|By Cloud Best Practices Network||
|October 23, 2012 10:00 AM EDT||
Open Data is data that can be freely used, reused and redistributed by anyone – subject only, at the most, to the requirement for attributes and sharealikes (Open Software Service Definition – OSSD). As a consequence, Open Data should create value and might have a positive impact in many different areas such as government (tax money expenditure), health (medical research, hospital acceptance by pathology), quality of life (air breathed in our city, pollution) or might influence public decisions like investments, public economy and expenditure. We are talking about services, so open data are services needed to connect the community with the public bodies. However, the required open data should be part of a design and then integrated, mapped, updated and published in a form, which is easy to use. MaaS is the Open Data driver and enables Open Data portability into the Cloud.
Data models used as a service mainly provide the following topics:
- Implementing and sharing data structure models;
- Verifying data model properties according to private and public cloud requirements;
- Designing and testing new query types. Specific query classes need to support heterogeneous data;
- Designing of the data storage model. The model should enable query processing directly against databases to ensure privacy and secure changes from data updates and review;
- Modeling data to predict usage “early”;
- Portability, a central property when data is shared among fields of application;
- Sharing, redistribution and participation of data among datasets and applications.
As a consequence, the data should be available as a whole and at a reasonable fee, preferably by finding, navigating and downloading over the Cloud. It should also be available in a usable and changeable form. This means modeling Open Data and then using the models to map location and usage, configuration, integration and changes along the Open Data lifecycle.
What is MaaS
Data models can be shared, off-line tested and verified to define data designing requirements, data topology, performance, placement and deployment. This means models themselves can be supplied as a service to allow providers to verify how and where data has to be designed to meet the Cloud service’s requisites: this is MaaS. As a consequence by using MaaS, Open Data designers can verify “on-premise” how and why datasets meet Open Data requirements. With this approach, Open Data models can be tuned on real usage and then mapped “on-premise” to the public body’s service. Further, MaaS inherits all the defined service’s properties and so the data model can be reused, shared and classified for new Open Data design and publication.
Open Data implementation is MaaS (Model as a Service) driven
Open Data is completely supported by data modeling and then MaaS completely supports Open Data. MaaS should be the first practice, helping to tune analysis and Open Data design. Furthermore, data models govern design, deployment, storage, changes, resources allocation, hence MaaS supports:
- Applying Best Practice for Open Data design;
- Classifying Open Data field of application;
- Designing Open Data taxonomy and integration;
- Guiding Open Data implementation;
- Documenting data maturity and evolution by applying DaaS lifecycle.
Accordingly, Maas provides “on-premise” properties supporting Open Data design and publication:
- Analysis – What data are you planning to make open? When working with MaaS, a data model is used to perform data analysis. This means the Open Data designer might return to this step to correct, update and improve the incoming analysis: he always works on an “on-premise” data model. Analysis performed by model helps in identifying data integration and interoperability. The latter assists in choosing what data has to be published and in defining open datasets;
- Design – During the analysis step, the design is carried out too. The design can be changed and traced along the Open Data lifecycle. Remember that with MaaS the model is a service, and the data opened offers the designed service;
- Data security – Data security becomes the key property to rule data access and navigation. MaaS plays a crucial role in data security: in fact, the models contain all the infrastructure properties and include information to classify accesses, classes of users, perimeters and risk mitigation assets. Models are the central way to enable data protection within the Open Data device;
- Participation - Because the goal is “everyone must be able to use Open Data”, participation is comprehensive of people and groups without any discrimination or restriction. Models contain data access rules and accreditations (open licensing).
- Mapping – The MaaS mapping property is important because many people can obtain the data after long navigation and several “bridges” connecting different fields of applications. Looking at this aspect, MaaS helps the Open Data designer to define the best initial “route” between transformation and aggregation linking different areas. Then continually engaging citizens, developers, sector’s expert, managers … helps in modifying the model to better update and scale Open Data contents: the easier it is for outsiders to discover data, the faster new and useful Open Data services will be built.
