A Geospatial Cyberinfrastructure for Urban Economic Analysis and Spatial Decision-Making

abstract: Urban economic modeling and effective spatial planning are critical tools towards achieving urban sustainability. However, in practice, many technical obstacles, such as information islands, poor documentation of data and lack of software platforms to facilitate virtual collaboration, are challenging the effectiveness of decision-making processes. In this paper, we report on our efforts to design and develop a geospatial cyberinfrastructure (GCI) for urban economic analysis and simulation. This GCI provides an operational graphic user interface, built upon a service-oriented architecture to allow (1) widespread sharing and seamless integration of distributed geospatial data; (2) an effective way to address the uncertainty and positional errors encountered in fusing data from diverse sources; (3) the decomposition of complex planning questions into atomic spatial analysis tasks and the generation of a web service chain to tackle such complex problems; and (4) capturing and representing provenance of geospatial data to trace its flow in the modeling task. The Greater Los Angeles Region serves as the test bed. We expect this work to contribute to effective spatial policy analysis and decision-making through the adoption of advanced GCI and to broaden the application coverage of GCI to include urban economic simulations

Full Metadata Object profiling for flexible geoprocessing workflows

The design and running of complex geoprocessing workflows is an increasingly common geospatial modelling and analysis task. The Business Process Model and Notation (BPMN) standard, which provides a graphical representation of a workflow, allows stakeholders to discuss the scientific conceptual approach behind this modelling while also defining a machine-readable encoding in XML. Previous research has enabled the orchestration of Open Geospatial Consortium (OGC) Web Processing Services (WPS) with a BPMN workflow engine. However, the need for direct access to pre-defined data inputs and outputs results in a lack of flexibility during composition of the workflow and of efficiency during execution. This article develops metadata profiling approaches, described as two possible configurations, which enable workflow management at the meta-level through a coupling with a metadata catalogue. Specifically, a WPS profile and a BPMN profile are developed and tested using open-source components to achieve this coupling. A case study in the context of an event mapping task applied within a big data framework and based on analysis of the Global Database of Event Language and Tone (GDELT) database illustrates the two different architectures

Building the IDECi-UIB: the scientific spatial data infrastructure node for the Balearic Islands University

Technical and methodological enhancements in Information Technologies (IT) and Geographical Information Systems (GIS) has permitted the growth in Spatial Data Infrastructures (SDI) performance. In this way, their uses and applications have grown very rapidly. In the scientific and educational working fields, different institutions and organisations have bet for its use enforcing information exchange that allows researchers to improve their studies as well as give a better dissemination within the scientific community. Therefore, the GIS and Remote Sensing Service (SSIGT) at the Balearic Islands University (UIB) has decided to build and launch its own SDI to serve scientific Geo-Information (GI) throughout the Balearic Islands society focussing on the university community. By these means it intends to boost the development of research and education focusing on the field of spatial information. This article tries to explain the background ideas that form the basic concept of the scientific SDI related to the concepts of e-Science and e-Research. Finally, it explains how these ideas are taken into practice into the new University Scientific SDI

A provenance metadata model integrating ISO geospatial lineage and the OGC WPS : conceptual model and implementation

Nowadays, there are still some gaps in the description of provenance metadata. These gaps prevent the capture of comprehensive provenance, useful for reuse and reproducibility. In addition, the lack of automated tools for capturing provenance hinders the broad generation and compilation of provenance information. This work presents a provenance engine (PE) that captures and represents provenance information using a combination of the Web Processing Service (WPS) standard and the ISO 19115 geospatial lineage model. The PE, developed within the MiraMon GIS & RS software, automatically records detailed information about sources and processes. The PE also includes a metadata editor that shows a graphical representation of the provenance and allows users to complement provenance information by adding missing processes or deleting redundant process steps or sources, thus building a consistent geospatial workflow. One use case is presented to demonstrate the usefulness and effectiveness of the PE: the generation of a radiometric pseudo-invariant areas bench for the Iberian Peninsula. This remote-sensing use case shows how provenance can be automatically captured, also in a non-sequential complex flow, and its essential role in the automation and replication tasks in work with very large amounts of geospatial data

W3C PROV to describe provenance at the dataset, feature and attribute levels in a distributed environment

