I'm evaluating 2sxc as a possible platform for implementing a knowledge management solution but we're in a bit of a rush. Our alternative is DNN Live Articles.
So far I really like the look of 2sxc, but I have questions regarding our possible use of it.
The main questions I have are around hierarchical lists like nested Categories and permissions.
From the look of some of the apps I've installed like FAQs with Categories but I can't find anything yet where they are nested. I tried creating a Content Type and adding fields where the first is the Category Name and the second is Parent Category. I created a new Content Type Field with a Data Type of Entity, but the only option for Input Type is default and Content Block Items. It works but when you create a new category the content that comes up in the Parent Category field covers just about everything - not sure I understand the concept behind this.
Then the second issue is permissions. Does this system somehow incorporate permissions because we'd like to lock down knowledge articles by category, but I haven't seen any implementations that showcase how one would do this.
Regarding #1 I don't understand your question, sorry :)
Regarding #2: there is no rule-based security, so you can't say "items with category X may be edited, but category Y may not"
BUT: you can easily implement this in your UI, if your main concern is user guidance and not "bad people with very good IT skills"
I know that to search for a page id of a wikipedia with known title, i can do:
https://en.wikipedia.org/w/api.php?action=query&titles=7_Studios
However, in this case, 7_Studios is a french wikipedia article, so the above link would not work. Instead I need to try
https://fr.wikipedia.org/w/api.php?action=query&titles=7_Studios
My question is, if I do not know what language the article is about but only the title itself, how can it make sure i can find it using the api?
As Bergi mentioned, you can use Wikidata for this: it contains the database of interwiki links, so it's possible some article title won't be there, but most should.
To do this, you can use the wbgetentities module: you specify the title to search for and a list of wikis to search. For example:
https://www.wikidata.org/w/api.php?action=wbgetentities&titles=7_Studios&sites=enwiki|frwiki|nlwiki|dewiki
You can specify up to 50 wikis in one query. Currently, there are around 300 Wikipedias, so if you really need to query all of them, you may need up to 6 requests for each title.
I was searching the net for something like a wiki database, just like wikipedia but instead stores structured content, editable by users. What I was looking for was an online database accessible by everyone where people can design the schema and data with proper versioning of both schema and data. I couldn't find any such site. I am not sure if it is my search skills or if there really is no wiki database as of now. Does anyone out there know anything like this?
I think there is a great potential for something like this. A possible example will be a website with a GUI for querying a MySQL DB where any website visitor can create DB objects and populate data.
UPDATE: I had registered the domain wikidatabase.org to get started on a tool but I didn't find enough time yet. If anyone is interested in spending some time and coding on this, please let me know at wikidatabase.org
It's not quite what you're looking for, but Semantic Mediawiki adds database-like features to MediaWiki:
http://semantic-mediawiki.org/wiki/Semantic_MediaWiki
It's still fundamentally a Wiki, but you can add semantic tags to pages ([[foo::bar]] [[baz::1000]]) and then do database-type queries across them: SELECT baz FROM pages WHERE foo=bar would be {{#ask: [[foo::bar]] | ?baz}}. There is even an embryonic SPARQL implementation for pseudo-SQL queries.
OK this question is old, but Google led me here, so for anyone else out there looking for a wiki for structured data: Take a look at Foswiki.
This might be like what you're looking for: dbpedia.org. They're working on extracting data from Wikipedia, and encoding it in a structured format using RDF, so that it can be queried using SPARQL.
Linkeddata.org has a big list of RDF data sets.
Do you mean something like http://www.freebase.com?
You should check out https://www.wikidata.org/wiki/Wikidata:Main_Page which is a bit different but still may be of interest.
Something that might come close to your requirements is Google Docs.
What's offered is document editing roughly similar to MS Word, and spreadsheets roughly similar to Excel. I'm thinking of the latter, of course.
In Google Docs, You can create spreadsheets for free; being spreadsheets, they naturally have a row-and-column structure similar to a database, and which you can define flexibly. You can also share these sheets with other people. This seems to be a by-invite-only process rather than open-to-all, but there may be other possibilities I'm not aware of, or that level of sharing might be enough for you in any case.
mindtouch should be able to do it. It's rather easy to get data in / out. (for example: it's trivial to aggregate all the IP's for servers into one table).
I pretty much use it as a DB in the wiki itself (pages have tables, key/value..inheritance, templates, etc...) but you can also interface with the API, write dekiscript, grab the XML...
I like this idea. I have heard of some sites that are trying to pull together large datasets for various things for open consumption, but none that would allow a wiki feel.
