Matches in Ruben’s data for { ?s ?p ?o }
- publication author me.
- publication creator seth_van_hooland.
- publication creator rik_van_de_walle.
- publication creator max_de_wilde.
- publication creator erik_mannens.
- publication creator me.
- publication about publication.
- publication about Linked_Data.
- publication about Semantic_Web.
- publication about World_Wide_Web.
- publication author seth_van_hooland.
- publication author rik_van_de_walle.
- publication author max_de_wilde.
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- publication type ScholarlyArticle.
- publication type Article.
- publication type Document.
- publication type Q386724.
- publication type CreativeWork.
- publication type Document.
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- publication type Document.
- publication P50 seth_van_hooland.
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- publication P50 max_de_wilde.
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- publication P50 me.
- publication maker seth_van_hooland.
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- publication maker me.
- publication title "Free Your Metadata: Inexpensive, Straightforward Linked Data".
- publication isPartOf open_government_data_camp.
- publication name "Free Your Metadata: Inexpensive, Straightforward Linked Data".
- publication label "Free Your Metadata: Inexpensive, Straightforward Linked Data".
- publication name "Free Your Metadata: Inexpensive, Straightforward Linked Data".
- publication topic publication.
- publication topic Linked_Data.
- publication topic Semantic_Web.
- publication topic World_Wide_Web.
- publication subject publication.
- publication subject Linked_Data.
- publication subject Semantic_Web.
- publication subject World_Wide_Web.
- publication authorList b0_b3516.
- publication topic publication.
- publication topic Linked_Data.
- publication topic Semantic_Web.
- publication topic World_Wide_Web.
- publication abstract "Publishing legacy data as Linked Data is too technical for most people, so this process needs expensive IT consulting. This high cost, balanced against sometimes underestimated benefits, might hold back governments from publishing Linked Data. To cut back on these costs, we illustrate how people with a non-technical background can use Google Refine to link their data to the Linked Data Cloud. Our straightforward method involves three steps: cleaning, reconciliation, and linking. In tests with several large data sets, over 80% of records could be connected to the Semantic Web in an almost automated process. In the end, the data set is in far better shape to either publish directly on the Web, or to pass to a higher level of processing, which will now be far less expensive. This way, we provide a substantial amount of enhancements that non-experts can perform on their own data, facilitating publication of Linked Data. Our belief is that, given the right tools, Linked Open Government Data can become a realistic goal even under tight schedules and limited budgets.".
- publication datePublished "2011".
- publication mainEntityOfPage verborgh_ogdcamp_2011.
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- publication author max_de_wilde.
- publication author me.
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- publication about World_Wide_Web.
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- publication type ScholarlyArticle.
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- publication type Document.
- publication type Q386724.
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- publication title "Using OpenRefine".
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- publication label "Using OpenRefine".
- publication name "Using OpenRefine".
- publication topic World_Wide_Web.
- publication subject World_Wide_Web.
- publication authorList b0_b3309.
- publication topic World_Wide_Web.
- publication abstract "Data is supposed to be the new gold, but how can you unlock the value in your data? Managing large datasets used to be a task for specialists, but you don’t have to worry about inconsistencies or errors anymore. OpenRefine lets you clean, link, and publish your dataset in a breeze. Using OpenRefine takes you on a practical tour of all the handy features of this well-known data transformation tool. It is a hands-on recipe book that teaches you data techniques by example. Starting from the basics, it gradually transforms you into an OpenRefine expert. This book will teach you all the necessary skills to handle any large dataset and to turn it into high-quality data for the Web. After you learn how to analyze data and spot issues, we’ll see how we can solve them to obtain a clean dataset. Messy and inconsistent data is recovered through advanced techniques such as automated clustering. We’ll then show extract links from keyword and full-text fields using reconciliation and named-entity extraction. Using OpenRefine is more than a manual: it’s a guide stuffed with tips and tricks to get the best out of your data.".
- publication datePublished "2013".
- publication mainEntityOfPage verborgh_packt_2013.
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- publication author steffen_stadtmuller.
- publication author rik_van_de_walle.
- publication author mohsen_taheriyan.