Producing and Using Linked Open Government Data in the TWC LOGD Portal

Lebo, Timothy; Erickson, John S.; Ding, Li; Graves, Alvaro; Williams, Gregory Todd; DiFranzo, Dominic; Li, Xian; Michaelis, James; Zheng, Jin; Flores, Johanna; Shangguan, Zhenning; McGuinness, Deborah L.; Hendler, Jim

doi:10.1007/978-1-4614-1767-5_3

Cited by 25 publications

(17 citation statements)

References 12 publications

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“…This approach initially uses relatively lightweight annotations and associated reasoning. Some of the authors have created and used a conversion tool to take in data and create lightly annotated data automatically [12]. This can be done with little effort since it is an automated effort.…”

Section: Discussionmentioning

confidence: 99%

Provenance Representation for the National Climate Assessment in the Global Change Information System

Tilmes

Fox²,

Ma³

et al. 2013

IEEE Trans. Geosci. Remote Sensing

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The important topic of global climate change builds on a huge collection of scientific research. It is common for agencies releasing climate change information to be served with requests for all supporting materials resulting in a particular conclusion. Capturing and presenting global change provenance, linking to the research papers, data sets, models, analyses, observations, satellites, etc., that support the key research findings in this domain can increase understanding and aid in reproducibility of results and conclusions. The U.S. Global Change Research Program is now coordinating the production of a national climate assessment (NCA) that presents our best understanding of global change. We are now developing a global change information system that will present the content of that report and its provenance, including the scientific support for the findings of the assessment. We are using an approach that will present this information both through a human accessible Web site as well as a machine-readable interface for automated mining of the provenance graph. We plan to use the developing World Wide Web Consortium (W3C) PROV data model and ontology for this system. This paper will describe an overview of the process of developing the NCA and how the provenance trail of the report and each of the technical inputs can be captured and represented using the W3C PROV ontology. This will improve the visibility into the assessment process, increase understanding and possibility of reproducibility, and ultimately increase the credibility and trust of the resulting report.

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Section: Discussionmentioning

confidence: 99%

Provenance Representation for the National Climate Assessment in the Global Change Information System

Tilmes

Fox²,

Ma³

et al. 2013

IEEE Trans. Geosci. Remote Sensing

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“…Because of its focus on interactive data curation, OpenRefine does not yet support automated processing of data through those histories without the use of that user interface. CSV2RDF4LOD [2] is a tool for creating RDF from tabular data, specifying the transformation using an RDF vocabulary. It demonstrates how to incorporate attribution, versioning, provenance, and scheduled automation when aggregating data from multiple, disparate parties.…”

Section: Rdf Refinementioning

confidence: 99%

SETLr: the semantic extract, transform, and load-r

McCusker

Chastain

Rashid

et al. 2018

Preprint

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Abstract. Semantic Extract, Transform, and Load-er (SETLr) is a flexible, scalable tool for providing semantic interpretations to tabular, XML, and JSON-based data from local or web files. It has been used by diverse projects and has shown to be scalable and flexible, allowing for the simplified creation of arbitrary RDF, including ontologies and nanopublications, from many different data formats. Semantic ETL scripts use best practice standards for provenance (PROV-O) and support streaming conversion for RDF transformation using the JSON-LD based templating language, JSLDT. SETLr also supports custom Python functions for remote APIs, entity resolution, external data lookup, or other tasks. We provide case studies for dynamic SETL scripts, ontology generation, and scaling to gigabytes of input and discuss the value and impact of this approach.

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“…The SDV organization principle [11] organizes the many individual ExtractTransform-Load (ETL) processes that a data corpus or application may require according to three fundamental provenance aspects:…”

Section: Prizms' "Sdv" Dataset Organization: Source Dataset Versionmentioning

confidence: 99%

“…The Prizms system emerged from the need to create high quality Linked Data [11] and has evolved into a Linked Data platform geared towards replicability, reproducibility, and transparency of the data that it publishes. Prizms supports the many Extract-Transform-Load processes that may be required to integrate a variety of others' data about a topic of interest, and it provides for consistent provenance capture, metadata descriptions, and hosting using best practices.…”

Section: Introductionmentioning

confidence: 99%

Walking into the Future with PROV Pingback: An Application to OPeNDAP Using Prizms

Lebo

West

McGuinness

2015

Lecture Notes in Computer Science

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Abstract. Adding provenance to existing systems can benefit users, but comes at an expense that may be difficult for some to justify. This tradeoff can be overcome by increasing the value of provenance, by decreasing the cost to add it -or by doing both. This paper offers a contribution for each. First, we develop further the W3C PROV pingback technique so that it may reach its potential to interconnect provenance records that would traditionally sit in isolation, thus increasing their value. Second, we reduce the expense to publish the provenance of existing host systems by using minimal coupling to the Prizms Linked Data platform. Using an Earth Sciences scenario and the OPeNDAP data transport architecture as an example host system, we investigate how PROV pingback could work in practice, demonstrate its potential, and identify outstanding issues that must be addressed before it can be widely adopted.

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Producing and Using Linked Open Government Data in the TWC LOGD Portal

Cited by 25 publications

References 12 publications

Provenance Representation for the National Climate Assessment in the Global Change Information System

Provenance Representation for the National Climate Assessment in the Global Change Information System

SETLr: the semantic extract, transform, and load-r

Walking into the Future with PROV Pingback: An Application to OPeNDAP Using Prizms

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