Enipedia:About

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[edit] About

Enipedia is an active exploration into the applications of wikis and the semantic web for energy and industry issues. Through this we seek to create a collaborative environment for discussion, while also providing the tools that allow for data from different sources to be connected, queried, and visualized from different perspectives.

More on the philosophy, ideas and principles behind Enipedia:

  • Chris Davis (2012), Making Sense of Open Data - From Raw Data to Actionable Insight. (PhD Thesis), Delft University of Technology.
    • Chapter 9 discusses in depth the initial development of Enipedia.
  • Chris Davis,Igor Nikolic and Gerard P. J. Dijkema (2010) , Industrial Ecology 2.0, Journal of Industrial Ecology, Volume 14, Issue 5, pages 707–726, October 2010 [1]
  • Alfredas Chmieliauskas, Emile J. L. Chappin, Chris Davis, Igor Nikolic and Gerard P. J. Dijkema (2012). New Methods for Analysis of Systems-of-Systems and Policy: The Power of Systems Theory,Crowd Sourcing and Data Management, System of Systems, Adrian V. Gheorghe (Ed.), ISBN: 978-953-51-0101-7, InTech, Available from: [2]

[edit] Maintainers

Enipedia has been started by the Energy and Industry Group, Department of Technology, Policy and Management at Delft University of Technology, the Netherlands. For more info please contact:

[edit] Licensing

All structured data available through SPARQL Endpoint is made available under the Open Database License. Any rights in individual contents of the database are licensed under the Database Contents License.

Content on individual pages are licensed under a Creative Commons Attribution Share-Alike 3.0 License

[edit] How to cite

If you use or refer to Enipedia, use Enipedia data or Enipedia query results, we ask that you cite as follows:

  • C.B. Davis, A. Chmieliauskas, G.P.J. Dijkema, I. Nikolic (2015), Enipedia, http://enipedia.tudelft.nl, Energy & Industry group, Faculty of Technology, Policy and Management, TU Delft, Delft, The Netherlands.

In wikimedia citation markup: {{cite web | first1 = C.B. | last1 = Davis | first2 = A. | last2 = Chmieliauskas | first3 = G.P.J. | last3 = Dijkema | first4 = I. | last4 = Nikolic | title = Enipedia | year = 2015 | publisher = Energy and Industry group, Faculty of Technology, Policy and Management, TU Delft | location = Delft, The Netherlands | url = http://enipedia.tudelft.nl | access-date = }}

[edit] Architecture

The picture below illustrates the way in which we have set up Enipedia. A detailed explaination is available in the Enipedia chapter of the PhD Thesis of Chris Davis. In general, we take existing open data sources, convert them into a data format (RDF) that makes them easier to query (via SPARQL queries). As an example of why this is important, the eGRID data published by the US EPA has extensive coverage of power plants in the US. The problem with it is that it is published as a series of Excel spreadsheets, one for each reporting year. If you want to find time series data about a particular plant, then you have to look through nine spreadsheets, 4000 rows, and about 150 columns to track down all of the data. We can find and display this information with a single query, given the unique identifier for the power plant. See Navajo Powerplant for an example of this in action.

We also use Enipedia as a repository of data for our various research efforts. In addition to hosting source data, we use various visualizations and queries to help people spot errors and get a better idea for what is actually contained in the data.

EnipediaSchematic.svg

A key tenet of Enipedia is that data displayed on the wiki is not trapped within the wiki, but people are free to extract the data via SPARQL queries, and build their own applications and tools with the data. In general any programming language that allows you to download data from a URL can be used to extract data from Enipedia.

Some of the tools that we have used to work with Enipedia data are the AgentSpring Agent Based Modeling framework (developed by Alfredas, among others), the R programming language (see the Google Earth Visualization and Enipedia Power Plant Dataset Reconciliation API), Matlab (used for load flow calculations of the electricity grid, based on data at Portal:OpenGridData), GAMS, and various web interfaces built using javascript (see Enipedia Maps and several here).

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