Systems and Means of Informatics
2019, Volume 29, Issue 1, pp 74-85
TYPES OF INHOMOGENEITIES IN THE STRUCTURE OF GEODATA GENERALIZATION
Abstract
A holistic description of the multilevel structure of the generalization of geodata containing nonuniform information objects is proposed.
A typology of relations of information objects of various levels of generalization is presented, in the context of which the formal criterion of the property of generalization reversibility is defined. The typology of inhomogeneities arising from the comparison of certain types of information objects and ways to eliminate them are considered. The criterion of heterogeneity of the structure of generalization and the concept of a segment of homogeneous generalization are introduced. Practical examples of nonuniform generalization in topography are given.
[+] References (20)
- Zatsman, I. M. 2018. Metodologiya obratimoy generalizatsii v kontekste klassifikatsii informatsionnykh transformatsiy [Methodology of reversible generalization in the context of classification of information transformations]. Sistemy i Sredstva Informatiki - Systems and Means of Informatics 28(2): 128-144.
- Codd, E. F. 1979. Extending the database relational model to capture more meaning. ACM T. Database Syst. 4(4):395-434.
- Zatsman, I.M., O. S. Mamonova, and A. Yu. Shchurova. 2017. Obratimost' i al'ternativnost' generalizatsii modeley perevoda konnektorov v parallel'nykh tek- stakh [Reversibility and alternativeness of generalization of connectives translations models in parallel texts]. Sistemy i Sredstva Informatiki - Systems and Means of Informatics 27(2):125-142.
- Zatsman, I.M., M. G. Kruzhkov, and E.Yu. Loshchilova. 2017. Metody analiza chastotnosti modeley perevoda konnektorov i obratimost' generalizatsii statisticheskikh dannykh [Methods of frequency analysis of connectives translations and reversibility of statistical data generalization]. Sistemy i Sredstva Informatiki - Systems and Means of Informatics 27 (4): 164-176.
- Nikishin, D. A. 2018. Sopostavlenie osobennostey predstavleniya geodannykh v kar- tografii i geoinformatike [Comparison of characteristics of the representation of geodata in cartography and geoinformatics]. Sistemy i Sredstva Informatiki - Systems and Means of Informatics 28(2):60-74.
- Nikishin, D. A. 2018. Protsessy generalizatsii v analogovoy i tsifrovoy kartografii [A generalization processes in analog and digital cartography]. Sistemy i Sredstva Informatiki - Systems and Means of Informatics 28(3):204-216.
- Rosenbloom, P. S. 2013. On computing: The fourth great scientific domain. Cambridge, MA: MIT Press. 307 p.
- Das Sarma, A., H. Lee, H. Gonzalez, J. Madhavan, and A. Halevy. 2012. Efficient spatial sampling of large geographical tables. ACM SIGMOD Conference (International) on Management of Data Proceedings. New York, NY: ACM. 193-204.
- De Andrade, F.G., C. de Souza Baptista, and H. B. Henriques. 2015. Semantic annotation of geodata based on linked-open data. 7th Conference (International) on Management of Computational and Collective Intelligence in Digital EcoSystems Proceedings. New York, NY: ACM. 9-16.
- Huang, Xin, B. Choi, J. Xu, W. K. Cheung, Y. Zhang, and J. Liu. 2017. Ontology- based graph visualization for summarized view. ACM on Conference on Information and Knowledge Management Proceedings . New York, NY: ACM. 2115-2118.
- Komkov, A. M., S. A. Nikolaev, and N. I. Shilov. 1958. Sostavlenie i redaktirovanie kart [Drafting and editing maps]. Moscow: VIA. 248 p.
- Komissarov, D. V. 2001. Metodika resheniya problem tsifrovogo fototriangulirovaniya [Method of addressing digital phototriangulation]. Conference (International) RDAMM Proceedings. 6(2):213-217.
- Bellahsene, Z., A. Bonifati, and E. Rahm, eds. 2011. Schema matching and mapping. Berlin-Heidelberg: Springer-Verlag. 326 p.
- Chiang, Yao-Yi, Bo Wu, A. Anand, K. Akade, and C. A. Knoblock. 2014. A system for efficient cleaning and transformation of geospatial data attributes. 22nd ACM SIGSPATIAL Conference (International) on Advances in Geographic Information Systems Proceedings. New York, NY: ACM. 577-580.
- Hong-Hai, Do. 2009. Data conflicts. Encyclopedia of database systems. Boston, MA: Springer US, 2009. 565-569.
- Ahlers, D. 2015. Granularity as a qualitative concept for GIR. 9th Workshop on Geographic Information Retrieval Proceedings. New York, NY: ACM. Article No. 4. P. 1-2.
- GIS "Panorama" PARB.00046-03. 2019. Formaty i spetsifikatsii dannykh. Format klassifikatora RSC [Data formats and specifications. The format of the classifier RSC]. Available at: https://gistoolkit.ru/download/doc/formatrsc.pdf (accessed February 12, 2019).
- Getmanova, A.D. 1995. Uchebnik po logike [A textbook on logic]. 2nd ed. Moscow: VLADOS. 303 p.
- Kang, Q., W. Liao, A. Agrawal, and A. Choudhary. 2016. A filtering-based clustering algorithm for improving spatio-temporal kriging interpolation accuracy. 25th ACM Conference (International) on Information and Knowledge Management Proceedings. New York, NY: ACM. 2209-2214.
- Atluri, G., A. Karpatne, and V. Kumar. 2018. Spatio-temporal data mining: A survey of problems and methods. ACM Comput. Surv. 51(4): 1 -41.
[+] About this article
Title
TYPES OF INHOMOGENEITIES IN THE STRUCTURE OF GEODATA GENERALIZATION
Journal
Systems and Means of Informatics
Volume 29, Issue 1, pp 74-85
Cover Date
2019-03-30
DOI
10.14357/08696527190107
Print ISSN
0869-6527
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
geodata; cartographic generalization; generalization of spatial data; digital cartography; geoinformatics
Authors
D. A. Nikishin
Author Affiliations
Institute of Informatics Problems, Federal Research Center "Computer Science
and Control", Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
|