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1 Technology Enhanced Learning Living Lab for Manufacturing D3.1 Distributed Learning Repositories Access Methods Issue 1 M12 issue Document Owner: Contributors: Fabio Cattaneo, Maurizio Megliola et al. (PIKS) Michele Sesana (TXT) Fridolin Wild, Peter Scott (OU) Erik Isaksson, Ambjorn Naeve (KTH) Tobias Maschler (DITF) TELL ME Consortium Dissemination: Public 1/139

2 Dissemination: Public Contributing to: WP3 Date: 31/10/2013 (Due Date) Revision: 1.1 TELL ME Consortium Dissemination: Public 2/139

3 VERSION HISTORY DATE NOT AND COMMENTS /10/2013 (PIKS) TOC AND DRAFT BASED ON WD /10/2013 (OU) CONTRIBUTION TO SOCIAL LEARNING MEDIA CLOUD, (PIKS) UPDATE OF DATA MODELS, EXAMPL OF SERVIC INPUT/OUTPUT, (KTH) OPENAPP ANNEX /10/2013 (TXT) GENERAL COMMENTS /10/2013 (PIKS) TAXONOMI ANNEX AND CONSOLIDATED VERSION /10/2013 (AARBA) PEER REVIEW /10/2013 (DITF) UPDATE CONTRIBUTION TO DOMAIN ONTOLOGY (TXT) UPDATE CONTRIBUTION TO LEARNINGCONTENT DB /09/2013 (PIKS) FINAL VERSION FOR FINAL CHECK /10/2013 (PIKS) FINAL VERSION DELIVERABLE PEER REVIEW SUMMARY ID 1 2 Comments I do not see added value in this history of database. Please, consider to review or to wrap it up In the Tab UserDetails and the SkillList there no reference to the user training or working performance. Addressed () Answered (A) TELL ME Consortium Dissemination: Public 3/139

4 DELIVERABLE ACRONYMS Acronym Full Name AR LA LC LCX LCO LN LP UI Augmented Reality Learning Activity Learning Challenge Learning Context Learning COntents Learning Need Learning Path User Interface TELL ME Consortium Dissemination: Public 4/139

5 TABLE OF CONTENTS EXECUTIVE SUMMARY INTRODUCTION INTRODUCTION APPLICABLE DOCUMENTS POSITIONING OF WP3 IN TELL ME INTRODUCTION OF WP3 COMPONENTS OVERALL ARCHITECTURE AND WP WP3 COMPONENTS REPOSITORI DATA ACCS LAYER SOCIAL LEARNING MEDIA CLOUD EXISTING DISTRIBUTED REPOSITORI AND LEARNING CONTENTS INTRODUCTION AERONAUTICS TEXTILE FURNITURE TELL ME REPOSITORI SPECIFICATIONS INTRODUCTION USER PROFILING AND EXPERIENCE Data Model Services MULTIMEDIA CONTENTS Data Model Services Content Administration LEARNING CONTENTS Overall Data Model Purpose and Functionalities Architecture Technical Information Services Learning Contents Management DOMAIN ONTOLOGI Taxonomies Data Model Services Administration SOCIAL, LIVING LAB AND COMMUNITI Data Model Services Connection with the other TELL ME repositories LEARNING PATHS/ACTIVITI Data Model TELL ME Consortium Dissemination: Public 5/139

6 4.7.2 Services CONCLUSIONS AND FUTURE PLANS ANNEX TAXONOMI Keyword taxonomy for Agusta Westland Keyword taxonomy for AIDIMA Keyword taxonomy for PROFITEX Keyword taxonomy for File Types OPENAPP DBMS TECHNOLOGY OVERVIEW FURNITURE DOMAIN - EXISTING LEARNING CONTENTS TELL ME Consortium Dissemination: Public 6/139

7 List of Figures Figure 1 - PERT diagram of the TELL ME project Figure 2 - First version of the TELL ME architecture Figure 3 - Basic architecture of the social media learning cloud Figure 4 - Screenshot the folder structure in Lotus Notes Figure 5 - Screenshot the folder structure in the Web Browser Figure 6 - Screenshot of a typical processing description, here about how to mark errors in the inspection of ready-made fabrics Figure 7 - User Profile and Experience Data Model Figure 8 - User Authentication with privacy protection Figure 9 - Multimedia Repository Data Model Figure 10 - Media Repository Administration: browsing, filtering, searching media assets Figure 11 - Media Repository Administration: tagging media assets Figure 12 - Media Repository Administration: video segmentation and annotation Figure 13 - Learning Contents component Architecture Figura 14 - Learning Contents component process Figure 15 - Learning Contents Management: Authentication Figure 16 - Learning Contents Management: Function list Figure 17 - Learning Contents Management: Learning contents list Figure 18 - Learning Contents Management: Search form Figure 19 - Learning Contents Management: Search result Figure 20 - Learning Contents Management: Insert new learning content Figure 21 - Learning Contents Management: Update function Figure 22 - Learning Contents Management: Update learning content Figure 23 - Learning Contents Management: Delete function Figure 24 - Screenshot of a keyword tree about file types in Excel Figure 25 - Main keyword categories of AW Figure 26 - Excel screenshot indicating keyword building from the tabellaric data provided by AW. 50 Figure 27 - Excel screenshot indicating the taxonomy at Profitex Figure 28 - Excel screenshot for the taxonomy maintenance for AIDIMA Figure 29 - Domain Ontologies Repository Data Model Figure 30 - Domain Ontologies Administration: managing taxonomies Figure 31 - Screenshot of an example community with overlay backpack Figure 32 - Logical data model: primary concepts (based on Le, 2013, p.7) Figure 33 - Database logical view (Le, 2013, p.6) Figure 34 - Database physical view (Le, 2013, p. 9) Figure 35 - Learning Paths/Activities simplified data structure Figure 36 - Learning Paths/Activities Data Model TELL ME Consortium Dissemination: Public 7/139

8 List of Tables Table 1 - Existing Repositories: template form + sample data Table 2 - Existing Repositories for AW pilot Table 3 - Existing Repositories for PROFI pilot Table 4 - Approaches for maintaining keywords Table 5 - OpenApp technologies TELL ME Consortium Dissemination: Public 8/139

9 Executive summary This document accompanies the release of the technical prototypes of WP3 TELL ME Multimedia Learning distributed Repository, providing information about the first versions released. It reflects the implementation achievements for the first platform prototype and will be followed by a second issue describing the final integrated repository (M24). In particular this document describes the following items. The main components introduced by WP3 in TELL ME: Repository Data Access layer, aiming to provide the software modules accessing the repositories with an API representing the individual entry point for accessing the TELL ME data, by means of services retrieving local/distributed media and generic learning contents. For the first prototype, the intial set of services developed includes create, read, update and delete on User profile, Learning Contents (both generic and media ones), Learning Paths/Activities, as well as Learning Content search by ID and Learning Content annotation using the existing domain ontologies; Social Learning Media Cloud first prototype, based on the Open University s SocialLearn 1 software project, focusing on setting up the dedicated TELL ME instance to be used in the trials and creating the walled gardens within to segregate the different manufacturing pilots from each other and to ensure privacy and protection within the boundaries already known to the companies involved. The databases and service interfaces of the TELL ME local repositories, as designed in WP6. The purpose of the local repositories is to store and manage all the data that are commonly useful for the platform as a whole. In particular the following db components have been developed: Learning Contents (both Generic Learning Contents and Multimedia Learning Contents); User profile; Social, Living Labs and Communities (included plans for the connection with the other TELL ME repositories); Domain Ontologies; Learning Paths/Activities. For each of the above repositories, the data model, architecture and high-level services/functionalities technical information for sotware integration are provided, precisely: Service Name, Input, Output, Description, URI, HTTP Methods, Input example, Output example. More specifically, about 50 service interfaces have been developed. In addition, details about the content administration interfaces developed for Multimedia Learning content and Domain Ontologies repositories are provided. A descriptive specification of the existing repositories containing both generic learning contents and audio-visual assets for the three domains (aeronautics, textile, and furniture) related to the three pilots. Several low-level technical details are included such as the entry point of the existing data structures, 1 TELL ME Consortium Dissemination: Public 9/139

