An Evaluation of Platforms for Open Government Data
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Odata Services Company
PUBLIC 2021-03-09 OData Services company. All rights reserved. All rights company. affiliate THE BEST RUN 2021 SAP SE or an SAP SE or an SAP SAP 2021 © Content 1 SAP Cloud for Customer OData API..............................................4 2 New Features.............................................................. 13 2.1 What's New in OData API v2 Reference.............................................13 2.2 Add Public Solution Model (PSM) Fields to Standard OData Services........................15 2.3 Transport Custom OData Services with Transport Management............................16 2.4 Compatibility Mode for READ Operations........................................... 16 2.5 Support for User-Friendly IDs in Standard OData Services................................16 2.6 Constant Values to Function Imports...............................................17 3 OData API Reference.........................................................18 3.1 OData API v2 Reference........................................................18 3.2 OData API v1 Reference (Deprecated)..............................................20 Account Contact Relationship.................................................21 Account EntityType........................................................22 Appointment Entity Type....................................................40 BusinessPartner Entity Type..................................................46 CodeList Entity Type....................................................... 47 Contextual CodeList Entity Type...............................................48 -
Pyslet Documentation Release 0.6.20160201
Pyslet Documentation Release 0.6.20160201 Steve Lay February 02, 2016 Contents 1 What’s New? 1 2 Compatibility 7 3 IMS Global Learning Consortium Specifications 13 4 The Open Data Protocol (OData) 101 5 Hypertext Transfer Protocol (RFC2616) 207 6 Other Supporting Standards 247 7 Welcome to Pyslet 357 Python Module Index 359 i ii CHAPTER 1 What’s New? As part of moving towards PEP-8 compliance a number of name changes are being made to methods and class at- tributes with each release. There is a module, pyslet.pep8, which contains a compatibility class for remapping missing class attribute names to their new forms and generating deprecation warnings, run your code with “python -Wd” to force these warnings to appear. As Pyslet makes the transition to Python 3 some of the old names will go away completely. It is still possible that some previously documented names could now fail (module level functions, function arguments, etc.) but I’ve tried to include wrappers or aliases so please raise an issue on Github if you discover a bug caused by the renaming. I’ll restore any missing old-style names to improve backwards compatibility on request. Finally, in some cases you are encouraged to derive classes from those defined by Pyslet and to override default method implementations. If you have done this using old-style names you will have to update your method names to prevent ambiguity. I have added code to automatically detect most problems and force fatal errors at runtime on construction, the error messages should explain which methods need to be renamed. -
ISO/IEC JTC 1 Information Technology
ISO/IEC JTC 1 Information technology Big data Preliminary Report 2014 Our vision Our process To be the world’s leading provider of high Our standards are developed by experts quality, globally relevant International all over the world who work on a Standards through its members and volunteer or part-time basis. We sell stakeholders. International Standards to recover the costs of organizing this process and Our mission making standards widely available. ISO develops high quality voluntary Please respect our licensing terms and International Standards that facilitate copyright to ensure this system remains international exchange of goods and independent. services, support sustainable and equitable economic growth, promote If you would like to contribute to the innovation and protect health, safety development of ISO standards, please and the environment. contact the ISO Member Body in your country: www.iso.org/iso/home/about/iso_ members.htm This document has been prepared by: Copyright protected document ISO/IEC JTC 1, Information technology All rights reserved. Unless otherwise Cover photo credit: ISO/CS, 2015 be reproduced or utilized otherwise in specified,any form noor partby anyof this means, publication electronic may or mechanical, including photocopy, or posting on the internet or intranet, without prior permission. Permission can be requested from either ISO at the address below or ISO’s member body in the country of the requester: © ISO 2015, Published in Switzerland Case postale 56 • CH-1211 Geneva 20 Tel.ISO copyright+41 22 -
Haris Kurtagic, SL-King Jason Birch, City of Nanaimo Geoff Zeiss, Autodesk Tim Berners-Lee, in Government Data Design Issues, Proposes