- Ontology – Defining metadata vocabulary for describing ontologies. Starting from standard naming definition, data models provide grouping and reorganizing vocabulary for further metadata re-use, integration, maintenance, mapping and versioning;
- Portability – Models contain all the properties belonging to data in order that MaaS can enable Open Data service’s portability to the Cloud. The model is portable by definition and it can be generated to different database and infrastructures;
- Availability – The DaaS lifecycle assures structure validation in terms of MaaS accessibility;
- Reuse and distribution – Open Data can include merging with additional datasets belonging to other fields of application (for example, medical research vs. air pollution). Open Data built by MaaS has this advantage. Merging open datasets means merging models by comparing and synchronizing, old and new versions, if needed;
- Change Management and History – Data models are organized in libraries to preserve Open Data changes and history. Changes are traced and maintained to restore, if necessary, model and/or datasets;
- Redesign – Redesigning Open Data, means redesigning the model it belongs to: the model drives the history of the changes;
- Fast BI – Publishing Open Data is an action strictly related to the BI process. Redesigning and publishing Open Data are two automated steps starting from the design of the data model and from its successive updates.
MaaS is the emerging solution for Open Data implementation. Open Data is public and private accessible data, designed to connect the social community with the public bodies. This data should be made available without restriction although it is placed under security and open licensing. In addition, Open Data is always up-to-date and transformation and aggregation have to be simple and time saving for inesperienced users. To achieve these goals, the Open Data service has to be model driven designed and providing data integration, interoperability, mapping, portability, availability, security, distribution, all properties assured by applying MaaS.
 N. Piscopo - ERwin® in the Cloud: How Data Modeling Supports Database as a Service (DaaS) Implementations
 N. Piscopo - CA ERwin® Data Modeler’s Role in the Relational Cloud
 N. Piscopo - DaaS Contract templates: main constraints and examples, in press
 D. Burbank, S. Hoberman - Data Modeling Made Simple with CA ERwin® Data Modeler r8
 N. Piscopo – Best Practices for Moving to the Cloud using Data Models in theDaaS Life Cycle
 N. Piscopo – Using CA ERwin® Data Modeler and Microsoft SQL Azure to Move Data to the Cloud within the DaaS Life Cycle
 The Open Software Service Definition (OSSD) at opendefinition.org
"Matrix is an ambitious open standard and implementation that's set up to break down the fragmentation problems that exist in IP messaging and VoIP communication," explained John Woolf, Technical Evangelist at Matrix, in this SYS-CON.tv interview at @ThingsExpo, held Nov 4–6, 2014, at the Santa Clara Convention Center in Santa Clara, CA.
Oct. 10, 2015 07:00 AM EDT Reads: 5,933
WebRTC has had a real tough three or four years, and so have those working with it. Only a few short years ago, the development world were excited about WebRTC and proclaiming how awesome it was. You might have played with the technology a couple of years ago, only to find the extra infrastructure requirements were painful to implement and poorly documented. This probably left a bitter taste in your mouth, especially when things went wrong.
Oct. 10, 2015 06:00 AM EDT Reads: 818
Nowadays, a large number of sensors and devices are connected to the network. Leading-edge IoT technologies integrate various types of sensor data to create a new value for several business decision scenarios. The transparent cloud is a model of a new IoT emergence service platform. Many service providers store and access various types of sensor data in order to create and find out new business values by integrating such data.
Oct. 10, 2015 04:00 AM EDT Reads: 604
The broad selection of hardware, the rapid evolution of operating systems and the time-to-market for mobile apps has been so rapid that new challenges for developers and engineers arise every day. Security, testing, hosting, and other metrics have to be considered through the process. In his session at Big Data Expo, Walter Maguire, Chief Field Technologist, HP Big Data Group, at Hewlett-Packard, will discuss the challenges faced by developers and a composite Big Data applications builder, focusing on how to help solve the problems that developers are continuously battling.
Oct. 10, 2015 04:00 AM EDT Reads: 523
There are so many tools and techniques for data analytics that even for a data scientist the choices, possible systems, and even the types of data can be daunting. In his session at @ThingsExpo, Chris Harrold, Global CTO for Big Data Solutions for EMC Corporation, will show how to perform a simple, but meaningful analysis of social sentiment data using freely available tools that take only minutes to download and install. Participants will get the download information, scripts, and complete end-to-end walkthrough of the analysis from start to finish. Participants will also be given the pract...