10 the adopted technologies, the content categories, etc. when available, with the aim to provide a clear understanding of the contents that are already available, for the benefit of all the technical WPs involved in the prototypes development, as well as the possible methods for integrating them in terms of communication, interfaces and access facilities, for the benefit of the TELL ME repositories design process. Finally, the initial taxonomies for the three pilots, harmonized according to the activity theory from D4.1 and to what (technically) reported in D6.1, are provided as an annex. The repository and services will be refined and fully integrated by M15, composing the CORE of the TELL ME platform. TELL ME Consortium Dissemination: Public 10/139

11 1. Introduction 1.1 Introduction WP3 is a technical workpackage of the TELL ME project; this document accompanies the technical prototype released at M12. After having introduced and described the WP3 positioning in the overall TELL ME architecture, the document reports the following items: Overview of the main components provided by WP3 within TELL ME, namely the Repository Data Access layer and the Social Learning Media Cloud; Description of the existing repositories and/or contents, already available by the three pilots; Repositories and services specifications according to the architecture components (WP6); Conclusions and future plans. The target audience of this document are all the partners (WP 2/3/4/6) directly connecting to the data layer as well as the entire front-end components specific to the prototype requirements derived in light of the architecture (WP6) and the use cases descriptions (WP7). 1.2 Applicable Documents List of applicable documents (for D3.1): TELL ME Description Of Work (DOW) D7.1 User Scenarios, System Requirements and Generalisation Issue 1 (M6) TELL ME Working Document WD3.1 (Internal to the consortium) TELL ME Working Document WD6.1 TELL ME architecture First Version Specification (Internal to the consortium) TELL ME Deliverable D2.1 TELL ME Deliverable D4.1 TELL ME Consortium Dissemination: Public 11/139

12 1.3 Positioning of WP3 in TELL ME TELL ME developments and iterations encompass: user requirements collection, architecture specification and implementation, software test and validation. The PERT diagram of the TELL ME project, taken from the DOW and showed in the picture below, reports WP3 receiving in input the information about the TELL ME architecture from T6.1 (internal Working Document WD6.1) and implementing/integrating its own components. The generated module will then be integrated and tested in the whole architecture in task 6.2 (first prototype first iteration) and 6.3 (final prototype second iteration). Figure 1 - PERT diagram of the TELL ME project TELL ME Consortium Dissemination: Public 12/139

13 2. Introduction of WP3 Components 2.1 Overall Architecture and WP3 The following picture is extracted from the DOW and represents the first version of the TELL ME General Architecture. The distributed learning repository is represented at the bottom of the architecture connected to the three-world platforms layer. Figure 2 - First version of the TELL ME architecture TELL ME Consortium Dissemination: Public 13/139

14 2.2 WP3 Components WP3 core components are: Repository Access (the Repository Data Access Layer, described in the next section) The Repositories: o User Profiling and Experience (detailed in section 4.2) o Multimedia (detailed in section 4.3) o Learning Contents (detailed in section 4.4) o Social, Living Labs and Community (implementing the repository for the Social Learning Media Cloud introduced in 2.4 and detailed in section 4.6) o Ontologies (detailed in section 4.5) o TELL ME path/activities (detailed in section 4.7) 2.3 Repositories Data Access Layer The Repository Data Access Layer purpose is to provide the software modules accessing the repositories with an API representing the individual entry point for accessing the TELL ME data. The goal is to provide a transparent way, regardless of the contents location and format, for the modules connecting to the TELL ME repositories by means of services retrieving local/distributed media and generic learning contents. The idea is to aggregate and expose the services already provided by each repository (please see Chapter 4 for more details) harmonising them by wrapping the available methods using RTful Web Services. Input and output parameters will be exchanged using json/jsonp or XML. In order to support the integration at different (and potentially evolving) degrees during the project lifetime, the Repository Data Access Layer is foreseen to incrementally include dedicated high-level services, as required and detailed by the modules connecting to it (WP2 on top of the list) building on the existing ones in order to implement higher level goals that could be achieved by aggregating and orchestrating the existing service base in a proper way. A more detailed description of each RTful service will be added reflecting the prototype development, in particular in light of the underlying services to be implemented for each core component of the TELL ME Repositories package. For the first prototype, the intial set of services includes: User profile C.R.U.D 2. Learning Contents (both generic and media ones) C.R.U.D. Learning Paths/Activities C.R.U.D. User authentication services (no session management at this level) Learning Content search by ID Learning Content annotation using the existing domain ontologies 2 In computer programming, create, read, update and delete (CRUD) are the four basic functions of persistent storage. TELL ME Consortium Dissemination: Public 14/139

15 2.4 Social Learning Media Cloud The open content revolution of the recent years has brought forward a rich variety of resources available free of charge or for a nominal fee on the web: podcasts, ebooks, education and training apps, and even whole training courses, to name but a few of the popular formats. While this certainly helps create economies of scale, it at the same time boosts demand for an improved social layer on the web a social layer to complement delivery with sharing, content with conversation, and matter with context. There are several alternative generic social media sites available on the web (such as FaceBook, LinkedIn, Xing, or Google Plus) that in principle could be used to support a company s social media cloud strategy. Since the focus within TELL ME, however, is on professional learning and thus particularly emphasis has to be laid on the design requirements and design solutions for the context of manufacturing environments, the WP3 prototype for the social learning media cloud will be based on the Open University s SocialLearn software project. The OU s SocialLearn platform was created to provide such a social layer for personalised as well as informal learning experiences. SocialLearn provides the standard social networking tools known from generic-purpose networking sites, such as status updates, friends and followers, ratings, or the ability to create groups for bird of a feather. More notably, it provides functionalities for learner-generated content such as for sharing thoughts, questions & answers, events, tasks, collections, and paths. The latter learning paths are user-generated play-lists of learning resources available within and outside of SocialLearn. A so-called backpack service assists in collecting learner-generated content in situ by launching functional mini-apps (widgets) as an overlay on top of the websites out on the open web. Figure 1 illustrates this concept: certain use-case sized mini applications (such as a bookmarking widget or a rating widget) can be opened using the backpack launcher on top of existing websites. The backpack apps as well as the main social media website both use the developer API to persistently store, update, and access data in the social layer. TELL ME Consortium Dissemination: Public 15/139

16 Figure 3 - Basic architecture of the social media learning cloud SocialLearn provides modularised recommendation and analytics services to report and advice on learning and to help users in identifying relevant content and people. The first prototype will focus on setting up the dedicated TELL ME instance to be used in the trials and creating the walled gardens within to segregate the different manufacturing pilots from each other and to ensure privacy and protection within the boundaries already known to the companies involved. In parallel further social learning analytics and recommenders will be developed, to advice on learning in manufacturing. This involves training a social-semantic space, in which learners actions can be inspected for performance and underlying competence and where required remediating recommendations can be derived. Together the access API, analytics, and recommender services form the community engine. TELL ME Consortium Dissemination: Public 16/139

