Protege4ClientServer

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Revision as of 13:40, January 13, 2013 by Tredmond (talk | contribs) (Client Installation)

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Introduction

These are some pages under development to document the Protege 4 Server. We are hoping to release an early alpha soon.

This server is in an early alpha stage and it is recommended that you backup critical files often.

What is it?

The Protege OWL Server provides a platform for collaborative editing and version control of a collection of ontologies. The Protege server tracks changes made to its ontologies, enforces an access control policy for its documents and checks for conflicts between its clients. When used with the Protege client, ontology editors can view and modify a shared ontology in parallel. If a editor chooses, the editor can watch changes made by other editors as they occur. To change an ontology, an editor first makes the changes in his local copy of the ontology. When he is happy with his changes, he can commit them making them available to other editors of the ontology. Alternatively, an editor making changes to his local copy can save his copy of the changes and commit them in a later session.

In addition, the Protege OWL Server can be used as something more like a simple version control system. We are developing a set of command line tools that will be able to use a Protege OWL Server to provide such traditional version control services as checkn, checkout, update, commit and history query commands. The Protege 4 client can be used in this manner as well: an ontology editor can choose not to turn on auto-update and make all his updates and commits manually.

Comparison with the Protege 3 Server

There are several differences between the Protege 3 Server and the Protege 4 Server:

The local copy.
In Protege 3, when a client connect to the server, any change made to the client is immediately reflected on the server. In Protege 4, in contrast, changes only get propagated to the Protege server when the user commits the change. This allows a user of a Protege client to consider his changes before sending the changes to the server. This is a significant enough concept that we describe it in more detail below.
Decoupled client-server.
In Protege 3 when the server goes down or the network is interrupted, the Protege 3 client either freezes or crashes. In contrast, in Protege 4, if the server stops or is inaccessible, the Protege client continues running normally. It is only when some server operation is attempted, such as an update or commit, that the user may become aware that there is a problem communicating with the server.
Commit granularity.
In Protege 3, changes are sent to the server as they are made. In Protege 4 a collection of changes are only committed when the user is ready the user is able to add a commit comment describing the nature of the changes.
Optional automatic update.
In Protege 3, a user sees edits from other users as they occur. In Protege 4, this is optional. This will allow, for instance, a user to start a reasoner and query the ontology state without worrying that the ontology will change as the query is in progress.

The Local Copy/Sandbox

With the Protege 4 client server, when a user checks an ontology out from the server, he gets a separate copy of the server ontology. The user can then modify this copy in any way that he likes and the changes will not go to the server until the user commits the changes.

In fact this local copy can be saved to disk and then even editted with a different editor than Protege before it is committed to the server. Specifically, a user can

  1. start protege and load an ontology from the server,
  2. save the ontology somewhere on the local disk,
  3. exit protege and edit the ontology with a text editor
  4. restart protege and open the ontology from disk
  5. commit the changes which will include the changes made with the text editor.

What happens is that when the file is saved, Protege also saves some files containing the server providing the ontology document, the location of the document on the server and the revision of the ontology document on the server. So if I save an ontology as Thesaurus-redmond.owl in the client.ontologies directory then Protege saves the following files:

  - client.ontologies
       o Thesaurus-redmond.owl
       - .owlserver
            o Thesaurus-redmond.owl.history
            o Thesaurus-redmond.owl.vontology

The Thesaurus-redmond.owl.vontology contains information that describes the relationship between the ontology in Thesaurus-redmond.owl and the document on the server. The Thesaurus-redmond.owl.history contains a local cache of the history of changes made to the ontology document on the server. It is not required - if it is deleted it will be rebuilt - but it provides significant performance advantages for the client especially in the case where either the network is slow or the ontology is large.

Videos

Here are some videos that I am making to demonstrate server features:

  • Protege OWL Client-Server Basics. This video shows how to
    • access a server,
    • upload an ontology,
    • follow changes made by another user with auto-update,
    • have an extended session with the server spanning multiple Protege sessions.
  • Accessing the Protege OWL Server from the command line. This video shows how to use the command line client to
    • browse the Protege OWL server directories and ontologies with the pos-list command.
    • upload ontologies to the Protege OWL server (pos-upload).
    • checkout ontologies from the Protege OWL server (pos-checkout).
    • commit changes back to the Protege OWL server (pos-commit).
    • support the use of ontology editing tools other than Protege to edit a shared ontology from the Protege OWL server.

