Web systems supporting collaborative knowledge engineering have attracted much attention recently. By using social software techniques and attractive yet simple user interface, the motivation of users increases and the process can be significantly improved. The willingness of community to invest their time as well as mutual encouragement can be achieved when users are convinced that their contribution is important and useful. We propose a social platform called Social Threat Monitor (STM) aimed at improving safety of local communities in urban environment. The main assumption of the system is the collaboration of users to build and maintain a knowledge base about threats in their neighborhood. Knowledge gathered in the system can be used by the citizens as well as local authorities and police. The system supports collaborative knowledge engineering and management using semantic methods and a GIS component. Web-based information systems are used for gathering, storing and processing diversified information for various purposes. In Web 2.0. era, users can actively participate in building such systems. Projects such as Wikipedia have shown that collaborative knowledge acquisition (KA) and management (KM) can be successful if people see the importance of the project and the KA process is relatively easy. Mechanisms such as voting, commenting and discussions increase the possibility of building reliable and useful knowledge bases. Semantic technologies enable adding metadata to regular content and facilitate automatic knowledge extraction and processing [5]. In this paper, we present a Web-based system for collaborative knowledge acquisition and management. It is a thematic portal which aims to gather knowledge about threats of various kinds in local environment. This information may be used by citizens as warnings and by local police as notifications. The system is being developed within the INDECT project: ”Intelligent information system supporting observation, searching and detection for security of citizens in urban environment” 2. The original contribution of this paper consists in presenting the collaborative knowledge engineering (KE) possibilities including knowledge exchange with external sources with use of a dedicated Application Programming Interface (API). The paper is organized as follows: In Sect. 2 the motivation for this research is given. Sect. 3 provides an overview of the system functionality, user interface and implementation. Mechanisms applied to facilitate KE with the system are discussed in Sect. 4. The API of the system is presented in Sect. 5. Related work is outlined in Sect. 6, followed by a summary in Sect. 7 and future work in Sect. 8.
Przemysław Cie˛z˙kowski1
The aim of the Task 4.6. of the INDECT project is to develop a
system for distributed knowledge acquisition and management with
GIS [
A social software platform facilitate collaborative knowledge engineering in an unintrusive way. Pieces of information shared by different persons are insignificant alone, but connected make a rich diversified picture. In popular social software platforms, people build personal knowledge bases half-consciously by acknowledging things and events shared by friends or ”followed” people. We want to leverage this dynamics and develop a system that would provide useful information while seamlessly integrating with daily life.
Within the INDECT project, several prototypes have been
developed [
The main goal of the system is to serve as a distributed knowledge
acquisition system for data, information and knowledge provided by
citizens, as well as to enable knowledge management and exchange.
Principles and a conceptual model of the system have been described
in [
To enhance the automated knowledge processing of the system,
semantic technologies for GIS were analyzed and discussed in [
The following groups of users are defined in the system: Guest is a user with the anonymous web account. He is able to use basic features of the application. In order to gain more privileges, a guest need to register and log in into the system.
Member is a user with registered account in the system. With this account user can add threats, manage his own threats, comment and vote threats of other users and edit his profile.
Services User is a special account with features helping threats monitoring.
Moderator is a user with full access to threat records, able to ban users.
Administrator is a user with full access to the application.
Main part of application is the map (see Fig. 2) that covers all space user have and resize immediately when needed. The interactive map implemented with use of AJAX technology – Asynchronous JavaScript and XML – provides easy and quick reloading as few times as possible. Because the URL does not change when only partial reloading is done, the identification of the state of the map (visible location or threat) is done with hashing (every time map position is changed or other action is performed, the hash changes).
The map have two editing modes: for browsing and adding threats. Mouse events are treated adequately to the mode. The map locates the user’s position, but it can be moved (with mouse or keyboard) and zoomed (with mouse scroll or scroll on the left on the map).
Users browsing the system can immediately view short threat details (votes, one picture if available, number of comments and quick edit link). Voting is available only for registered users, but anonymous are able to see how many votes the threat got. Full gallery, list of tags and all comments are available on new page for each threat.
Top menu toolbar allows the user to toggle options of the login panel. If a user is already logged in, the login link is replaced with his account name and five options: 1) Profile (where the user can change account settings), 2) Logout, 3) Threats (where the user can list all threats, last added threats, top reliability threats and most dangerous threats), 4) Language (which allows user to change site language) and 5) About Indect – which is a link to the INDECT project page3.
Most of the functionality is available form the left menu: (1) adding threats, including selecting area for a new threat, (2) browsing map by location, and (3) searching for threats using various filters. Each section of the left menu can be shown or hide.