17 3. Existing Distributed Repositories and Learning Contents 3.1 Introduction This chapter provides a descriptive specification of the existing repositories containing both generic learning contents and audio-visual assets for the three domains (aeronautics, textile, and furniture) related to the 3 pilots. Several low-level technical details are included such as the entry point of the existing data structures, the adopted technologies, the content categories, etc. when available. The goal is to provide a clear understanding of the contents that are already available, for the benefit of all the technical WPs involved in the prototypes development, as well as the possible methods for integrating them in terms of communication, interfaces and access facilities, for the benefit of the TELL ME repositories design process. In the table here below the template for the information summarisation is reported. Repository Owner Repository Responsible (contact details) AW / PROFITEX / AIDIMA / maurizio.megliola@piksel.com, Database Management System SQL Database, IIS Server, Windows 2003 R2 Server / Access method(s) Remote File System (e.g. FTP) / Web endpoint (HTTP) / Direct Access (SQL) / Web Services(SOAP/RT) / Streaming / Content Category Teaching material / Entry Point Public (Web): provide the URI (e.g. ME/repository/ ) / Private (LAN) Content Type Text/presentations/images/ audio/video Content Format XML / JPEG / MPEG-1 / MPEG-2 / Windows Media / H264 / MP3 / WAV / Content Structure / Standards Content Package Average size of the database SCORM / Proprietary (provide an example) / Raw Data / Metadata / Raw Data + Metadata / 500 doc files, 50 videos, in total 20 GB, etc. How do you manage the life cycle of content? Content is periodically updated / New content is created by necessity TELL ME Consortium Dissemination: Public 17/139

18 Access Privileges Intellectual Property Security Requirements Trainers / Trainees / System Administrator / Public / Private / Commercial / Contents must be protected (DRM) / Contents can be sent without protection / Table 1 - Existing Repositories: template form + sample data 3.2 Aeronautics The following table describes the existing Legacy Repository of Learning and Multimedia in the Aeronautics scenario. Repository Owner Repository Responsible (contact details) Database Management System AW roberto.sanguini@agustawestland.com The repository is an Common Source Data Base (CSDB) which the main objectives are: implement the concept of Write Once Read Many (WORM) this means that the same information entered into the database can be used in different contexts (training manuals, PTT presentations, multimedia, etc); ensure the process of information generation of training; allow the control of contents; apply the QA process; support the training information distribution by means of different media, regardless the source data format. The CSDB utilized by AWTA ITA is Simplicio by ISSELNORD which is an integrated software solution supporting training contents authors on the development, management and delivery of training aids. The system is a SQL database application (Ref. ANNEX- 22_Simplicio Datasheet). Access method(s) Content Category Web Services(SOAP/RT) All the training materials to be used during the theoretical courses in the classrooms. In particular the repository is devoted to develop, manage and issue the Training Publications (training manual, PPT presentation, multimedia, etc.). TELL ME Consortium Dissemination: Public 18/139

19 Entry Point Content Type Content Format Content Structure / Standards Private Document, data modules, 2D drawings, 3D models, audio, video, sound, multimedia application SCORM compliant. XML files, Microsoft Word documents, Microsoft PowerPoint files, Adobe PDF documents, PTC IsoDraw files, Adobe Illustrator CS5 files, Autodesk 3ds Max files, Adobe Flash files, MPEG, AVI, JPEG, TIF, BMP, MP3, SCORM. The standard in use is the ASD S1000D Issue 4.0 that is specific for training publications. The document can be downloaded from the following link: Content Package Raw Data + Metadata (Dublin Core) The CSDB Simplicio identifies a Training Publication as Publication Module (PM). The PM is a collection of Data Module (DM) for the type of course to which this document relates. A DM is a self-contain data unit used for the description and identification of helicopter systems. The data unit consists of an identification section and one of status as well of content. It is produced in a form that can be inserted and used by the CSDB. For example the text of publication is written in XML format in which are placed the link to the graphics. Average size of the database How do you manage the life cycle of content? About multimedia files (2D/3D graphics, video, photos, PDF, etc.) plus 11 GB of documents. The AW Operational Procedure Design of the Training Course describes with the Annex 2 Training Publication Generation and Management the life cycle of content. In particular this document details the requirements and the methodologies that AWTA utilizes for the generation of training manuals, as well as the training aids to be used during the theoretical courses provided at the AWTA and the related database. The development is carried out according to the ASD S1000D Issue 4.0 standard. The method used as reference to populate the CSDB allows the application of the concept of WORM (Write Once Ready Many). This method allows the control of information utilizing, as much as possible, the TELL ME Consortium Dissemination: Public 19/139

20 data generated by other AW department. Access Privileges Intellectual Property Security Requirements Trainers / Trainees / System Administrator / Subject Matter Experts Private Contents must be protected Table 2 - Existing Repositories for AW pilot 3.3 Textile The current status of the repository description by Profitex is reported in the following table: Repository Owner Repository Responsible (contact details) Database Management System Access method(s) Content Category PROFI Klaus.zuleeg@zuleeg.de Lotus Notes Server Notes native (internal) http with user + password (external) Teaching and reference material Entry Point External Access: User name: Password: extern.webaccess@profitex-textilservice.de Owae nternal Access: LAN Content Type Text, rtf, images, video Content Format rich text format, pdf, mpeg-*,... Content Structure / Standards Similarly to Windows Explorer-Structure 3 Content Package Raw Data / Metadata / Raw Data + Metadata / Average size of the database How do you manage the life cycle of content? Access Privileges New content is created and changes are integrated by necessity. Standard-User, Admin-User, System Administrator 3 See next figure TELL ME Consortium Dissemination: Public 20/139

21 Intellectual Property Security Requirements Private Contents can be sent without protection Table 3 - Existing Repositories for PROFI pilot The following figure gives an overview about the folder structure: Figure 4 - Screenshot the folder structure in Lotus Notes. The folder structure translates to: Security at work place o Regulative affairs about security at work place.rtf o Forklift driver Klaus.flv IT o Documentation FTP Configuration for file exchange.pdf Quality Management o Labelling fabric errors.pdf TELL ME Consortium Dissemination: Public 21/139

22 Figure 5 - Screenshot the folder structure in the Web Browser. The document labelling fabric errors.rtf Fehlerkennzeichnung in der Endkontrolle by Michael Heinrich is a processing description; the next figure shows a screenshot of this document. Figure 6 - Screenshot of a typical processing description, here about how to mark errors in the inspection of readymade fabrics. TELL ME Consortium Dissemination: Public 22/139

23 3.4 Furniture The input from AIDIMA is described as a separate Excel file, not referring to the template provided in Table 1, and focusing on the available contents rather than the available facilities aimed at providing access to the same contents. Please see the Annex (Chapter 6.4) for a summary of the collected data. From an early analysis, the following commonalities have been extracted: Content Categories Web pages (HTML documents/uri) Slides (PPT) PDF documents (textual) Video (media) Target Audience: Manager (top management in a company. Director) Head of area (head of department, area, section, etc. - managing people) Technician (in laboratories or specific areas not managing people) Postgraduate Teacher (including early students with no grade) Both English and Spanish language is adopted. TELL ME Consortium Dissemination: Public 23/139

24 4. TELL ME Repositories Specifications 4.1 Introduction This chapter provides specification insights about the TELL ME local repositories, as designed in WP6 including the data structure as well as high-level services/functionalities technical information for sotware integration, precisely: Service Name, Input, Output, Description, URI, HTTP Methods, Input example, Output example. The purpose of the local repository is to store and manage all the data that are commonly useful for the platform as a whole, in particular: Learning Contents o Generic Learning Contents Chapter 4.4 o Multimedia Learning Contents Chapter 4.3 User profile and experience Chapter 4.2 Social, Living Labs and Communities Chapter 4.6 Domain Ontologies Chapter 4.5 Learning Paths/Activities Chapter 4.7 TELL ME Consortium Dissemination: Public 24/139