Haris Kurtagic, SL-King Jason Birch, City of Nanaimo Geoff Zeiss, Autodesk Tim Berners-Lee, in Government Data Design Issues, proposes ○ Geodata on the web in raw form. ○ Raw geodata must be searchable How do you find raw geospatial data ? Data Catalogs Wouldn’t it be nice if… And see.. Searchable Raw Geospatial Data www.georest.org Open Data Protocol “The Open Data Protocol (OData) is a Web protocol for querying and updating data that provides a way to unlock your data and free it from silos that exist in applications today.” www.odata.org ODATA HTTP Atom AtomPUB JSON HTTP://.../vancouver/libraries <feed xmlns=http://www.w3.org/2005/Atom … > <title type="text">libraries</title> <id>http://…/vancouver/libraries(10)</id> <title type="text"></title> <entry> <content type="application/xml"> <m:properties> <d:library_name>Britannia</d:library_name> <d:latitude m:type="Edm.Double">49.2756486</d:latitude> <d:longitude m:type="Edm.Double">-123.0737717</d:longitude> <d:address>1661 Napier St</d:address> </m:properties> …..</entry> <entry>…</entry></feed> HTTP://.../vancouver/libraries ?$format=JSON {"d":[{"library_name":"Britannia","latitude":" 49.2756486","longitude":"- 123.0737717","address":"1661 Napier St"} , {..}] } HTTP Header accept: application/json OData Example Live OData Service from Vancouver OData Producers SharePoint 2010, SQL Azure, IBM WebSphere, … GeoREST OData Live Services Netflix, Open Goverment Data Initiative (OGDI), Stack Overflow, Vancouver, Edmonton, … City of Nanaimo OData Consumers Browsers, Odata Explorer, Excel 2010,… -
The Construction of Open Data Portal Using DKAN for Integrate to Multiple Japanese Local Government Open Data *Toshikazu Seto 1 , Yoshihide Sekimoto 2
Free and Open Source Software for Geospatial (FOSS4G) Conference Proceedings Volume 16 Bonn, Germany Article 17 2016 The onsC truction of Open Data Portal using DKAN for nI tegrate to Multiple Japanese Local Government Open Data Toshikazu Seto Center for Spatial Information Science, the University of Tokyo Yoshihide Sekimoto Institute of Industrial Science, the University of Tokyo Follow this and additional works at: https://scholarworks.umass.edu/foss4g Part of the Computer and Systems Architecture Commons, and the Geographic Information Sciences Commons Recommended Citation Seto, Toshikazu and Sekimoto, Yoshihide (2016) "The onC struction of Open Data Portal using DKAN for Integrate to Multiple Japanese Local Government Open Data," Free and Open Source Software for Geospatial (FOSS4G) Conference Proceedings: Vol. 16 , Article 17. DOI: https://doi.org/10.7275/R5W957B0 Available at: https://scholarworks.umass.edu/foss4g/vol16/iss1/17 This Poster is brought to you for free and open access by ScholarWorks@UMass Amherst. It has been accepted for inclusion in Free and Open Source Software for Geospatial (FOSS4G) Conference Proceedings by an authorized editor of ScholarWorks@UMass Amherst. For more information, please contact [email protected]. Center for Spatial Information Science at The University of Tokyo The Construction of Open Data Portal using DKAN for Integrate to Multiple Japanese Local Government Open Data *Toshikazu Seto 1 , Yoshihide Sekimoto 2 *1: Center for Spatial Information Science, the University of Tokyo, 4-6-1, Komaba, Meguro-ku, Tokyo 153-8505, Japan, 153-8505 Email: [email protected] 2: Institute of Industrial Science, the University of Tokyo 3. -
SAP Analytics Cloud, Analytics Designer Developer Handbook
SAP Analytics Cloud, analytics designer Developer Handbook Document Version: 5.1 – 2020-04-06 Table of Contents 1 Table of Contents Table of Contents ......................................................................................................................... 1 Figures .......................................................................................................................................... 7 1 About Analytics Designer .............................................................................................10 1.1 What Is an Analytic Application? .....................................................................................10 1.2 What Is Analytics Designer? ............................................................................................10 1.3 What Can You Do with Analytic Applications That You Can’t Do with Stories? ..............10 1.4 How Are Stories and Analytic Applications Related to Each Other? ...............................10 1.5 Why Do We Need Both Stories and Analytic Applications? ............................................11 1.6 What Is the Typical Workflow in Creating an Analytic Application? .................................11 1.7 What Are Typical Analytic Applications? .........................................................................12 1.8 How Does Scripting Work in Analytic Applications? ........................................................12 1.9 What’s the Scripting Language for Analytic Applications? ..............................................13 2 Getting -
Catalogue Open Data Protocol (Odata API) User Guide
