RESEARCH HIGHLIGHTS:
# An old record is not a data but now defined as a new semantic dataset.
i.e. its triples, graphs, links, file formats ...
i.e. its revised, vocabulary encoded versions ...
ex. data:d2148340 a dcat:dataset. #files:json-ld, ttl, XML
# A new method to curate, publish & visualize LOD graphs via CKAN portal.
i.e. two models for one dataset published in two views.
ex. data:d2148340 a dcat:dataset. # Dublin Core @schema1
ex. data:d2148340 a data:Refined. # more semantics@schema2
# Validation & Reproducibility: Provenance and Contexts are in details.
Introduction
In order to enhance the reuse value of existing datasets, it is now becoming a general practice to add semantic links among the records in a dataset, and to link these records to external resources. The enriched datasets are published on the Web for both the human and the machine to consume and re-purpose.
The concrete outcome of this research work is the following:
Open Data Web (data.odw.tw) |
In the paper, we make use of publicly available structured records from a digital archive catalogue, and we demonstrate a principled approach to converting the records into semantically rich and interlinked resources for all to reuse.
While exploring the various issues involved in the process of reusing and re-purposing existing datasets, we review the recent progress in the field of Linked Open Data (LOD), and examine twelve well-known knowledge bases built with a Linked Data approach. We also discuss the general issues of data quality, metadata vocabularies, and data provenance.
Different Contexts in Different Data Curation Phases |
The concrete outcome of this research work is the following:
- a website/repository (Open Data Web) that hosts more than 840,000 semantically enriched catalogue records across multiple subject areas,
- a lightweight ontology voc4odw for describing data reuse and provenance, among others, and
- a set of open source software tools available to all to perform the kind of data conversion and enrichment we did in this research. We have used and extended CKAN (The Comprehensive Knowledge Archive Network) as a platform to host and publish Linked Data.
Five of them are built by domain knowledge experts (OpenCyc, Getty Art and Architecture Thesaurus (AAT), Getty Thesaurus of Geographic Names (TGN), and Ordnance Survey/ Open Names), six of them are collaborative databases (Freebase, YAGO, DBpedia, Wikidata, LinkedGeoData, GeoNames), and the last one is about ecological observations based on expert and community collaborations (Encyclopedia of Life/ EOL/ TraitBank). We further compare datasets about geospatial entities with controlled vocabularies: Getty TGN, Open Names (Ordnance Survey), DBpediaPlace*(instances of dbo:Place), LinkedGeoData, and GeoNames.
To make good reuse of structured data, ones need to first deal with the problem of data quality. Currently there exist different evaluation criteria, with various techniques for measuring the quality of information, data, metadata, and Linked Data.
LOD Knowledge Graph | since | organization | domain | resource | triples | update frequency | data source | |
Expert Lead (top down) | 2008 | business | cross-domain | 41,029 | 2,412,520 | over one year | owner | |
2014 | business | art & | 45,327 | 13,259,890 | 3-5 times a year | owner | ||
2014 | business | place name | 2,495,100 | 204,614,290 | owner | |||
2010 | government | geography | 2,938,707 | 58,377,209 | depending | owner | ||
2015 | government | place name | 925,157 | 21,360,688 | twice a year | |||
Collective Collaboration (bottom up) | 2008 | business | cross-domain | 49,947,799 | 3,124,791,156 | close din 2015 | ||
2007 | university | cross-domain | 5,130,031 | 1,001,461,786 | over one year | |||
2007 | university | cross-domain | 5,109,890 | 402,086,316 | about one year/ some in Live. | |||
DBpediaPlace* | 2007 | university | place (name) | 816,252 | 53,895,946 | |||
2012 | NGO | cross-domain | 19,367,201 | 1,371,170,022 | real time | |||
2010 | university | geography | > 3 billion | 1,384,887,500 | about one year | |||
2010 | NGO | place name | >6.2 million | 93,896,732 | real Time | data collaboration/ partly integrated with others | ||
Mix Mode | 2014 | association | biodiversity | 10,753,384 | 359,292,712 | statistic data/ a week | research databases integration/ partly collaborated |
We review four papers on data quality and systematically compare their evaluation criteria. Moreover, data provenance --- contextual metadata about the source and use of data --- has proven to be fundamental for assessing authenticity, enabling trust, and allowing reproducibility. Thus, we examine key mechanisms of data provenance before we move forward to discussing LOD applications.