25 4.2 User Profiling and Experience The User Profiling and Experience repository aim is to provide facilities for storing and handling the user profile and authentication details, providing data about the linked workplace including the supported hardware devices as well as personal skills and experience tracking. While the experience tracking will be performed by logging the platform events leveraging the local file system (with the related specifications provided in the second issue of the deliverable), the user profiling data model has been designed with more details and presented in the next paragraph Data Model Figure 7 - User Profile and Experience Data Model. The UserDetails table contains static details such as the user name, surname, , etc. (the list of details is subject to be extended during the development phase) and links to: Audience Used to describe the user Roles (e.g.: Carpenter, Assembler etc.) associated to the considered user. The AudienceList table provides connections to the audience taxonomy described in Chapter 4.5 Domain Used to link the considered user to a particular domain, as described in the Domain Ontologies repository Context In order to provide details related to the workplace (a list of attributes could be specified in the WorkspaceAttributeList table, e.g.: indoor/outdoor, noise level, etc.) + a list of supported devices for the learning delivery TELL ME Consortium Dissemination: Public 25/139

26 Skills used to link the considered user to his/her skills The authentication is implemented by separating the user identity ( User table) by the personal details ( UserDetails table) using and hash function. The User table stores only the username but not the password. The UserDetails table s primary key is represented by the results of the function hash(username + password) where the password is provided by the user in real-time when logging in. Figure 8 - User Authentication with privacy protection. In this way a malicious user breaking into the system is prevented to associate an identity to personal details Services Service Name createuser Input username, user details Output ack Description Registers a new user for the TELL ME platform. URI ME/TELL Mervices/createUser HTTP Methods POST Input example userdetail={ username : TELL MEtestuser, audiencelistid : 1, skilllistid : 1, domainid : 1, contextid : 1, password : ABC123, name : Mario, surname : Rossi, mario@rossi.it, otherdetails : { arbaaid :2}} Output example { message : } or { error : } Service Name deleteuser TELL ME Consortium Dissemination: Public 26/139

27 Input Output Description URI HTTP Methods Input example Output example username or userid ack Deletes an existing user from the TELL ME platform ME/TELL Mervices/deleteUser DELETE userdetail= { username : TELL MEtestuser, sessionid : aaaa } { message : } or { error : } Service Name updateuser Input username, password, updated user details Output ack Description Updates the profile of an existing user URI ME/TELL Mervices/updateUser HTTP Methods POST Input example { audiencelistid : 1, domainid : 1, contextid : 1, name : Mario, surname : Rossi Jr, asd@asdasd.it, otherdetails : { arbaaid :32}, sessionid : aaaa } Output example { message : } or { error : } Service Name getuserdetails Input username, password Output ack, user details Description Retrieves the user details providing username + password. Returns an errorcode together with the details. URI ME/TELL Mervices/getUserDetails HTTP Methods GET Input example userdetail= { sessionid : aaaa } Output example { username : TELL MEtestuser, audiencelistid : 1, skilllistid :1, domainid : 1, contextid : 1, name : Mario, surname : Rossi, mario@rossi.it, otherdetails : { arbaaid :2}} or { error : } Service Name Input Output Description URI HTTP Methods Input example Output example isregistered username boolean Checks if the requested user is already registered and returns a Boolean accordingly ME/TELL Mervices/isRegistered GET userdetail={ username : TELL MEtestuser } { message : true/false} or { error : } Service Name Input Output userauthenticate username, password ack, token (to manage the session) TELL ME Consortium Dissemination: Public 27/139

28 Description URI HTTP Methods Input example Output example Authenticate the user using hash(username+password) as primary key. Returns an errorcode together with a live-generated token if successfully registered ME/TELL Mervices/userAuthenticate POST userdetail= { username : TELL MEtestuser, password : ABC123 } { sessionid, }or { error : } Service Name logout Input sessionid Output boolean Description Log off the user from the current session URI ME/TELL Mervices/logOut HTTP Methods POST Input example userdetail={ sessionid : aaaa } Output example { message : } or { error : } TELL ME Consortium Dissemination: Public 28/139

29 4.3 Multimedia Contents The Multimedia Repository aim is to provide facilities for storing and then handling (through services) the audiovisual learning contents of the TELL ME platform, being these already existent (see Chapter 3), prepared for the project or ingested (see WP2, Task 2.3). Below is the current data model Data Model Figure 9 - Multimedia Repository Data Model. The central table named MediaContent is deputed to store audiovisual contents. Each one is linked to: A category (so far: Audio/Video/Video without audio/picture), linking to the Category table, that will be populated with names, accordingly ( CategoryNames table) as well as a list of attributes describing each considered category (e.g.: bitrate, resolution, video codec, etc.) A content quality (Low Quality/High Quality, etc.) that could be useful for the Streaming Engine described in WP2 Task 2.3 Access details Containing connection details for a remote, existing content or the path to a local content. An attribute instance That represents an instance of the category details structure, associated to the considered media content A list of annotations Useful to add tags or, in general, metadata to the considered media content, in light of the taxonomies described in the Domain Ontologies repository (Chapter 4.5). TELL ME Consortium Dissemination: Public 29/139

30 4.3.2 Services The following tables provide a summary of the main services published. Further higher-level services could be added during the prototype development in order to satisfy specific requirements of the interacting modules (mainly WP2 and engines). Service Name getmediacontentbyid Input MediaContentID Output ack, binary access details Description Retrieves the media content file URI ME/TELL Mervices/getMediaContentByID HTTP Methods GET Input example MediaContent={ mediacontentid : 1} Output example { mediacontentid :1, categoryid :1, qualityid :1, accessdetails :, attribute :, quality : low, category : Video } Service Name getmediacontentsbyquality Input Quality Output ack, MediaContentID list Description Retrieves the media content IDs related to the desired quality URI ME/TELL Mervices/getMediaContentsByQuality HTTP Methods GET Input example MediaContent= { qualityid : 1} Output example [{ mediacontentid :1, categoryid :1, qualityid :1, accessdetails :, attribute :, quality : low, category : Video },{ mediacontentid :3, categoryid :1, qua lityid : 1, accessdetails :, attribute :, quality : low, category : Video }] Service Name getmediacontentbycategory Input Category name Output ack, MediaContentID list Description Retrieves the media content IDs related to the desired category (video, audio, etc.) URI ME/TELL Mervices/getMediaContentByCategory HTTP Methods GET Input example MediaContent={ categoryid : 1} Output example [{ mediacontentid :1, categoryid :1, qualityid :1, accessdetails :, attribute :, quality : low, category : Video },{ mediacontentid :2, categoryid :1, qua lityid : 1, accessdetails :, attribute :, quality : low, category : Video }] Service Name Input Output getmediacontentattributes MediaContentID ack, AttributesInstance TELL ME Consortium Dissemination: Public 30/139

