VI-SEEM. for Digital Cultural Heritage. Panayiotis Charalambous Associate Research Scientist CaSToRC The Cyprus Institute
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1 SIMDAS AND VI-SEEM WORKSHOP ON DATA MANAGEMENT AND SEMANTIC STRUCTURES FOR CROSS- DISCIPLINARY RESEARCH IN THE SEEM REGION VI-SEEM for Digital Cultural Heritage Panayiotis Charalambous Associate Research Scientist CaSToRC The Cyprus Institute
2 is a research data management system. Supports many data format and multiple research domains. Extension points: pre-processing, processing previewing
3 What s so special about it? Processing and Management of Heterogeneous Data Extensibility
4 DCH Data Courtesy of Direct Dimensions Polynomial Texture Maps (a.k.a. Reflectance Transformation Imaging) 3D Models Documents Images
5 Deployment architecture Core Core
6 MANAGING USERS AND DATA
7 Users Users can have different roles Viewers: can view and download data Editors = viewers + manage (add, remove) data in datasets, collections and spaces Administrators = editors + can manage users and roles Custom types of users can be defined
8 Data Management
9 DATA PROCESSING & EXTENSIBILITY
10 Data Processing How? Web Interface RESTful API Web Browser Web Browser 2 Datasets / File Levels When uploaded, data are: 1. Offloaded to extraction services. 2. Information and data are extracted based on data type. 3. The metadata are then written in the repository. 1.Thumbnail 2. Metadata 2000x5000 pixels RGBA Canon Camera etc 3. Face Recognition None 4. OCR None Image Preview (Python) Image Metadata (Java) Face Recognition (C++) RESTful API Extraction Bus OCR (C++) Mesh Simplification (Python) Interfaces Extractors
11 REST API
12 Extraction Services Documents: Office Formats (doc, ppt, ): Preview PDF: Preview, OCR (currently only for Latin alphabet) 3D Meshes: Previewing, Streaming of large meshes Polynomial Texture Maps: Thumbnails, Metadata, Maps, 3D Audio: Playback, Thumbnail Images: Preview, Metadata, OCR Video: Playback, Thumbnail Utilities: File digests
13 Extractors: Images
14 Extractors: Audio
15 Extractors: Video
16 Extractors: PTM
17 Extraction Services: BVL Banatica Virtual Library: Making old prints widely available and machine-readable. Metadata for 1000 books scanned books Implementation: Python Parses and imports all metadata Tags are also created and associated with data All documents are then processed by the document extractors
18 Extraction Services 3Dinv Three-dimensional (3-D) inversion of surface Electrical Resistivity Tomography (ERT) data to automatically determine a 3-D resistivity subsurface model Implementation: Forth researchers provided binaries of 3DInv Interface for running 3DInv agreed beforehand Input: zip file with all necessary files Output: zip file with results
19 Extraction Services AutoGr Automatic Image Georeferencing Implementation: Forth researchers provided code Interface for running AutoGr agreed beforehand Input: zip file with all necessary files Output: zip file with results
20 Extraction Services 3D Meshes Up to now, clowder had basic 3D support for textureless meshes Implementation: Python Supports both meshes and point clouds Meshlab (headless): converts meshes to.ply format (including textures) Nexus converts.ply files to streaming binary meshes which are used for previewing Previewer (JS) allows for: viewing, measuring and slicing of meshes.
21 3D Previewing in
22 THE FUTURE
23 Vi-SEEM DCH Repository
24 Code Docker files, code and compilation scripts will be provided
25 Docker and Besides code, we share Docker containers for everything: One Docker container per extraction service. One Docker container for the platform itself. New Data / Metadata Image Extractor 1 (Python) Web Browser Image Image RESTful API Image Web Browser 2 Extraction Bus PDF New File / Dataset 3D Model Interfaces Complete setup in a few minutes! Image Extractor 2 (Java) Image Extractor 3 (C++) PDF Extractor 1 (C++) Mesh Extractor 1 (Python) Extractors
26 The immediate future New RTI Viewer Better 3D File support Wide 3D File Formats JS based viewer Measurements Cross Sections
27 The future More extensions and management capabilities is being used in proposals NCSA has in the core of many projects PASCL: as platform for: crowd data management automatic crowd simulation crowd analysis
28 Thank You
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