Catalogue Open Data Protocol (OData API) User Guide Content 1. Introduction .......................................................................................................................................... 3 1.1. Purpose......................................................................................................................... 3 1.2. Change register ............................................................................................................. 3 1.3. Structure of the document ............................................................................................. 3 1.4. Acronyms ...................................................................................................................... 4 1.5. Reference Documents ................................................................................................... 4 2. Open Data Protocol overview ............................................................................................................. 6 2.1. Entity Data Model concept ............................................................................................ 6 Entity Type ..................................................................................................................... 7 Entity Set ....................................................................................................................... 7 3. ONDA OData Entity Data Model ......................................................................................................... 8 3.1. ONDA Entity -
Linkedpipes DCAT-AP Viewer: a Native DCAT-AP Data Catalog⋆
LinkedPipes DCAT-AP Viewer: A Native DCAT-AP Data Catalog? Jakub Klímek[0000−0001−7234−3051] and Petr Škoda[0000−0002−2732−9370] Charles University, Faculty of Mathematics and Physics Malostranské nám. 25, 118 00 Praha 1, Czech Republic [email protected] Abstract. In this demonstration we present LinkedPipes DCAT-AP Viewer (LP-DAV), a data catalog built to support DCAT-AP, the Eu- ropean standard for representation of metadata in data portals, and an application profile of the DCAT W3C Recommendation. We present its architecture and data loading process and on the example of the Czech National Open Data portal we show its main advantages compared to other data catalog solutions such as CKAN. These include the support for Named Authority Lists in EU Vocabularies (EU NALs), controlled vocabularies mandatory in DCAT-AP, and the support for bulk loading of DCAT-AP RDF dumps using LinkedPipes ETL. Keywords: catalog · DCAT · DCAT-AP · linked data 1 Introduction Currently, two worlds exist in the area of data catalogs on the web. In the first one there are a few well established data catalog implementations such as CKAN or DKAN, each with their data model and a JSON-based API for accessing and writing the metadata. In the second one, there is the Linked Data and RDF based DCAT W3C Recommendation [1] and its application profiles, such as the European DCAT-AP1, which are de facto standards for representation of metadata in data portals. The problem is that CKAN has been around for a while now, and is better developed, whereas DCAT is still quite new, with insufficient tooling support, nevertheless it is the standard. -
Deliverable D7.5: Standards and Methodologies Big Data Guidance
Project acronym: BYTE Project title: Big data roadmap and cross-disciplinarY community for addressing socieTal Externalities Grant number: 619551 Programme: Seventh Framework Programme for ICT Objective: ICT-2013.4.2 Scalable data analytics Contract type: Co-ordination and Support Action Start date of project: 01 March 2014 Duration: 36 months Website: www.byte-project.eu Deliverable D7.5: Standards and methodologies big data guidance Author(s): Jarl Magnusson, DNV GL AS Erik Stensrud, DNV GL AS Tore Hartvigsen, DNV GL AS Lorenzo Bigagli, National Research Council of Italy Dissemination level: Public Deliverable type: Final Version: 1.1 Submission date: 26 July 2017 Table of Contents Preface ......................................................................................................................................... 3 Task 7.5 Description ............................................................................................................... 3 Executive summary ..................................................................................................................... 4 1 Introduction ......................................................................................................................... 5 2 Big Data Standards Organizations ...................................................................................... 6 3 Big Data Standards ............................................................................................................. 8 4 Big Data Quality Standards ............................................................................................. -
Blackbaud CRM Query and Export Guide