31 Description Retrieves the media content attributes (e.g.: bitrate, size, etc.) related to the desired content ID URI ME/TELL Mervices/getMediaContentAttributes HTTP Methods GET Input example MediaContent={ mediacontentid : 1} Output example { attribute : } Service Name getmediacontentannotations Input MediaContentID Output ack, idannotation list Description Retrieves the list of Annotation ID, containing domain-specific annotation related to the considered media content URI ME/TELL Mervices/getMediaContentAnnotations HTTP Methods GET Input example MediaContent={ mediacontentid : 1} Output example [{ taxonomyid :0, idfather :0, name : },[{ taxonomyid :0, idfather :0, name : }] Service Name getmediacontentsegments Input MediaContentID Output ack, idsegment list Description Retrieves the media content segment list (IDs) related to the specified media content URI ME/TELL Mervices/getMediaContentSegments HTTP Methods GET Input example MediaContent= { mediacontentid : 1} Output example [{ segmentid :0, idfather :0, start_time :, end_time :, name :, description : },{ segmentid :1, idfather :0, start_time :, end_time :, name :, description : }] Service Name issegment Input MediaContentID Output Boolean Description Returns true if the considered mediacontent is a segment, false otherwise URI ME/TELL Mervices/isSegment HTTP Methods GET Input example MediaContent={ mediacontentid : 1} Output example { issegment : true/false } Service Name Input Output getparent MediaContentID (must be a segment) ack, MediaContentID TELL ME Consortium Dissemination: Public 31/139

32 Description Returns the father ID related to the considered mediacontent segment URI ME/TELL Mervices/getParent HTTP Methods GET Input example MediaContent={ mediacontentid : 1} Output example { getparentid :0} Service Name storemediacontent Input URI, Category, Quality Output Ack, MediaContentID Description Stores the media content referenced by URI together with the information describing the content category and quality. Returns the stored MediaContentID if successful URI ME/TELL Mervices/storeMediaContent HTTP Methods POST Input example MediaContent={ categoryid : 1, qualityid : 1, accessdetails : } Output example { MediaContentId :0} or { error : } Service Name storemediacontentattributes Input MediaContentID, attributesinstance Output Ack Description Stores the media content attributes instance for the considered media content URI ME/TELL Mervices/storeMediaContentAttributes HTTP Methods POST Input example MediaContent={ MediaContentId : 1, attributesinstance : } Output example { message : } or { error : } Service Name storemediacontentannotations Input MediaContentID, Attributes Output Ack Description Stores the media content attributes (tags for the considered media content URI ME/TELL Mervices/storeMediaContentAnnotations HTTP Methods POST Input example MediaContent= { MediaContentId : 1, annotationslist : [{ taxonomyid : 1},{ taxonomyid : 2},{ taxonomyid : 3}]} Output example { message : } or { error : } Service Name Input Output Description URI HTTP Methods annotatesegment Father MediaContentID, Segment MediaContentID Ack Stores the media content hierarchy between the father and the son (segment) ME/TELL Mervices/annotateSegment POST TELL ME Consortium Dissemination: Public 32/139

33 Input example MediaContent={ MediaContentId : 1, FatherMediaContentId : 3, segmentslist : [{ starttime : 00:00:00, endtime : 00:05:00, description : },{ starttime : 00:07:00, endtime : 00:12:00, description : },{ starttime : 00:22:00, endtime : 00:45:00, description : }]} Output example { message : } or { error : } Content Administration The content administration component is aimed at managing the media repository contents in a visual way; hence the intended target is the platform administrator / the trainer. The main functionalities envisaged are: Browsing, filtering, search of media assets Tagging of the media contents Video segmentation and annotation For the first prototype the repository has been populated manually. Later on the idea is to use ad-hoc scripts for fast processing and injection as well as to leverage the PIKSEL VideoCMS 4, customising certain parts of the tool in order to reflect the intended workflow. As an indicative example, below you can find some mock-ups of the intended interface, for the functionalities listed above. 4 TELL ME Consortium Dissemination: Public 33/139

34 Figure 10 - Media Repository Administration: browsing, filtering, searching media assets. The figure above presents a list of media contents grouped in categories (or projects) on the left. The administrator is enabled to browse them and interact with each content by clicking on the various icons (edit, delete, etc.). Below is a mock-up of the interface aimed at tagging the selected content, in the hypothesis of clicking the edit button: Figure 11 - Media Repository Administration: tagging media assets. The idea is to leverage, for the keywords list, the domain taxonomies defined in Chapter 4.5. TELL ME Consortium Dissemination: Public 34/139

35 Moreover, in order to speed-up the video segmentation and annotation phase for both the already existing and the newly ingested contents, below is a mock-up of the PIKSEL Video Editor applied to generic media content: Figure 12 - Media Repository Administration: video segmentation and annotation. 4.4 Learning Contents Overall Component Name Learning Content repository Reference WP Task Task 3.1 Responsible TXT Version 1.0 Source Control Contact Person Michele Sesana (michele.sesana@txtgroup.com) Short Description The Learning Content repository supports the management of learning contents Data Model The Learning Content repository supports the management of learning content. The trainer in this mode has the vision of all contents. The contents will be saved and represented by: 1. content name: to identify in unique mode the content; TELL ME Consortium Dissemination: Public 35/139

36 2. tags: to identify the content, these will represent the content semantic. The keys will be suggested come from one RDF schema; 3. format content: to represent the format of contents (for example AVI, PDF, etc) Purpose and Functionalities The application provides the following functionalities: 1. Insert new learning content, the user can insert a new learning content, he should insert: o a name (unique) of learning content, o the tags (inserted manually or choose from a list loaded from RDF schema) o URL, represents the local location of the related file to upload in the learning content repository, o Format, represents the format of the learning content file 2. Update learning content, the user can update one learning content, he choose the content and after can modify the tags, URL, format or file 3. Delete learning content, the user can delete one or more learning contents 4. Search all learning content, the user can see all learning content 5. Search specific content, the user can filtered by specific tags: he can insert manually the tag (there is also the autocomplete) or he can select from one list wich suggested the tags, this list come from OWL format 6. Download the media file related to the learning content Architecture Figure 13 - Learning Contents component Architecture. TELL ME Consortium Dissemination: Public 36/139

37 Figura 14 - Learning Contents component process. The architecture is composed by 5 items: 1. MONGODB database, MongoDB 5 (from "humongous") is an open source document-oriented database system developed and supported by 10gen. It is part of the NoSQL family of database systems. Instead of storing data in tables as is done in a "classical" relational database, MongoDB stores structured data as JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster. 2. Learning Content Service (SERVER-SIDE), is a SOAP/RT services to interfaced with MONGODB, the principal services are: insert, update, delete, read in a MONGODB. 3. Learning Content Manager (CLIENT-SIDE) is the web application, the language are used for create user interface and used the service come from Learning Content Service. The language used is HTML5, CSS3, Javascript, jquery, jquery mobile, jqueryui Technical Information Nature Programming Language Development Tools Additional libraries No-SQL database HTML5 + CSS3 + Javascipt + jquery+ jquery mobile, jquery UI, java Visual studio 2012, Eclipse Juno N/A 5 TELL ME Consortium Dissemination: Public 37/139

38 Application Server Databases Apache Tomcat MONGODB Services The following tables provide a summary of the main services offered by Learning Content Service. Service Name getalllearningcontents Input - Output Learning contents list Description Retrieves all the learning contents related to a context URI MERestService/learningContent Parameters context HTTP Methods GET Parameters?context=aw example Output example [ { "_id": { "$oid": "51fb6ee6ed27071e7bde393f" }, "tags": [ "AW139" ], "id": "AW139ScormPackages", "chunksize": , "length": , "md5": "add2dd6b6b507310de380880d81767fc", "filename": "CH67.zip", "format": "scorm", "contenttype": "application/zip", "uploaddate": { "$date": " T08:33:42.661Z" }, "aliases": null }, { "_id": { "$oid": "51fb701aed27071e7bde3afd" }, "tags": [ "AW139" ], "id": "AW139ScormPackagesCH71", "chunksize": , "length": , "md5": "0855a3fa5ba6e4aaeb564b ", "filename": "CH71.zip", TELL ME Consortium Dissemination: Public 38/139