The system has been implemented using widely-accepted,
costfree Web technologies: HTML, CSS, JavaScript, jQuery, Google
Maps API version 3 and the Django framework (for details see [
Semantic annotations for the threats The basic piece of knowledge in the system represents a single threat. Each threat may be described using a set of attributes, such as: geometry – the information about the shape and the location of the danger, name, category – each danger is assigned to one category, comments – all logged in users may post their comment on the danger info, severity – a number telling how severe the danger is, reliability – a number telling to what degree the information is reliable, photo gallery – a relation to an object being a set of pictures illustrating the threat, date added – when the information has been added into the system, modification date – when the information has been last modified, and tags – in order to search for interesting information.
Tags Tags are non-hierarchical keyword or terms that describe an object, specifically a threat. One threat can be assigned several tags. They help searching and categorizing threats. Threats are tagged while adding by user. Well tagged threats are more reliable for other users and usually get more votes.
Categories Categories constitute a hierarchical way of describing threats. One threat has one category, but categories can contain many threats. Categories are organized into a tree structure. The root of the categories is not visible on site. There is no children limit for 3 http://www.indect-project.eu/ categories. As relational databases are not designed for storing hierarchical data, retrieving category and its all parents with use of procedural SQL is complicated. Also, fetching the whole tree requires additional operations after database query execution. To solve this problems in STM, Nested Set Model was implemented through django-mptt module. It provides an efficient way to retrieve categories from database. Modifying the tree is more complicated, thus slower, but it is only possible for admin user and rarely executed. User Groups Except for categories for threats, the users can also be grouped. Groups allows to publish threats for specified users. When adding a threat, a user (who is at least in Services group) can decide if the threat will be public or visible only for selected groups. This solution allows special groups have their own threats that will never be published for all system users.
An exemplary use-case has been presented in [
Parts or the system data can be imported and exported to JSON, XML and YAML formats. In order to enable export of knowledge for further custom processing and import from another knowledge base, a simple Application Programming Interface (API) has been developed. Standarized knowledge representation using attribute-value pairs describing threats allows for using the system knowledge in various semantic applications (where triples of the form: object-attribute-value or subject-predicate-object are used). External systems can communicate with STM and use it as a web service. The API is available over HTTP protocol: http://application.url/api/method_name/. API access and exchange format Part of the functionality of the Social Threat Monitor is available for external applications without authorization. For instance, by preparing an appropriate request conforming to the system API one can get all the threats defined for a given location or filter. In order to use the whole functionality, including adding threats to the system, the application must be authorized. Its user must be defined in the STM and assigned to the API group.
The API uses POST requests and HTTP cookies. All responses are in JSON format. Each successful request returns HTTP 200 header and the 400 header is returned, if a method does not exist. Moreover, if an anonymous user wants to access a method that requires authorization, a HTTP 200 header with appropriate content is returned. Methods The system API provides three basic methods: 1) logging in, 2) adding a new threat, and 3) retrieving existing threats. Each method accepts arguments that must be sent using POST or COOKIES. Below, the methods with required (marked with an asterisk "*") and optional parameters are presented:
Parameters:
– *username:string – user’s name.
Demo implementation An example system using API has been developed and is available for testing at: http://home.agh. edu.pl/kk/stm. It has been implemented in PHP and uses cURL library. The library allows for connecting to and communicating with various types of servers and different protocols. An example screenshot showing STM response is presented in Figure 3.
Crime Mapping systems were originally a class of systems that map,
visualize and analyze crime incident patterns using Geographic
Information Systems (GIS). However, the name has been later extended
to incorporate all applications that aid in improving the public safety.
This include natural disasters monitoring systems, often designed for
specific regions, which scope of functionalities is limited to the
specific types of disasters that are most common and dangerous in those
regions, systems monitoring threats on the roads and crime
monitoring systems. A detailed survey of existing crime mapping systems is
given in [
One of the tasks within the INDECT Project is the development of
a Web-based system for knowledge acquisition and management.
Once the main assumptions and requirements were defined, the
development has been done iteratively. Semantic description,
categories and tags constitute the basis for further development of
intelligent information processing and knowledge management. System
API allows for easy integration with other applications and facilitate
knowledge exchange and integration from various sources.
The approach to semantics representation now used in the STM can
be extended. Currently, only basic semantics is represented with use
of tags and categories. They are closer to the model of folksonomies,
where users provide custom tags that can be a foundation for a
simple hierarchy of categories. A possible direction of future work is to
refactor the hierarchy currently existing in STM with the use of a
selected OWL 2.0 profile. All of the important relations should be
identified and formalized. This will allow for having a complete
formal model of the threat ontology. It is also planned to work on the
rule-based engine [
Although the system works in a regular Web browser and thus can be accessed from any mobile device that has a browser, further adaptation for smartphones is planned. In particular, the system should use the GPS embedded in mobile devices to facilitate adding threats.
The research presented in this paper is carried out within the EU FP7 INDECT Project: ”Intelligent information system supporting observation, searching and detection for security of citizens in urban environment” (http://indect-project.eu).