Publikasjoner
NIBIOs ansatte publiserer flere hundre vitenskapelige artikler og forskningsrapporter hvert år. Her finner du referanser og lenker til publikasjoner og andre forsknings- og formidlingsaktiviteter. Samlingen oppdateres løpende med både nytt og historisk materiale. For mer informasjon om NIBIOs publikasjoner, besøk NIBIOs bibliotek.
2022
Forfattere
Lars Aksel OpsahlSammendrag
When you care about data integrity of spatial data you need to know about the limitations/weaknesses of using simple feature datatype in your database. For instance https://land.copernicus.eu/pan-european/corine-land-cover/clc2018 contains 2,377,772 simple features among which we find 852 overlaps and 1420 invalid polygons. For this test I used “ESRI FGDB” file and gdal for import to postgis. We find such minor overlaps and gaps quite often, which might not be visible for the human eye. The problem here is that it covers up for real errors and makes difficult to enforce database integrity constraints for this. Close parallel lines also seems to cause Topology Exception in many spatial libraries. A core problem with simple features is that they don't contain information about the relation they have with neighbor features, so integrity of such relations is hard to constraint. Another problem is mixing of old and new data in the payload from the client. This makes it hard and expensive to create clients, because you will need a full stack of spatial libraries and maybe a complete locked exact snapshot of your database on the client side. Another thing is that a common line may differ from client to client depending on spatial lib, snapTo usage, tolerance values and transport formats. In 2022 many system are depending on live updates also for spatial data. So it’s big advantage to be able to provide a simple and “secure” API’s with fast server side integrity constraints checks that can be used from a standard web browser. When we have this checks on server side we will secure the equal rules across different clients. Is there alternatives that can secure data integrity in a better way? Yes, for instance Postgis Topology. The big difference is that Postgis Topology has more open structure that is realized by using standard database relational features. This lower the complexity of the client and secures data integrity. In the talk “Use Postgis Topology to secure data integrity, simple API and clean up messy simple feature datasets.” we will dive more into the details off Postgis Topology Building an API for clients may be possible using simple features, but it would require expensive computations to ensure topological integrity but to solve problem with mixing of new and old borders parts can not be solved without breaking the polygon up into logical parts. Another thing is attribute handling, like if you place surface partly overlapping with another surface should that have an influence on the attributes on the new surface. We need to focus more on data integrity and the complexity and cost of creating clients when using simple feature, because the demands for spatial data updated in real time from many different clients in a secure and consistent way will increase. This will be main focus in this talk. https://www.slideshare.net/laopsahl/dataintegrityriskswhenusingsimplefeaturepdf
Forfattere
Nicolai MunsterhjelmSammendrag
Det er ikke registrert sammendrag
Forfattere
Nicolai MunsterhjelmSammendrag
Det er ikke registrert sammendrag
Forfattere
Nicolai MunsterhjelmSammendrag
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Forfattere
Bjørn Tobias BorchseniusSammendrag
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Forfattere
Bjørn Tobias BorchseniusSammendrag
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Forfattere
Anne B. NilsenSammendrag
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Sammendrag
Sustainable water resources management roots in monitoring data reliability and a full engagement of all institutions involved in the water sector. When competences and interests are overlapping, however, coordination may be difficult, thus hampering cooperative actions. This is the case of Santa Cruz Island (Galápagos, Ecuador). A comprehensive assessment on water quality data (physico-chemical parameters, major elements, trace elements and coliforms) collected since 1985 revealed the need of optimizing monitoring efforts to fill knowledge gaps and to better target decision-making processes. A Water Committee (Comité de la gestión del Agua) was established to foster the coordinated action among stakeholders and to pave the way for joint monitoring in the island that can optimize the efforts for water quality assessment and protection. Shared procedures for data collection, sample analysis, evaluation and data assessment by an open-access geodatabase were proposed and implemented for the first time as a prototype in order to improve accountability and outreach towards civil society and water users. The overall results reveal the high potential of a well-structured and effective joint monitoring approach within a complex, multi-stakeholder framework.
Forfattere
Henrik Forsberg MathiesenSammendrag
Det er ikke registrert sammendrag
Forfattere
Henrik Forsberg MathiesenSammendrag
Det er ikke registrert sammendrag