39 "format": "scorm", "contenttype": "application/zip", "uploaddate": { "$date": " T08:38:50.638Z" }, "aliases": null } ] Service Name filterlearningcontents Input - Output Learning contents list Description Retrieves the learning contents, related to a content, that matches the given tags URI MERestService/learningContent Parameters Context, tags HTTP Methods GET Input example?context=aw&tags=aw109,video Output example [ { "_id": { "$oid": "51fb762fed27071e7bde3c32" }, "tags": [ "AW109", "video" ], "id": "A109E_01", "chunksize": , "length": , "md5": "5f5fd2489c2976cc16e4e0b2f91deabd", "filename": "A109E_01.avi", "format": "avi", "contenttype": "video/x-msvideo", "uploaddate": { "$date": " T09:04:47.679Z" }, "aliases": null } ] Service Name getlearningcontent Input - Output Learning content file input stream Description Retrieve a learning content URI MERestService/learningContent Parameters Context, learningcontentid HTTP Methods GET TELL ME Consortium Dissemination: Public 39/139

40 Parameters?context=aw&id=lc1 example Output example - Service Name Input Output Description URI Parameters HTTP Methods Parameters example Output example uploadlearningcontent Learning content file ack Upload a new learning content file in the learning content repository MERestService/learningContent Context, learningcontentid, tags POST?context=aw&id=lc1&tags=AW109,video 204 Success Created Service Name Input Output Description URI Parameters HTTP Methods Parameters example Output example updatelearningcontent Learning content file ack Update a learning content in the learning content repository MERestService/learningContent Context, learningcontentid, tags PUT?context=aw&id=lc1&tags=AW109,video 204 Success Created Service Name deletelearningcontent Input - Output ack Description Delete a learning content in the learning content repository URI MERestService/learningContent Parameters Context, learningcontentid HTTP Methods DELETE Parameters?context=aw&id=lc1 example Output example 200 Success Learning Contents Management The learning content manger module is aimed at managing the learning content repository by the trainer, using a HTML5 GUI. The main functionalities envisaged are: Search e visualization of learning contentsbrowsing, TELL ME Consortium Dissemination: Public 40/139

41 Insertion of learning contents, Update of learning contents information, Delete of selected learning contents. As an indicative example, below you can find some screenshot of the intended interface, for the functionalities listed above. After the administrator/trainer authentication the GUI presents the list of learning content functions. Figure 15 - Learning Contents Management: Authentication. Figure 16 - Learning Contents Management: Function list. TELL ME Consortium Dissemination: Public 41/139

42 Using the See all contents function the GUI presents the list of all learning contents stored in the learning content repository, with the related attributes: ID, keys (tags), format and download link. Figure 17 - Learning Contents Management: Learning contents list. The search function allows the user to filter the learning contents by specific tags. The search form provides a autocomplete function that support the user to get the tags defined in the taxonomy. Moreover, the form allows to search all or any of the tags required. If one or more learning contents match the required tags, the GUI shows them with the related attributes. Figure 18 - Learning Contents Management: Search form. TELL ME Consortium Dissemination: Public 42/139

43 Figure 19 - Learning Contents Management: Search result. The insertion function provides a form to set the new learning content attributes and upload the related file from the local file system. The learning content tags and format can be selected from a tree visualization of the taxonomy. Figure 20 - Learning Contents Management: Insert new learning content. The update function allow the user to update the information of a selected learning content, except its ID. TELL ME Consortium Dissemination: Public 43/139

44 Figure 21 - Learning Contents Management: Update function. Figure 22 - Learning Contents Management: Update learning content. The delete function allows the user to delete one or more learning contents from the repository. TELL ME Consortium Dissemination: Public 44/139

45 Figure 23 - Learning Contents Management: Delete function. TELL ME Consortium Dissemination: Public 45/139

46 4.5 Domain Ontologies This section reports about the development of domain ontologies and models for tagging TELL ME content of the three pilot partners Agusta Westland (Aeronautics domain), AIDIMA (Furniture domain) and Profitex (Textile domain). Any content of the TELL ME system will be described by a special combination of keywords, called tags. These tags are usually commonly used terms in a group of people that communicate because they share similar interests. There are several approaches for maintaining keywords, e.g.: Keyword maintenance approach How users enter keywords Benefits and drawbacks The open, subjective approach The assisted approach The controlled approach each user enters the keywords that he has in mind when a user starts entering a keyword, the system suggests a list of matching keywords, sorted by frecuency of use the user may select keywords from a given list, only + Easy to use - different spelling, synonyms, singular and plural possible - no controlled vocabluary + Easy to use - no controlled vocabulary - different spelling and synonyms still possible + Controlled, managed vocabluary - How to deal with new terms? Table 4 - Approaches for maintaining keywords For organising keywords, there are the following keyword organisation schemes: Glossary A glossary is typically a flat, alphabetical list of terms that form in particular domain knowledge. The list comes usually with definitions for these terms. An index is in contrast to a glossary an alphabetical list of terms with references to their appearance in a document. Taxonomy A taxonomy or a taxonomic scheme is a classification of terms, usually in a tree-like, segmenting structure, a containment hierarchy of terms in super and sub sets. Thesaurus In general use, thesauri form lists of words that are grouped by similarity of meaning (synonyms and sometimes antonyms). In information retrieval, thesauri are used to guide both indexers and searchers for select the same preferred term representing a given subject. ISO defines thesauri as a controlled and structured vocabulary in which concepts are represented by terms, organized so that relationships between concepts are made explicit, and preferred terms are accompanied by lead-in entries for synonyms or quasi-synonyms. The norm gives recommendations for the development and maintenance of thesauri intended for 6 ISO (2011): Information and documentation -- Thesauri and interoperability with other vocabularies -- Part 1: Thesauri for information retrieval. ( ). TELL ME Consortium Dissemination: Public 46/139

47 information retrieval applications and provides a data model and recommended format for the import and export of thesaurus data. Concept Maps Concept maps form a way to express relations between terms, usually by expressing the specific relation type between terms in a written manner. Topic maps form a standard that relies on topic maps:- ISO/IEC 13250: Relevant resources to a particular topic are called occurrences, links to them can be inserted. Topic maps can be easily expressed as RDF, they have a higher level of semantic abstraction, as they allow n-ary relationships between any number of nodes. Ontologies form in contrast to these keyword organisation schemes shared descriptions of terms (concepts), their attributes and relationships as well as rules and axioms for their properties. There are a number of so called ontology languages for encoding ontologies. It can be seen that any kind of formalised information schema including the ones mentioned above forms an ontology in broader terms. Domain ontologies do usually represent knowledge for a specific part, the domain, of the real world. Keyword usage at the three pilot partners Usually, employees in a company tend to use always the same terms to refer to activities, roles, means of production, goods, etc. Therefore, the need for synonyms is only given, if i.e. the daily business vocabulary is different because of distinct production sites or only sparsely communicating subdivisions. What happens often is that employees tend to refer to groups of business objects in an abstracting manner, e.g. fabric means in Profitex any kind of fabric, woven or knitted one. Therefore, a domain ontology for keywords needs to be able to cope with this aspect. The abovedescribed possibility to formalise different types of relations between terms seems not necessary as employees at the three pilot partners are intuitively aware of these. Keyword domains An important aspect for designing domain ontologes for tagging form the keyword domains. There will be a least two different description and communication domains in the social communities for TEL learning at the pilot partners: the individual ones, e.g. for each associate of AIDIMA or AW, and the community domains, e.g. the training materials domain of AIDIMA or of AW. Whereas the terms in the training material domains form either controlled vocabulary by the training material provider or standardised general terms, the terms in the individual domains refer to specific and real items, e.g. the powertool Bosch GST 160 CE Professional, a specific fabric inspection lot at Profitex or a specific location in the hangar of a helicopter maintenance station. It can be seen that these terms in the individual domains can be seen as sub terms of the training material domains. The training material domains do further consist of terms that relate to the used media/ file types, forms of training activities, etc. These terms belong to subdomains that are usually provided with the TELL ME system. Ther are further subdomains of the training material domains that are specific for the business activities of the training material provider, e.g. AW, PROFITEX or AIDIMA. 7 TELL ME Consortium Dissemination: Public 47/139

