Designing a Language for Spatial Computing

Kuhn, Walther; Ballatore, Andrea

doi:10.1007/978-3-319-16787-9_18

Cited by 40 publications

(61 citation statements)

References 18 publications

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“…This requires abstracting from particular tools and data sets and describing data analysis on a conceptual level [40], which would allow partial adaption of workflows across computing environments. It would also allow analysts to focus on the questions they want to answer and the methods to answer them, instead of the software and data formats needed for computation [41,42]. A particular challenge is to decide when such adaptions can be considered meaningful [18].…”

Section: The Curse Of Modularity: Arguments From Reusability Of Analysismentioning

confidence: 99%

“…Semantic technology could support analysts in deciding whether such derivation tools are meaningfully applicable to a data set [55]. Also they could help them in formulating an appropriate hypothesis that corresponds to a research question [42,56]. As another example, in the geosciences, georeferencing information (assigning coordinates to information including a textual reference to a place) is an important and ubiquitous step.…”

Section: Selection Of Datamentioning

confidence: 99%

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Why good data analysts need to be critical synthesists. Determining the role of semantics in data analysis

Scheider¹,

Ostermann²,

Adams

2017

Future Generation Computer Systems

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In this article, we critically examine the role of semantic technology in data driven analysis. We explain why learning from data is more than just analyzing data, including also a number of essential synthetic parts that suggest a revision of George Box's model of data analysis in statistics. We review arguments from statistical learning under uncertainty, workflow reproducibility, as well as from philosophy of science, and propose an alternative, synthetic learning model that takes into account semantic conflicts, observation, biased model and data selection, as well as interpretation into background knowledge. The model highlights and clarifies the different roles that semantic technology may have in fostering reproduction and reuse of data analysis across communities of practice under the conditions of informational uncertainty. We also investigate the role of semantic technology in current analysis and workflow tools, compare it with the requirements of our model, and conclude with a roadmap of 8 challenging research problems which currently seem largely unaddressed.

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Section: The Curse Of Modularity: Arguments From Reusability Of Analysismentioning

confidence: 99%

Section: Selection Of Datamentioning

confidence: 99%

Why good data analysts need to be critical synthesists. Determining the role of semantics in data analysis

Scheider¹,

Ostermann²,

Adams

2017

Future Generation Computer Systems

View full text Add to dashboard Cite

show abstract

“…This conceptualization of scale as an information filter cannot be determined in an absolute sense but depends on the hierarchical organization. Transferred to the geospatial domain, it means that smaller geographical units are constrained by larger ones within a certain hierarchical distance and decreasing spatial granularity (Kuhn & Ballatore, 2015). This spatial granularity goes hand in hand with semantic depth, to be expressed in levels of ontologies.…”

Section: Introductionmentioning

confidence: 99%

Urban green valuation integrating biophysical and qualitative aspects

Lang

2017

European Journal of Remote Sensing

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Urban green mapping has become an operational task in city planning, urban land management, and quality of life assessments. As a multi-dimensional, integrative concept, urban green comprising several ecological, socio-economic, and policy-related aspects. In this paper, the author advances the representation of urban green by deriving scale-adapted, policy-relevant units. These so-called geons represent areas of uniform green valuation under certain size and homogeneity constraints in a spatially explicit representation. The study accompanies a regular monitoring scheme carried out by the urban municipality of the city of Salzburg, Austria, using optical satellite data. It was conducted in two stages, namely SBG_QB (10.2 km², QuickBird data from 2005) and SBG_WV (140 km², WorldView-2 data from 2010), within the functional urban area of Salzburg. The geon delineation was validated by several quantitative measures and spatial analysis techniques, as well as ground documentation, including panorama photographs and visual interpretation. The spatial association pattern was assessed by calculating Global Moran’s I with incremental search distances. The final geonscape, consisting of 1083 units with an average size of 13.5 ha, was analyzed by spatial metrics. Finally, categories were derived for different types of functional geons. Future research paths and improvements to the described strategy are outlined.

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“…KuhnandBallatore [9] developed a language for spatial computing that uses the core concepts of spatial information [10] for translating a spatial problem into an analysis workflow. The motivation of their work is an abstraction from GIS terminology and concepts that do not relate to the spatial problem that users actually try to solve.…”

Section: Improved Workflow Developmentmentioning

confidence: 99%

“…User support in this context can address the translation of spatial questions into workflows, the discovery of suitable data and operations, and the validation of chains of operations. The proposed approaches put different components of the workflow development process at their centre; core concepts of spatial information [9,10], data [7,11], operations [12,13], domain knowledge [6], and workflow verification [14].…”

Section: Introductionmentioning

confidence: 99%

Coupling Knowledge with GIS Operations: The Benefits of Extended Operation Descriptions

Hofer

Papadakis

Mäs

2017

IJGI

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Abstract:The automated development of spatial analysis workflows is one of the envisioned benefits of Web services that provide geoprocessing functionality. Automated workflow development requires the means to translate a user objective into a series of geographic information system (GIS) operations and to evaluate the match between data and operations. Even though full automation is yet out of reach, users benefit from formalized knowledge about operations that is available during workflow development. This article presents user support during workflow development based on a recent approach to extended operation descriptions. User support thereby focuses on the discovery of operations across GIS tools and the validation of chains of spatial analysis operations. The required knowledge about operations is stored in a knowledge base, which builds on an approach called geooperators and extends the geooperator approach with a data-type ontology for describing the interfaces of geooperators and for expressing constraints of geooperator inputs. The advantages of the knowledge base are demonstrated for the construction of a multi-criteria decision making workflow. This workflow contains a set of pre-processing tasks for the input datasets and eventually the calculation of a cost distance raster. A critical discussion of the complexity of the knowledge base and a comparison with existing approaches complement this contribution.

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Designing a Language for Spatial Computing

Cited by 40 publications

References 18 publications

Why good data analysts need to be critical synthesists. Determining the role of semantics in data analysis

Why good data analysts need to be critical synthesists. Determining the role of semantics in data analysis

Urban green valuation integrating biophysical and qualitative aspects

Coupling Knowledge with GIS Operations: The Benefits of Extended Operation Descriptions

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