http://blogs.worldbank.org/dmblog/open-vs-public-data-the-big-difference The major difference between open and public data is [that with open data] you have the ability to re-use it. Data in document format is effectively useless. By making [data] open...people can analyze, compare, and benchmark it, and find patterns that you did not realize. Doug Hadden, Vice President/Products at the financial management software company FreeBalance, explained: "Open" Vs. "Public" Data - The Big Difference Open Data vs Public Data vs Proprietary Data When talking about crime data, is there a distinction between open, public, and proprietary crime data. http://blog.spotcrime.com/2014/04/open-data-vs-public-data-vs-proprietary.html Open data is data that’s available in a machine readable format without restrictions on the ability to use, consume, or share the information Open crime data is the best option for police agencies. The easier the information is to obtain, the easier it is to get more eyes on the information which, we believe, leads to really cool ways to view the data and, most importantly, leads to safer and more informed neighborhoods. What is public data? Public data is data that’s available to the public to collect or look at, but it’s not easily redistributed (or machine readable) and sometimes not easily obtained. It might require an open records request or FOIA in order to obtain the information if it’s not already available on a website. These requests can sometimes be very finicky and can take days to months to garner a response. Public data is not the best option, however it’s a start! Moving from public data to open data would be a pivotal next step for an agency. And, in the case with agencies requiring a lengthy FOIA process for the information, open data has numerous cost savings and benefits for the department. Proprietary data is data that is claimed ownership by a specific entity or company. We don’t believe there is such a thing as proprietary crime data because crime data is public and it’s created and maintained by public tax dollars. However, we’ve found that when a police agency partners with a third party vendor to display public information, the vendor will place restrictions or a terms of use on the data controlling how the public and press can use and share the information. Data Sharing is Not Open Data https://theodi.org/blog/data-sharing-is-not-open-data Data sharing is providing restricted data to restricted organisations or individuals. Open data is providing unrestricted data to everyone. By definition, open data must be available to all without restrictions on what they do with it. And the corollary of that is there cannot be legal restrictions on making that data available. When data sharing arrangements are put in place, we recommend using open data to minimise the number of restricted data releases that are made, to make the process transparent, and to ensure that everyone benefits from it. Namely: Release open data. Provide aggregate and anonymised information that satisfies the majority of the demands that organisations have for data. Document the data and the process to access it. It should be clear what the data holds, and the robust process that those who get hold of it have to go through to be granted access. See the information on the National Pupil Database as a good example. Publish all requests for access as open data. The public has a right to know who is asking for, and being granted access, to their data and for what purpose. When this is transparent, it reassures the public that there is a robust process in place for granting access, and it discourages organisations for requesting data that they don’t have a good reason for needing. Require the publication of the results of data analysis as open data. The public should benefit from the results of analyses of public data – there should be a requirement for publication of anonymised derived datasets that result from priviledged access to the data. Monitor repeated requests. When the same data is requested repeatedly, including by different organisations, this is a signal that the analysis should be carried out by the organisation that holds the data and the result then published as open data for all to benefit from. “While big data is defined by its size, open data is defined by its use,” notes Joel Gurin in a piece for the Public Leaders Network. https://www.linkedin.com/pulse/big-data-vs-open-wael-youssef Big Data Vs. Open Data https://www.linkedin.com/topic/open-data The Public Data Corporation Vs. Good Governance https://countculture.wordpress.com/2011/10/10/the-public-data-corporation-vs-good-governance/ openlylocal.com retired so they could work on opencorporates passed baton to Local Web List http://localweblist.net/ http://localweblist.net/about/ https://github.com/adrianshort/talhyperlocaltheme https://code.google.com/archive/p/planningalerts/ planningalerts PlanningAlerts.com + screen scrapers for local councils PlanningAlerts.com is a free service that searches as many local authority planning websites as it can find and emails people details of planning applications near them. The aim of this is to enable shared scrutiny of what is being built (and knocked down) in peoples communities. Search Google Code Archive for "Civic Hacking" Labels https://code.google.com/archive/search?q=domain:code.google.com%20label:civichacking Search Google Code Archive for "Open Data" Labels https://code.google.com/archive/search?q=domain:code.google.com%20label:open%20data spotcrime FOIA response by BAIR analytics https://spotcrimecrimereports.files.wordpress.com/2016/02/253282959-letter-from-bair-analytics-to-spotcrime.pdf In this PDF "Open Source vs. Open Data" http://www.data-publica.com/content/wp-content/uploads/2012/05/open-source-vs.-open-data-9052012.pdf Public vs. private SECTION Public vs. private Open source has been traditionally orthogonal to the public vs. private distinction: it can apply to software produced by private or by public parties. Initially, the public sector has embraced it more readily than the private sector, but it also widely adopted by private players now5 . Open source proponents push for a systematic use of open source for all types of programs, public or private. Open data is currently pushed mainly for public data, and associated to PSI (Public Sector Information). There are good reasons to extend the idea of open data to the private sector and many open source advocates push for this. But, to my knowledge, no one is advocating the idea that all private data should be made public. Open data from private corporation is unusual at this stage, but you can start hearing it here and there. Extending the notion of open data to the private sector makes a lot of sense in a number of situations. But clearly the motivation for the private sector is going to be different : transparency is an image issue, and open data in the private sector wil The New Ambiguity of 'Open Government' Harlan Yu, David G. Robinson http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2012489 What "Open Data" Means-And What It Doesn't https://opensource.com/government/10/12/what-%22open-data%22-means-%E2%80%93-and-what-it-doesn%E2%80%99t Simply put, all open data is publicly available. But not all public data is open. Open data means that whatever data is released is done so in a specific way to allow the public to access it without having to pay fees or be unfairly restricted in its use. In other words, you shouldn't have to buy a particular vendor's product in order to be able to open, use, or repurpose the data. You, as a taxpayer, have already paid for the collection of the data. You shouldn't have to pay an additional fee to open it. Whether data should be made publicly available is where privacy concerns come into play. Once it has been determined that government data should be made public, then it should be done so in an open format. Defending Open Standards http://fsfe.org/activities/os/bsa-letter-analysis.en.html The Businesses of Open Data and Open Source: Some Key Similarities and Differences http://timreview.ca/article/757 2014-01 Lindman, Juho and Nyman, Linus "It's difficult to imagine the power that you're going to have when so many different sorts of data are available." Tim Berners-Lee Inventor of the World Wide Web Data has multiple meanings, including any end-product of measurement, but in this investigation, we use a slightly more technical definition of data: data refers to stored symbols. Data is considered a resource - raw material for the application. Open data means data that is technically and legally made available for reuse and republication. The underlying idea is that the increased transparency will help to create trust in users and developers, as well as offer a way to create new services based on the collected data. In many cases, the data is collected by government entities for various purposes and thus additional economic value would be created when the published data is put to use. However, open data includes open government-collected data as well as data released by private actors. Significant Difference Between Open Data and Open Source: 1) data versus application. although reliant on each other for their significance, are different in both essence and purpose. DotGob Fail http://web.archive.org/web/20150311213814/http://fedstats.sites.usa.gov/ http://www.kdnuggets.com/2016/02/top-10-data-visualization-github.html http://www.kdnuggets.com/2016/02/top-10-data-visualization-github.html Licensing of Open Data vs Open Source

