the MIG Working group, “While INSPIRE data encoded according to the current schemas can be downloaded and viewed, simple use (visualisation, simple joins, visual overlays, spatial search, …) is difficult in standard GIS clients.”
The webinar described how the GeoJSON encoding can help you gain maximum value from your INSPIRE data by making the data more compatible with GIS clients. The GeoJSON alternative encoding can be used instead of the nested INSPIRE GML data. GeoJSON is designed from the ground up to easily be consumed by web applications and web service APIs, thus providing for a use case that is not well-suited to INSPIRE GML. The webinar also covered the most common issues faced while trying to create an alternative encoding, the structure of GeoJSON encoding rules and model transformation rules. It mentioned how to measure the success of alternative encoding and looked at whether the GeoJSON alternative encoding succeeded in making INSPIRE data more usable in a specific target environment.
You can find a link to the webinar here.
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There’s a lot of data published on hale»connect, and it’s important to us that it looks good to you. For this purpose, we’d like you to have the opportunity to publish Styled Layer Descriptors (SLDs.)
The OGC standard Styled Layer Descriptor (SLD) defines an XML format to encode cartographic rules by which to display features. It reuses the OGC standards Symbology Encoding (SE) and Filter Encoding (FE). The SLD standard extends the OGC Web Map Service (WMS). A basic WMS supports named layers and styles which do not enable end-users to define custom symbology. The SLD standard extends the WMS standard to allow users to provide styling rules in a Styled Layer Descriptor file.
The hale»connect platform enables users to provide their own layer styles, or to leverage our own, extensive library of INSPIRE Styled Layer Descriptors, and growing library of XPlanung SLDs. When you publish data on hale»connect, the data is matched against the hale»connect SLD library. SLDs are then applied if available. A default style layer is applied to all datasets for which a matching style layer does not exist. Alternatively, you can upload your own, valid SLDs. Here’s an example of a fully valid SLD file that is ready to be published:
SLD for shapefile
<?xml version="1.0" encoding="UTF-8"?>
<StyledLayerDescriptor
version="1.1.0"
xmlns="http://www.opengis.net/sld"
xmlns:ogc="http://www.opengis.net/ogc"
xmlns:se="http://www.opengis.net/se"
xmlns:xlink="http://www.w3.org/1999/xlink"
xmlns:gml="http://www.opengis.net/gml/3.2"
xmlns:sld="http://www.opengis.net/sld"
xmlns:ns="http://www.esdi-humboldt.eu/hale/shp/myShapefile"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://www.opengis.net/sld http://schemas.opengis.net/sld/1.1.0/sldAll.xsd http://www.opengis.net/se http://schemas.opengis.net/se/1.1.0/FeatureStyle.xsd">
<NamedLayer>
<se:Name>MyShapefileLayer</se:Name>
<UserStyle>
<se:Name>MyStyle</se:Name>
<se:Title>MyStyle</se:Title>
<se:FeatureTypeStyle>
<se:Name>Default Polygon Style</se:Name>
<se:FeatureTypeName>ns:myShapefile</se:FeatureTypeName>
<se:Rule>
<se:Title>Shapefile Polygons</se:Title>
<se:PolygonSymbolizer>
<se:Fill>
<se:SvgParameter name="fill">#78C46E</se:SvgParameter>
<se:SvgParameter name="fill-opacity">0.5</se:SvgParameter>
</se:Fill>
<se:Stroke>
<se:SvgParameter name="stroke">#38A800</se:SvgParameter>
<se:SvgParameter name="stroke-width">1.5</se:SvgParameter>
</se:Stroke>
</se:PolygonSymbolizer>
</se:Rule>
<se:Rule>
<se:MaxScaleDenominator>40000</se:MaxScaleDenominator>
<se:TextSymbolizer>
<se:Label>
<ogc:PropertyName>ns:name/text()</ogc:PropertyName>
</se:Label>
<se:Font>
<se:SvgParameter name="font-family">Arial</se:SvgParameter>
<se:SvgParameter name="font-size">14</se:SvgParameter>
<se:SvgParameter name="font-style">normal</se:SvgParameter>
<se:SvgParameter name="font-weight">bold</se:SvgParameter>
</se:Font>
<se:Halo>
<se:Radius>3</se:Radius>
<se:Fill>
<se:SvgParameter name="fill">#ffffff</se:SvgParameter>
</se:Fill>
</se:Halo>
<se:Fill>
<se:SvgParameter name="fill">#38A800</se:SvgParameter>
</se:Fill>
</se:TextSymbolizer>
</se:Rule>
</se:FeatureTypeStyle>
</UserStyle>
</NamedLayer>
</StyledLayerDescriptor>
Want to learn more about publishing SLDs? We just created an SLD tutorial for users interested in creating their own SLDs for shapefile or GML. You can check it out here.