48 For the first prototypes, the partners decided to start to organise partner-specific keywords as simple taxonomies. DITF developed these individual taxonomies together with the pilot partners. The taxonomies are currently mainly organised in Excel sheets for: Easy, intuitive editing Simple exchange Simple export to another application Later on, Excel as an intermediate file format for taxonomies was replaced by another one that will meet all necessary design specifications for the ontology-based keyword instances. The taxonomies were imported into repositories, then. Figure 24 - Screenshot of a keyword tree about file types in Excel Taxonomies Training material-specific domains Currently, the following training-material-specific taxonomies are already completed: File types by file extension (see Error! Reference source not found., p. Error! Bookmark not defined.) Aeronautics - Augusta Westland TELL ME Consortium Dissemination: Public 48/139

49 AW has provided quite extensive information about necessary keywords for tagging training content. The provided keywords were converted to taxonomies in Excel. The main top level keyword categories of AW 8 : It can be seen that the keyword categories cover: Figure 25 - Main keyword categories of AW. Tools, equipment and consumables Location areas in the helicopter Maintenance tasks System and subsystem definitions Model and mission types Document types If suitable, special prefixes were added to identify keyword names spaces easier. The following figure gives an example how the keywords are generated from the table-based input from AW. 8 The whole tree contains currently 1033 items and is far too big for an exemplary inclusion. TELL ME Consortium Dissemination: Public 49/139

50 Figure 26 - Excel screenshot indicating keyword building from the tabellaric data provided by AW. Using special prefixes permits to search e.g. for 09 and to retrieve both the keyword for ATA 100 systems definitions and its sub keywords, but as well other keywords that contain 09. But searching for SNS:09 will only lead to keywords from the ATA 100 systems definitions tree Textile - Profitex Here is an example excerpt from Excel that indicates the current taxonomy: TELL ME Consortium Dissemination: Public 50/139

51 Figure 27 - Excel screenshot indicating the taxonomy at Profitex. The taxonomy for Profitex has currently the following main categories: Tasks Work environments Means of Production Error types and codes Materials As Profitex is only an SME with just one major production stage, the keyword tree is currently relatively simple. The distinct fabric error types should be added as keywords, as well. For easier understanding in the consortium, the taxonomy for Profitex is available both in English and in German (except of the error codes) Furniture - AIDIMA The taxonomy for AIDIMA is a quite extensive one, as there is a clear division of labour and there are different work locations, a broad variety of machinery and tools as well as a wide portfolio of possible materials and products. TELL ME Consortium Dissemination: Public 51/139

52 The following screenshot shows the grouping of tasks for preparing and installing parts into a ship s hull. The tabs indicate the main keyword groups. Figure 28 - Excel screenshot for the taxonomy maintenance for AIDIMA. The taxonomy for Profitex has the following main categories: Work Environment Types of profession Production tools Input products Output products Furniture destination Tasks for blue collar workers The taxonomy is currently maintained in English. It refers in general to types of products and tools, hence there is a need for additional keywords that identify concrete items or locations (see above) Data Model TELL ME Consortium Dissemination: Public 52/139

53 Figure 29 - Domain Ontologies Repository Data Model. The Domain table is the central one, containing the name of the domain. Linked to it the data model handles: Workplace attributes ( WorkplaceAttributes table), providing a list of details related to a particular workplace (e.g.: indoor, outdoor, noisy, quiet, etc. etc.) The skills tree ( SkillTaxonomy table), providing the keywords tree for the supported skills associated to the considered domain The tags tree ( TagTaxonomy table), providing the keywords tree for the supported tags associated to the considered domain (useful for tagging learning contents) The audience categories tree ( AudienceTaxonomy table), providing the keywords tree for the supported audience categories associated to the considered domain The devices tree ( DeviceTaxonomy table), providing the keywords tree for the supported devices associated to the considered domain; each devices may have specific attributes ( Device table) Services Service Name Input Output getdomains none List of domain names TELL ME Consortium Dissemination: Public 53/139

54 Description URI HTTP Methods Input example Output example Retrieves the list of domain names ME/TELL Mervices/getDomains GET none [{"iddomain":1,"domainname":"name"}] Service Name getdomaintagstree Input domainname Output List of idtagsltaxonomy Description Retrieves the tags tree for the desired taxonomy URI ME/TELL Mervices/getDomainTagsTree HTTP Methods GET Input example domain={'domainid': 1} Output example [{"idfather":-1,"idtagtaxonomy":1,"name":"test1","leaf":false},{"idfather":-1, "idtagtaxonomy":2,"name":"test2","leaf":false},{"idfather":1,"idtagtaxonomy":3,"name":"subtest1","leaf":false},{"idfather":2,"idtagtaxono my":4, "name":"subtest2","leaf":false}] Service Name getdomainskillstree Input domainname Output List of idskillstaxonomy Description Retrieves the skills tree for the desired taxonomy URI ME/TELL Mervices/getDomainSkillsTree HTTP Methods GET Input example domain={'domainid': 1} Output example [{"idfather":-1,idskilltaxonomy":1,"name":"analysis","leaf":false},{"idfather":- 1,idSkillTaxonomy":2,"name":"Organization","leaf":false},{"idFather":1,idSkillTaxo nomy":3,"name":"recognizing attributes","leaf":false},{"idfather":1,idskilltaxonomy":4,"name":"categorizing","l eaf":false},{"idfather":1,idskilltaxonomy":5,"name":"making analogies","leaf":false},{"idfather":2,idskilltaxonomy":6,"name":"memorizing","le af": true},{"idfather":2,idskilltaxonomy":7,"name":"goal setting","leaf":true}] Service Name getdomainaudiencetree Input domainname Output List of idaudiencetaxonomy Description Retrieves the audience tree for the desired taxonomy URI ME/TELL Mervices/getDomainAudienceTree HTTP Methods GET Input example domain={'domainid': 1} Output example [{"idfather":- 1,"idAudienceTaxonomy":1,"name":"Test","leaf":false},{"idFather":1,"idAudienceT axonomy":2,"name":"subtest","leaf":true}] Service Name getdomainworkplaceattributes TELL ME Consortium Dissemination: Public 54/139