Large ontologies on a slow network

When a large ontology is being uploaded or downloaded from a server on a slow network, it can take a while to transfer all the necessary data. Unfortunately we have not yet determined how to best monitor and report the progress of this operation so the user doing the upload/download will have little indication of the progress. The good news here is that the user only needs to experience this once for the initial upload of the ontology to the server and once for his initial download of the ontology. In addition, since the upload of an ontology is a one time thing, it is very likely that it can be performed on a faster network.

The issue concerns the change history stored on the server representing the set of changes between revision 0 and revision 1. These changes consist of the full set of changes needed to create the initial version of the ontology. Thus for instance, if the NCI Thesaurus is uploaded onto the server, the set of changes to go from revision 0 (the empty ontology) to revision 1 (the initial version of the Thesaurus on the server) will contain over 1.2 million individual changes. This change set is stored in a 300 MB file which then needs to be transfered to any client that wants a copy of the ontology. (In point of fact, this change set gets compressed before it hits the network so the actual data copied across the wire is only about 44 MB.)

Once the ontology is downloaded to the client, the client can save the ontology with the change history to disk for later reference. When the ontology is reloaded from the disk, the client will already have a copy of the 1.2 million changes from revision 0 to revision 1 and will not need to download it again from the server.

Installation details

Prerequisites

For the client installation, the only prerequisite is that you successfully installed Protege. For the server installation you must have installed


Client Installation

When the Protege OWL server is released, the latest Protege distribution will include the latest version of the plugins needed to access the Protege OWL Server. In the mean time, to allow Protege to access the server you need to download the following files and copy them to the Protege plugins directory:

  1. the server library,
  2. the Protege client plugin and
  3. [1].

Server Installation

This page describes how to install the Protege OWL server. Eventually we will have a java program that provides an installation wizard but for now you will need to run a script that will build and install the server onto your system. To run this script, you will need to have the java development kit (jdk) version 6 or 7 from oracle and the ant (ant.apache.org) program.

When we are ready to release the server we will provide a zip file that you will unzip. You will then run ant in the extracted directory. Until the release, or to get the bleeding edge version, you can checkout the directory from the subversion sources. After obtaining these files, the first thing that you need to do is to set a few configuration parameters. To do this you create a local.properties file and a typical installation will contain the following lines:

memory.mb=2700
hostname=wormhole.stanford.edu
sandbox.user=protege

This local.properties file defines the three mandatory parameters which are:

The server memory footprint
In this case we are giving server 2.7G of memory. The more memory the server has the better it will handle users accessing multiple large ontologies at the same time. The downside is that as the server gets more memory, it potentially means that other processes on that same machine will have less memory available. Memory is always specified in megabytes.
The hostname.
This is a name that other hosts can use to look up the server machine.
The sandbox user.
This is a very important parameter which relates to the security of the server system. It should correspond to a login account with relatively few access rights and no access to any critical files. When the Protege OWL Server is started it will run under this id. By running the Protege OWL Server under a restricted id, we guarantee that even if a hacker breaks into the Java Virtual Machine or the Protege OWL Server code, the hacker will still have to contend with the operating system security checks before he can do any real harm. At this time we know of no security loopholes in the Protege OWL Server (this statement depends on the threat model of course) but we have great respect for the abilities of the opposition.

Unfortunately at this time, while still mandatory, the sandbox user parameter does not work on Windows machines. This means that a windows machine hosting the Protege OWL server should either be running on a machine that does not have access to any critical data or only be exposed (even as a Protege server) to a protected network free from hostile forces. Users who consider such a configuration acceptable can set the sandbox user parameter to their own login. Alternatively, the manual method of starting the server on windows (described below) does take the sandbox user information into account.

When the local.properties file is put in the right place the directory structure should look as follows:

ServerInstallLocalProperties.png

Now there are two installation choices:

ant install
This will install the Protege OWL server but not start it. This is useful in case the user wants to use some of the command line tools.
ant deploy
This will install and start the Protege OWL server. The Protege OWL server will also restart on reboot.

A detailed description of how the installed protege server is configured on your system can be found here.

Windows Considerations

The windows operating system includes a Services.exe program which allows the user to see if the Protege OWL server has been installed.

When the Windows Service Fails

The windows platform has been the most difficult platform to work with. We have developed an alternative approach for running the server on a Windows platform in case the "ant deploy" target does not work. If the "ant install" target succeeds, it will install a .bat script in tne following directory:

        C:\Program Files\Protege OWL Server\bin\run-protege-owl-server.bat.

Running this script should get the server running. An advantage of this script is that it will run the server with the user id specified in the local.properties file. This means that the server, when run this way is much more secure. On the other hand, the server will have to be started manually on each reboot.