You could start with something as simple as an installation of phpMyAdmin with a known password that would allow people to log in, create a database, edit data and query from any other site on the web.
It might suffer from more accuracy problems than wikipedia though.
OpenRecord, development of which seems to have halted in 2008, seems to approach this. It is a structured wiki in which pages are views on the data. Unlike RDBMSes it is loosely typed - the system tries to make a best guess about what data you entered, but defaults to text when it cannot guess. Schemas appear to have been implied.
http://openrecord.org
An example of the typing that is given is that of a date. If you enter '2008' in a record, the system interprets this as a date. If you enter 'unknown' however, the system allows that as well.
Perhaps you might be interested in Couch DB:
Apache CouchDB is a document-oriented
database that can be queried and
indexed in a MapReduce fashion using
JavaScript. CouchDB also offers
incremental replication with
bi-directional conflict detection and
resolution.
I'm working on an Open Source PHP / Symfony / PostgreSQL app that does this.
It allows multiple projects, each project can have multiple directories, each directory has a defined field structure. Admins set all this up.
Then members of the public can suggest new records, edit or report existing ones. All this is moderated and versioned.
It's early days yet but it basically works and is already in real world use in several projects.
Future plans already in progress include tools to help keep the data up to date, better searching/querying and field types that allow translations of content between languages.
There is more at http://www.directoki.org/
I'm surprised that nobody has mentioned Wikibase yet, which is the software that powers Wikidata.
A bit of an SEO question here.
I've got a site with a ton of pages, of content. I know lots of the content is the same on each page.
I thought that Search Engines keyed off of the differences in page content so that they could promote the correct data, but when I look at the summary in google and bing, the summary shows my 'feedback' block (which is where I just ask for feedback).
Yahoo (and the summary in Facebook) shows my search options menu.
These aren't really things that are going to make a person want to click on the page.
So I'm wondering what the best way is to either hide this content from search engines, or improve the visibility of the other content that should get indexed.
The page structure is pretty consistent, so I thought it would have been easy for the search robots to pick this stuff out, but apparently not.
You may want to try using a meta tag like this.
< META NAME="description" CONTENT="Here is a short summary of the page" >
Search engines also prefer title and header tags over regular text.
Meta is the best way to do that.
However,Beware that your structure of page is a also important, which means search engines prefer to use metal tag, but they also weigh the structures, keywords, headers things like that.
I encountered such trouble couple of months ago. I found Google showed price and download rather than meta description. I solved that by reorganize meta description(more accurate and shorter,177 characters)eliminate tags from price and download tags. And made some slight adjustments to the structure. Now the Google summary is what I want.
Hope this helps you!
Here's the basic scenario - I have a corpus of say 100,000 newspaper-like articles. Minimally they will all have a well-defined title, and some amount of body content.
What I want to do is find runs of text in articles that ought to link to other articles.
So, if article Foo has a run of text like "Students in 8th grade are being encouraged to read works by John-Paul Sartre" and article Bar is titled (and about) "The important works of John-Paul Sartre", I'd like to automagically create that HTML link from Foo to Bar within the text of Foo.
You should ask yourself something before adding the links. What benefit for users do you want to achieve by doing this? You probably want to increase the navigability of your site. Maybe it is better to create an easier way to add links to older articles in form used to submit new ones. Maybe it is possible to add a "one click search for selected text" feature. Maybe you can add a wiki-like functionality that lets users propose link for selected text. You probably want to add links to related articles (generated through tagging system or text mining) below the articles.
Some potential problems with fully automated link adder:
You may need to implement a good word sense disambiguation algorithm to avoid confusing or even irritating the user by placing bad automatic links with regex (or simple substring matching).
As the number of articles is large you do not want to generate the html for extra links on every request, cache it instead.
You need to make a decision on duplicate titles or titles that contain other title as substring (either take longest title or link to most recent article or prefer article from same category).
TLDR version: find alternative solutions that provide desired functionality to the users.
What you are looking for are text mining tools. You can find more info and links at http://en.wikipedia.org/wiki/Text_mining. You might also want to check out Lucene and its ports at http://lucene.apache.org. Using these tools, the basic idea would be to find a set of similar articles based on the article (or title) in question. You could search various properties of the article including titles and content or both. A tagging system a la Delicious (or Stackoverflow) might also be helpful. Rather than pre-creating the links between articles, you'd present the relevant articles in an interface much like the Related questions interface on the right-hand side of this page.
If you wanted to find and link specific text in each article, I think you'd need to do some preprocessing to select pertinent phrases to key on. Even then I think it would be very hard not to miss things due to punctuation/misspellings or to not include irrelevant links for the same reasons.