55 Input domainname Output List of idworkplaceattributetaxonomy Description Retrieves the workplace attributes for the desired taxonomy (potentially a tree) URI ME/TELL Mervices/getDomainWorkplaceAttributes HTTP Methods GET Input example domain={'domainid': 1} Output example [{"idfather":- 1,"idWorkplaceAttributeTaxonomy":1,"name":"Test","leaf":false},{"idFather":1,"id WorkplaceAttributeTaxonomy":2,"name":"SubTest","leaf":true}] Service Name getdomaindevices Input domainname Output List of iddevicetaxonomy Description Retrieves the devices ID list for the desired taxonomy URI ME/TELL Mervices/getDomainDevices HTTP Methods GET Input example domain={'domainid': 1} Output example [{"iddevicetaxonomy":1,"idfather":- 1,"name":"Tablet","leaf":false,"attributes":""},{"idDeviceTaxonomy":2,"idFather":- 1,"name":"Phone","leaf":false},{"idDeviceTaxonomy":3,"idFather":1,"name":"Appl e","leaf":false},{"iddevicetaxonomy":4,"idfather":1,"name":"samsung","leaf":fals e},{"iddevicetaxonomy":5,"idfather":2,"name":"apple","leaf":false},{"iddevicetax onomy":6,"idfather":2,"name":"samsung","leaf":false},{"iddevicetaxonomy":7,"id Father":3,"name":"iPhone5","leaf":false},{"idDeviceTaxonomy":8,"idFather":5,"na me":"ipad2","leaf":false},{"iddevicetaxonomy":9,"idfather":4,"name":"galaxy S4","leaf":false},{"idDeviceTaxonomy":10,"idFather":6,"name":"Galaxy Tab 10","leaf":false}] Service Name getdevicesattributes Input iddevicetaxonomy Output attributes Description Retrieves the attributes instance describing the considered device specs URI ME/TELL Mervices/getDevicesAttributes HTTP Methods GET Input example domain= {'iddevice': 102} Output example [{"name":"galaxy S4", attributes : }] Service Name Input Output Description URI HTTP Methods adddomaintag domainname, tag name, [fatherid] ack Adds a new tag to the existing taxonomy for the considered domain. The fatherid is optional ME/TELL Mervices/addDomainTag POST TELL ME Consortium Dissemination: Public 55/139

56 Input example {'iddomain': 1,'idFather': -1,'name': 'test','leaf': 1} Output example { message : } or { error : } Service Name deletedomain Input domainname Output ack Description Remove an existing domain URI ME/TELL Mervices/deleteDomain HTTP Methods DELETE Input example {'domainid': 1} Output example { message : } or { error : } Service Name deletedomaintag Input domainname, tag name tag ID Output ack Description Remove an existing tag from the taxonomy tree as well as all the sons URI ME/TELL Mervices/deleteDomainTag HTTP Methods DELETE Input example {'domainid': 1, 'idtagtaxonomy' : 1} Output example { message : } or { error : } Service Name Input Output Description adddomainskill domainname, skill name, [fatherid] ack Adds a new skill to the existing taxonomy for the considered domain. The fatherid is optional ME/TELL Mervices/addDomainSkill POST URI HTTP Methods Input example {'iddomain': 1,'idFather': -1,'name': 'test','leaf': 1} Output example { message : } or { error : } Service Name deletedomainskill Input domainname, skill name skill ID Output ack Description Remove an existing skill from the taxonomy tree as well as all the sons URI ME/TELL Mervices/deleteDomainSkill HTTP Methods DELETE Input example {'domainid': 1,'idSkillTaxonomy' : 1} Output example { message : } or { error : } Service Name Input Output adddomainaudience domainname, audience name, [fatherid] ack TELL ME Consortium Dissemination: Public 56/139

57 Description Adds a new audience category to the existing taxonomy for the considered domain. The fatherid is optional URI ME/TELL Mervices/addDomainAudience HTTP Methods POST Input example {'iddomain': 1,'idFather': -1,'name': 'test','leaf': 1} Output example { message : } or { error : } Service Name Input Output Description deletedomainaudience domainname, audience name audience ID ack Remove an existing audience category from the taxonomy tree as well as all the sons ME/TELL Mervices/deleteDomainAudience DELETE URI HTTP Methods Input example {'domainid': 1,'idAudienceTaxonomy' : 1} Output example { message : } or { error : } Service Name adddomainworkplace Input domainname, workplace name, list of attributes Output Ack Description Adds a workplace to the workplaceattributes table URI ME/TELL Mervices/addDomainWorkplace HTTP Methods POST Input example {'iddomain': 1,'idFather': -1,'name': 'test','leaf': 1} Output example { message : } or { error : } Service Name deleteddomainworkplace Input domainname, workplace name, list of attributes Output ack Description Remove a workplace linked to a particular domain URI ME/TELL Mervices/deleteDomainWorkplace HTTP Methods DELETE Input example {'domainid': 1,'idWorkplaceAttributeTaxonomy' : 1 } Output example { message : } or { error : } Service Name Input Output Description URI HTTP Methods Input example Output example adddomain domainname ack Add a domain to the Domain table ME/TELL Mervices/addDomain POST {'domainname' : 'newtest'} { message : } or { error : } TELL ME Consortium Dissemination: Public 57/139

58 Service Name Input Output Description URI HTTP Methods Input example Output example updatedomain domainname ack Updates a domain within the Domain table ME/TELL Mervices/updateDomain POST {'domainid': 1, 'domainname' : 'test'} { message : } or { error : } Administration The content administration component is aimed at managing the TELL ME ontologies/taxonomies a visual way, hence the intended target is the platform administrator / the trainer. The main functionalities envisaged are: Browsing, filtering, search of keyword trees Adding/Deleting nodes For the first prototype the repository has been populated manually through a web-based GUI as shown below. Later on the idea is to develop ad-hoc scripts for fast processing and injection. Figure 30 - Domain Ontologies Administration: managing taxonomies. TELL ME Consortium Dissemination: Public 58/139

59 4.6 Social, Living Lab and Communities TELL ME social is modularised into several components to allow for flexible (including thirdparty!) development. Other than generic social networking sites, the overall functionality of it is geared towards facilitating exchange in and around a wide range of learning objects (see McGreal, 2004, and Quin & Hernandez, 2005, for their discussion sensu latu). As already indicated in section 2.4, the system provides a platform, a backpack, and a developer API to serve different needs in integration with other websites and platforms involved. The platform itself is compartmentalised in modules. Figure 31 - Screenshot of an example community with overlay backpack Most notably, this includes recommender services. This involves running automaton services for preparing data independently of user activity through scheduled calculation via the operating system s crontab. Several automaton services for harvesting content to existing platforms exist (e.g. indexing OpenLearn content, publications from Open Research Online, or for media from YouTube). Moreover, basic analytics modules exist and can be extended further to fit to specific needs in manufacturing environments. The analytics provide basic web reports and allow for export of raw data. Facilities to launch (proprietory) widgets in the backpack are provided and can be flexibly extended. At the time of writing this includes key widgets such as for commenting, tagging, rating, and bookmarking. The existing developer API exposes core functionality as web services. TELL ME Consortium Dissemination: Public 59/139

60 4.6.1 Data Model Figure 5 below provides an overview on the logical structure of the data model underlying TELL ME Social. The model differentiates between users, containers (holding users, e.g. communities), and content objects such as thoughts, comments, or ratings. Users are bound together in containers via memberships. Figure 32 - Logical data model: primary concepts (based on Le, 2013, p.7). All of these entities can have permissions (and they can be tagged, see Figure 32. The entities can be involved in the generation of activity traces, either visible as part of activities or invisible as part of logs, see Figure 33 below. The latter is particularly useful to prevent cluttering of activity streams with repetitive information. TELL ME Consortium Dissemination: Public 60/139

61 Figure 33 - Database logical view (Le, 2013, p.6) Figure 34 depicts the physical database model. The physical model is no longer fully normalised for performance reasons: this allows for some of the queries operating with fewer joins required. Not all table attributes are included in the figure for overview reasons. TELL ME Consortium Dissemination: Public 61/139

62 4.6.2 Services Figure 34 - Database physical view (Le, 2013, p. 9). The following services for querying and storing data are planned. Additional services are already available, but may not be required. Service Name Input Output Description URI Activity (get) Type (getall/getuser), start, page size, stop JSON Retrieves entries from the activity stream, returns JSON wrapped activity stream. /api/v1/activity/... TELL ME Consortium Dissemination: Public 62/139

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