Query and Export Guide 03/23/2016 Blackbaud CRM 4.0 Query and Export US ©2016 Blackbaud, Inc. This publication, or any part thereof, may not be reproduced or transmitted in any form or by any means, electronic, or mechanical, including photocopying, recording, storage in an information retrieval system, or otherwise, without the prior written permission of Blackbaud, Inc. The information in this manual has been carefully checked and is believed to be accurate. Blackbaud, Inc., assumes no responsibility for any inaccuracies, errors, or omissions in this manual. In no event will Blackbaud, Inc., be liable for direct, indirect, special, incidental, or consequential damages resulting from any defect or omission in this manual, even if advised of the possibility of damages. In the interest of continuing product development, Blackbaud, Inc., reserves the right to make improvements in this manual and the products it describes at any time, without notice or obligation. All Blackbaud product names appearing herein are trademarks or registered trademarks of Blackbaud, Inc. All other products and company names mentioned herein are trademarks of their respective holder. QueryExport-2016 Contents Getting Started with Query 4 Query: A Guided Tour 4 Common Query Fields 20 Common Query Filters 22 Query 25 Information Library 27 Ad-Hoc Queries 27 Smart Queries 58 Selections 71 Copy an Existing Query 74 Export Queries 74 Browse Query Results 75 View Query Results 75 Organize Queries 75 Open Data Protocol (OData) 79 Export 82 Exports 82 Export Definitions 86 Export Process Status Page 100 Import Selections 106 Import Selections 106 Import Selection Process Status Page 110 chapter 1 Getting Started with Query Query: A Guided Tour 4 Common Query Fields 20 Constituent Query Fields 20 Revenue Query Fields 21 Registrant Query Fields 22 Common Query Filters 22 Constituent Query Filters 22 Revenue Query Filters 23 Registrant Query Filters 23 Query is a powerful tool you can use to help filter and group records. -
Denodo Odata 2.0 Service User Manual
Denodo OData 2.0 Service User Manual Revision 20200508 NOTE This document is confidential and proprietary of Denodo Technologies. No part of this document may be reproduced in any form by any means without prior written authorization of Denodo Technologies. Copyright © 2021 Denodo Technologies Proprietary and Confidential Denodo OData 2.0 Service User Manual 20200508 2 of 34 CONTENTS 1 OVERVIEW........................................................................5 2 INSTALLATION..................................................................6 2.1 DEPLOYING INTO THE DENODO EMBEDDED WEB CONTAINER............8 2.2 CONFIGURING JNDI RESOURCES IN APACHE TOMCAT......................10 3 VIRTUAL DATAPORT PRIVILEGE REQUIREMENTS.................12 4 FEATURES.......................................................................13 5 SERVING METADATA........................................................14 6 QUERYING DATA: THE BASICS..........................................16 6.1 QUERYING COLLECTIONS..............................................................16 6.2 OBTAINING ITEMS BY PRIMARY KEY..............................................16 6.3 ACCESSING INDIVIDUAL PROPERTIES............................................16 6.4 ACCESSING INDIVIDUAL PROPERTY VALUES...................................17 6.5 ACCESSING COMPLEX PROPERTIES...............................................17 6.6 COUNTING ELEMENTS IN A COLLECTION: $COUNT..........................18 6.7 ESTABLISHING RESPONSE FORMAT...............................................18 7 NAVIGATING -
The Envidat Concept for an Institutional Environmental Data
I Iosifescu Enescu, I, et al. 2018. The EnviDat Concept for an CODATA '$7$6&,(1&( S Institutional Environmental Data Portal. Data Science Journal, U -2851$/ 17: 28, pp. 1–17. DOI: https://doi.org/10.5334/dsj-2018-028 RESEARCH PAPER The EnviDat Concept for an Institutional Environmental Data Portal Ionuț Iosifescu Enescu1, Gian-Kasper Plattner1, Lucia Espona Pernas1, Dominik Haas-Artho1, Sandro Bischof1, Michael Lehning2,3 and Konrad Steffen1,3,4 1 Swiss Federal Institute for Forest, Snow and Landscape WSL, CH 2 WSL Institute for Snow and Avalanche Research SLF, CH 3 School of Architecture, Civil and Environmental Engineering, EPFL, CH 4 ETH Zurich, CH Corresponding author: Ionuț Iosifescu Enescu ([email protected]) EnviDat is the environmental data portal developed by the Swiss Federal Institute for Forest, Snow and Landscape Research WSL. The strategic initiative EnviDat highlights the importance WSL lays on Research Data Management (RDM) at the institutional level and demonstrates the commitment to accessible research data in order to advance environmental science. EnviDat focuses on registering and publishing environmental data sets and provides unified and efficient access to the WSL’s comprehensive reservoir of environmental monitoring and research data. Research data management is organized in a decentralized manner where the responsibility to curate research data remains with the experts and the original data providers. EnviDat supports data producers and data users in registration, documentation, storage, publi- cation, search and retrieval of a wide range of heterogeneous data sets from the environmental domain. Innovative features include (i) a flexible, three-layer metadata schema, (ii) an additive data discovery model that considers spatial data and (iii) a DataCRediT mechanism designed for specifying data authorship.