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Kaskadna nekakovost geodetskih podatkov
ID Legen, Urška (Author), ID Filipčič, Tjaša (Mentor) More about this mentor... This link opens in a new window, ID Radovan, Dalibor (Author)

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PID: 20.500.12556/rul/9c65dd9d-e5ed-4240-abd2-61c1ca6081f3

Abstract
Geodetska stroka uporabnikom zagotavlja geodetske podatke s področja osnovnega geodetskega sistema, nepremičnin in topografije, ti pa jih uporabljajo skupaj z drugimi prostorskimi podatki. Kakovost takšnih aplikacij je odvisna od kakovosti podatkov, pri čemer pa se tako ponudniki kot uporabniki podatkov premalo zavedajo kaskadnega prenosa napak z nekakovostne primarne ravni podatkov na druge, sekundarne, izvedene podatke. Geodezija je tradicionalno obravnavala napake predvsem kot položajne pogreške po zakonu o prenosu pogreškov, od obdobja vsesplošne digitalizacije geodetskih podatkov v devetdesetih letih pa se njihova kakovost, predvsem v povezavi z uporabo v geografskih informacijskih sistemih, opredeljuje tudi s standardiziranimi parametri kakovosti in metapodatkov, pri čemer je položajna natančnost le eden od njih. Žal se pri tem zakriva vedenje, kateri podatek je referenčen in na kaj se relativno nanaša specificirana kakovost. V članku je zato obrazložen in uporabljen pojem »kaskadnost«, saj najbolje izraža, da je za dvig kakovosti potrebna stopenjska izboljšava, ki se začne pri temeljnih referenčnih podatkih in semantičnih definicijah objektnih tipov, šele zatem je smiselno ažuriranje in usklajevanje sekundarnih podatkov, ki so nastali na podlagi referenčnih. V članku so opisani vzroki, ki spreminjajo paradigmo in način obravnavanja kakovosti. Ker kaskadna slaba kakovost geodetskih podatkov lahko resno ogrozi ugled geodetske stoke, so opisani sodobni primeri aplikacij in projektov, pri katerih se je to že zgodilo. V sklepu so podani predlogi za izboljšanje stanja.

Language:Unknown
Keywords:kakovost geodetskega podatka, referenčni podatek, hierarhija, kaskadni prenos napak
Work type:Not categorized
Organization:FGG - Faculty of Civil and Geodetic Engineering
Publisher:Zveza geodetov Slovenije
Year:2011
Number of pages:205-214
Numbering:55
PID:20.500.12556/RUL-68414 This link opens in a new window
ISSN:0351-0271
Publication date in RUL:10.07.2015
Views:1810
Downloads:431
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Secondary language

Language:Unknown
Title:Cascading poor quality of geodetic data
Abstract:
The geodetic profession provides geodetic data obtained in the fields of fundamental geodetic system, real estate and topography Users integrate this data with other spatial data. The quality of such applications depends on the data quality; however, the providers and the users are not sufficiently aware of the cascading transfer of errors from the primary data layers to the secondary, derived data. Geodesy has traditionally considered errors mainly as positional errors, according to the law of the transfer of errors. Since the era of widespread digitizing of geodetic data began in the 1990s, data quality in the realm of geographic information systems has been expressed with the standardized parameters of data quality and with metadata, of which positional accuracy is just one type. Unfortunately in this way, the knowledge about which data is a reference can be obscured. To many users, it is not clear what is the specified quality referred to. This article describes, and intentionally uses, the term `cascading' since for the rise of data quality one needs to upgrade data level by data level, starting first with the reference data and the semantic definitions of object types, and continuing by updating and harmonizing the secondary data, which were developed from the primary level. The reasons for the change of paradigm regarding the treatment of quality are considered. As the cascading poor quality of geodetic data can become a serious threat for the reputation of the profession of geodesy, several contemporary applications and projects are described in which this has already happened. In the conclusion, proposals are given for improving the situationion.

Keywords:spatial data quality, reference data, hierarchy, cascading errors

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