The Web is My Back-end: Creating Mashups with Linked Open Government Data

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

doi:10.1007/978-1-4614-1767-5_10

Cited by 18 publications

(13 citation statements)

References 8 publications

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“…The White House Visitor Log 24 is a demo mashup made at Rensselaer Polytechnic Institute which shows how different sources of data can be mashed up in a single application. On this website users can search for the visitors to the White House-the data are taken from data.gov-and the search results are enriched with DBpedia data, as many of the visitors are prominent politicians with their own Wiki pages [10]. Similarly, Academia Europea 25 has many members whose profile page was created with the help of DBpedia and DBLP data [19].…”

Section: Identifyingmentioning

confidence: 99%

“…9 Especially the notability test: https://en.wikipedia.org/wiki/Wikipedia:Notability. 10 http://wiki.freebase.com/wiki/WEX. is acknowledged.…”

Section: Freebasementioning

confidence: 99%

“…Freebase's extraction framework 10 (WEX) transforms Wikipedia articles available as wikitext into a wellformed and structured XML dump, opening it up for other projects without the need to deal with peculiarities of wikitext. Both DBpedia and Freebase data are free as in 'free speech', they are made available under a Creative Commons Attribution license that allows both derivative works and commercial use as long as the source 7 http://www.freebase.com/.…”

Section: Freebasementioning

confidence: 99%

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DBpedia Mashups

Héder¹,

Solt²

2013

Semantic Mashups

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If you see Wikipedia as a main place where the knowledge of mankind is concentrated, then DBpedia-which is extracted from Wikipedia-is the best place to find the machine representation of that knowledge. DBpedia constitutes a major part of the semantic data on the web. Its sheer size and wide coverage enables you to use it in many kind of mashups: it contains biographical, geographical, bibliographical data; as well as discographies, movie metadata, technical specifications, and links to social media profiles and much more. Just like Wikipedia, DBpedia is a truly cross-language effort, e.g., it provides descriptions and other information in various languages. In this chapter we introduce its structure, contents, and its connections to outside resources. We describe how the structured information in DBpedia is gathered, what you can expect from it and what are its characteristics and limitations. We analyze how other mashups exploit DBpedia and present best practices of its usage. In particular, we describe how Sztakipedia-an intelligent writing aid based on DBpedia-can help Wikipedia contributors to improve the quality and integrity of articles. DBpedia offers a myriad of ways to accessing the information it contains, ranging from SPARQL to bulk download. We compare the pros and cons of these methods. We conclude that DBpedia is an unavoidable resource for applications dealing with commonly known entities like notable persons, places; and for others looking for a rich hub connecting other semantic resources. IntroductionIn this section, we take a closer look at Wikipedia itself, then we examine the process by which DBpedia extracts information from it. WikipediaBy now, Wikipedia is a big ubiquitous collaborative encyclopedia counting over 10 million articles in over 200 languages. Readers are very active: Wikipedia receives over 10 billion page views per month and over 200 thousand edits per day. However, growth in article count and number of contributions no longer seems to be exponential for the largest English language edition. 1 For our purposes, contrasting Wikipedia to traditional printed works is not essential, but it allows us to draw attention to some of its key characteristics. Wikipedia is not governed by a formal editorial board, but instead by the community and its self-imposed guidelines, decision making and escalation processes. Unavoidably, the coverage of articles in a given language edition is biased towards public interest of the Wikipedians speaking the language. The English language Wikipedia has been found to be on a par in accuracy with Encyclopaedia Britannica [12], and with peer reviewed medical journals [25]. Furthermore, Wikipedia has the unmatched ability to cover current events and incorporate changes in near real time.Also, Wikipedia is free to download and hack for everyone. As all digital documents, it has structural elements, like lists and tables. Like encyclopedias, it also has a category system. Furthermore, it contains many infoboxes-structured schemas that communica...

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Section: Identifyingmentioning

confidence: 99%

“…9 Especially the notability test: https://en.wikipedia.org/wiki/Wikipedia:Notability. 10 http://wiki.freebase.com/wiki/WEX. is acknowledged.…”

Section: Freebasementioning

confidence: 99%

Section: Freebasementioning

confidence: 99%

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DBpedia Mashups

Héder¹,

Solt²

2013

Semantic Mashups

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“…They may create innovative new services and/or present data in new and unforeseen ways (Beemer and Gregg, 2009;Salminen, Kallio, and Mikkonen, 2011;Wakaruk, 2013). Value may be created by providing context and meaning that is relevant to the individual user (DiFranzo et al, 2011). At a technical level, a mashup is a "lightweight, Web-based, composite application[s], with no native data store or content repository" (Gartner, 2013).…”

Section: Literature Reviewmentioning

confidence: 99%

Value in the mash: exploring the benefits, barriers and enablers of open data apps

Cranefield¹,

Robertson²,

Oliver³

2020

Preprint

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The open government paradigm relies on the provision and reuse of open government data (OGD) to improve transparency and create new sources of value. This study aims to progress understanding of OGD beyond a theoretical commentary by exploring the perceived sources of value of mashups (online services that combine diverse OGD), and to examine issues that impact on, and facilitate, the delivery of this value from an 'insider' perspective. Based on open-ended interviews with 17 individuals actively involved in OGD application design, use, and advocacy in New Zealand (ranked fourth in the 2013 Global Open Data Barometer) nine key sources of value were identified: Ease of discovery, improved data quality, bringing knowledge into relevant contexts, economic benefits, social benefits, cost reduction and efficiencies, predictive value, transparency, and ability to explore and play. Twelve barriers to delivering this value were found, ranging from change-related issues to problems relating to sustainability. Six facilitators were identified as helping to overcome these barriers and realise the value of OGD.

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“…Essentially, these initiatives can serve to reduce information asymmetry between public agencies and their external stakeholders for the innovation of government services. Although datasets are in their raw form and may not have much value on their own, public agencies can leverage on businesses and citizens to contribute to the innovation of government services through the reorganizing, repackaging, and synthesizing information from various sources (DiFranzo et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Innovation in Government Services: The Case of Open Data

Zhou

Kankanhalli

2013

Grand Successes and Failures in IT. Public and Private Sectors

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Abstract.Governments are initiating open data initiatives as a new approach where external stakeholders can play an increased role in the innovation of government services. This is unlike previous approaches of e-government service innovation where services are solely initiated and developed by the agencies themselves. However, despite public agencies actively promoting the use of their data by organizing events such as challenge competitions, the response from external stakeholders to leverage government data for innovative activities has been lacking. This raises the question about the reasons inhibiting the interest to innovate using open data. Yet, the existing literature points to a lack of understanding about external stakeholders' willingness to innovate with the data provided. Motivated thus, this paper aims to identify the antecedents of the willingness of external stakeholders to innovate with open data. We propose the use of the case study methodology for this purpose.

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The Web is My Back-end: Creating Mashups with Linked Open Government Data

Cited by 18 publications

References 8 publications

DBpedia Mashups

DBpedia Mashups

Value in the mash: exploring the benefits, barriers and enablers of open data apps

Innovation in Government Services: The Case of Open Data

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