 

Open Source (Application)

Open Data (Data)

Copyright

Applies to all source code

May apply

Licensing

Licenses must comply with the Open Source Definition

Relevant if protected by copyright. Possible licensing options include the Wikimedia Commons and the Creative Commons

Original publisher

Several versions (distributions) of application and forking are possible

Data often collected, maintained, and controlled by data publisher

Contracts

Normally not required; the license agreement defines the rights of the developers and users

Data publisher may have an incentive to monitor data use or to create feedback loops to reusers of their data
Table 1. Licensing of open data versus open source Table 2. Examples of Key Values Sources in Open Source Versus Open Data

 

Actor

Economic value

Other value

Open Source

Companies

Dual licensing, support and services

Product innovation, platform innovation

Customers

Cost savings

Evade vendor lock-in

 

Actor

Economic value

Other value

Open Data

Data owner

Sales of premium access

Public service, receive additional developmental resources

3rd party

Sell applications

Increased transparency, novel services

Figure 1. Comparing actors and activities of an open data versus open source project

In an open source project, both a corporate community and an open source community can participate in the software development. When data is being developed for release, data consultants as well as those who clean data participate to the process. Output of the processes are released as open source programs and as published open data. As shown in Figure 1, the main difference concerning the processes is that the open source process is more open than the open data process. The developers are able to participate in open source software development with varying motivations. For community driven projects in particular, motivations commonly are not financial. In open data, the data publisher is usually expected to carry costs related to releasing the data, such as the costs of collection, aggregation, and anonymization. If these services are outsourced, there is new business opportunity for companies that provide them. The output is also different: in open data, the data ultimately remains the same through the process, whereas the open source development process aims to change the software. The software is an end in itself, whereas the released open dataset is just the first step in providing the service to the customer.

Proponents of both phenomena promote the openness of the output, which offers transparency but also changes the competition dynamic. The open source alternative hampers traditional software subscription sales. Open datasets can be easily copied, but the original data collector still has a prominent role in the maintenance of the said dataset: a copied dataset, if not maintained properly, may soon become obsolete.

">The Businesses of Open Data and Open Source: Some Key Similarities and Differences, http://timreview.ca/article/757