If you are interested in having us create a custom style for you, please contact support.
There’s a lot of data published on hale»connect, and it’s important to us that it looks good to you. For this purpose, we’d like you to have the opportunity to publish Styled Layer Descriptors (SLDs.)
The OGC standard Styled Layer Descriptor (SLD) defines an XML format to encode cartographic rules by which to display features. It reuses the OGC standards Symbology Encoding (SE) and Filter Encoding (FE). The SLD standard extends the OGC Web Map Service (WMS). A basic WMS supports named layers and styles which do not enable end-users to define custom symbology. The SLD standard extends the WMS standard to allow users to provide styling rules in a Styled Layer Descriptor file.
The hale»connect platform enables users to provide their own layer styles, or to leverage our own, extensive library of INSPIRE Styled Layer Descriptors, and growing library of XPlanung SLDs. When you publish data on hale»connect, the data is matched against the hale»connect SLD library. SLDs are then applied if available. A default style layer is applied to all datasets for which a matching style layer does not exist. Alternatively, you can upload your own, valid SLDs. Here’s an example of a fully valid SLD file that is ready to be published:
SLD for shapefile
<?xml version="1.0" encoding="UTF-8"?>
<StyledLayerDescriptor
version="1.1.0"
xmlns="http://www.opengis.net/sld"
xmlns:ogc="http://www.opengis.net/ogc"
xmlns:se="http://www.opengis.net/se"
xmlns:xlink="http://www.w3.org/1999/xlink"
xmlns:gml="http://www.opengis.net/gml/3.2"
xmlns:sld="http://www.opengis.net/sld"
xmlns:ns="http://www.esdi-humboldt.eu/hale/shp/myShapefile"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://www.opengis.net/sld http://schemas.opengis.net/sld/1.1.0/sldAll.xsd http://www.opengis.net/se http://schemas.opengis.net/se/1.1.0/FeatureStyle.xsd">
<NamedLayer>
<se:Name>MyShapefileLayer</se:Name>
<UserStyle>
<se:Name>MyStyle</se:Name>
<se:Title>MyStyle</se:Title>
<se:FeatureTypeStyle>
<se:Name>Default Polygon Style</se:Name>
<se:FeatureTypeName>ns:myShapefile</se:FeatureTypeName>
<se:Rule>
<se:Title>Shapefile Polygons</se:Title>
<se:PolygonSymbolizer>
<se:Fill>
<se:SvgParameter name="fill">#78C46E</se:SvgParameter>
<se:SvgParameter name="fill-opacity">0.5</se:SvgParameter>
</se:Fill>
<se:Stroke>
<se:SvgParameter name="stroke">#38A800</se:SvgParameter>
<se:SvgParameter name="stroke-width">1.5</se:SvgParameter>
</se:Stroke>
</se:PolygonSymbolizer>
</se:Rule>
<se:Rule>
<se:MaxScaleDenominator>40000</se:MaxScaleDenominator>
<se:TextSymbolizer>
<se:Label>
<ogc:PropertyName>ns:name/text()</ogc:PropertyName>
</se:Label>
<se:Font>
<se:SvgParameter name="font-family">Arial</se:SvgParameter>
<se:SvgParameter name="font-size">14</se:SvgParameter>
<se:SvgParameter name="font-style">normal</se:SvgParameter>
<se:SvgParameter name="font-weight">bold</se:SvgParameter>
</se:Font>
<se:Halo>
<se:Radius>3</se:Radius>
<se:Fill>
<se:SvgParameter name="fill">#ffffff</se:SvgParameter>
</se:Fill>
</se:Halo>
<se:Fill>
<se:SvgParameter name="fill">#38A800</se:SvgParameter>
</se:Fill>
</se:TextSymbolizer>
</se:Rule>
</se:FeatureTypeStyle>
</UserStyle>
</NamedLayer>
</StyledLayerDescriptor>
Want to learn more about publishing SLDs? We just created an SLD tutorial for users interested in creating their own SLDs for shapefile or GML. You can check it out here.
If you are interested in having us create a custom style for you, please contact support.
(more)