Provenance, a metadata component referring to the origin and the processes undertaken to obtain a specific geographic digital feature or product, is crucial to evaluate the quality of spatial information and help in reproducing and replicating geospatial processes. However, the heterogeneity and complexity of the geospatial processes, which can potentially modify part or the complete content of datasets, make evident the necessity for describing geospatial provenance at dataset, feature and attribute levels. This paper presents the application of W3C PROV, which is a generic specification to express provenance records, for representing geospatial data provenance at these different levels. In particular, W3C PROV is applied to feature models, where geospatial phenomena are represented as individual features described with spatial (point, lines, polygons, etc.) and non-spatial (names, measures, etc.) attributes. This paper first analyses the potential for representing geospatial provenance in a distributed environment at the three levels of granularity using ISO 19115 and W3C PROV models. Next, an approach for applying the generic W3C PROV provenance model to the geospatial environment is presented. As a proof of concept, we provide an application of W3C PROV to describe geospatial provenance at the feature and attribute levels. The use case presented consists of a conflation of the U.S. Geological Survey dataset with the National Geospatial-Intelligence Agency dataset. Finally, an example of how to capture the provenance resulting from workflows and chain executions with PROV is also presented. The application uses a web processing service, which enables geospatial processing in a distributed system and allows to capture the provenance information based on the W3C PROV ontology at the feature and attribute levels

Automatic Generation of Geospatial Metadata for Web Resources

Web resources that are not part of any Spatial Data Infrastructure can be an important source of information. However, the incorporation of Web resources within a Spatial Data Infrastructure requires a significant effort to create metadata. This work presents an extensible architecture for an automatic characterisation of Web resources and a strategy for assignation of their geographic scope. The implemented prototype generates automatically geospatial metadata for Web pages. The metadata model conforms to the Common Element Set, a set of core properties, which is encouraged by the OGC Catalogue Service Specification to permit the minimal implementation of a catalogue service independent of an application profile. The performed experiments consisted in the creation of metadata for Web pages of providers of Geospatial Web resources. The Web pages have been gathered by a Web crawler focused on OGC Web Services. The manual revision of the results has shown that the coverage estimation method applied produces acceptable results for more than 80% of tested Web resources

Integration of Remote Sensing Data in a Cloud Computing Environment

With the rapid development of remote sensingltechnology, our ability to obtain remote sensing data haslbeen improved to an unprecedented level. We have enteredlan era of big data. Remote sensing data clear showing thelcharacteristics of Big Data such as hyper spectral, highlspatial resolution, and high time resolution, thus, resultinglin a significant increase in the volume, variety, velocity andlveracity of data.This paper and in view of the current issuesof remote sensing data integration, we proposed an OODT-baseddata integration framework. Specifically, aiming at heterogeneousfeatures of multi-source remote sensing data, we proposed an ISO19115-2:2009-based metadata transform method to achieve unityof metadata format in the distributed sub-centers. Constructingla distributed executed engine based on dask ensures thelefficient analysis of large-scale RS data. This work couldlprovide a convenient and efficient multidimensional datalservices for many remote sens-ing applications.

Geospatial Workflows and Trust: a Use Case for Provenance

At first glance the Astronomer by Vermeer, Tutankhamun’s burial mask, and a geospatial workflow may appear to have nothing in common. However, a commonality exists; each of these items can have a record of provenance detailing their history. Provenance is a record that shows who did what to an object, where this happened, and how and why these actions took place. In relation to the geospatial domain, provenance can be used to track and analyze the changes data has undergone in a workflow, and can facilitate scientific reproducibility. Collecting provenance from geospatial workflows and finding effective ways to use this provenance is an important application. When using geospatial data in a workflow it is important to determine if the data and workflow used are trustworthy. This study examines whether provenance can be collected from a geospatial workflow. Each workflow examined is a use case for a specific type of geospatial problem. In addition to this, the collected provenance is then used to determine workflow trust and content trust for each of the workflows examined in this study. The results of this study determined that provenance can be collected from a geospatial workflow in such a way as to be of use to additional applications, such as provenance interchange. From this collected provenance, content trust and workflow trust can be estimated. The simple workflow had a content trust value of .83 (trustworthy) and a workflow trust value of .44 (untrustworthy). Two additional workflows were examined for content trust and workflow trust. The methods used to calculate content trust and workflow trust could also be expanded to other types of geospatial data and workflows. Future research could include complete automation of the provenance collection and trust calculations, as well as examining additional techniques for deciding trust in relation to workflows