Oct. 10, 2015 03:00 AM EDT Reads: 336
WebRTC: together these advances have created a perfect storm of technologies that are disrupting and transforming classic communications models and ecosystems. In his session at WebRTC Summit, Cary Bran, VP of Innovation and New Ventures at Plantronics and PLT Labs, will provide an overview of this technological shift, including associated business and consumer communications impacts, and opportunities it may enable, complement or entirely transform.
Oct. 10, 2015 02:15 AM EDT Reads: 775
SYS-CON Events announced today that Dyn, the worldwide leader in Internet Performance, will exhibit at SYS-CON's 17th International Cloud Expo®, which will take place on November 3-5, 2015, at the Santa Clara Convention Center in Santa Clara, CA. Dyn is a cloud-based Internet Performance company. Dyn helps companies monitor, control, and optimize online infrastructure for an exceptional end-user experience. Through a world-class network and unrivaled, objective intelligence into Internet conditions, Dyn ensures traffic gets delivered faster, safer, and more reliably than ever.
Oct. 10, 2015 02:00 AM EDT Reads: 663
WebRTC services have already permeated corporate communications in the form of videoconferencing solutions. However, WebRTC has the potential of going beyond and catalyzing a new class of services providing more than calls with capabilities such as mass-scale real-time media broadcasting, enriched and augmented video, person-to-machine and machine-to-machine communications. In his session at @ThingsExpo, Luis Lopez, CEO of Kurento, will introduce the technologies required for implementing these ideas and some early experiments performed in the Kurento open source software community in areas ...
Oct. 10, 2015 01:00 AM EDT Reads: 788
Too often with compelling new technologies market participants become overly enamored with that attractiveness of the technology and neglect underlying business drivers. This tendency, what some call the “newest shiny object syndrome,” is understandable given that virtually all of us are heavily engaged in technology. But it is also mistaken. Without concrete business cases driving its deployment, IoT, like many other technologies before it, will fade into obscurity.
Oct. 10, 2015 12:00 AM EDT Reads: 188
Today air travel is a minefield of delays, hassles and customer disappointment. Airlines struggle to revitalize the experience. GE and M2Mi will demonstrate practical examples of how IoT solutions are helping airlines bring back personalization, reduce trip time and improve reliability. In their session at @ThingsExpo, Shyam Varan Nath, Principal Architect with GE, and Dr. Sarah Cooper, M2Mi's VP Business Development and Engineering, will explore the IoT cloud-based platform technologies driving this change including privacy controls, data transparency and integration of real time context w...
Oct. 9, 2015 10:15 PM EDT Reads: 154
Who are you? How do you introduce yourself? Do you use a name, or do you greet a friend by the last four digits of his social security number? Assuming you don’t, why are we content to associate our identity with 10 random digits assigned by our phone company? Identity is an issue that affects everyone, but as individuals we don’t spend a lot of time thinking about it. In his session at @ThingsExpo, Ben Klang, Founder & President of Mojo Lingo, will discuss the impact of technology on identity. Should we federate, or not? How should identity be secured? Who owns the identity? How is identity ...
Oct. 9, 2015 10:00 PM EDT Reads: 458
The IoT market is on track to hit $7.1 trillion in 2020. The reality is that only a handful of companies are ready for this massive demand. There are a lot of barriers, paint points, traps, and hidden roadblocks. How can we deal with these issues and challenges? The paradigm has changed. Old-style ad-hoc trial-and-error ways will certainly lead you to the dead end. What is mandatory is an overarching and adaptive approach to effectively handle the rapid changes and exponential growth.
Oct. 9, 2015 10:00 PM EDT Reads: 253
The buzz continues for cloud, data analytics and the Internet of Things (IoT) and their collective impact across all industries. But a new conversation is emerging - how do companies use industry disruption and technology enablers to lead in markets undergoing change, uncertainty and ambiguity? Organizations of all sizes need to evolve and transform, often under massive pressure, as industry lines blur and merge and traditional business models are assaulted and turned upside down. In this new data-driven world, marketplaces reign supreme while interoperability, APIs and applications deliver un...
Oct. 9, 2015 08:00 PM EDT Reads: 325
Electric power utilities face relentless pressure on their financial performance, and reducing distribution grid losses is one of the last untapped opportunities to meet their business goals. Combining IoT-enabled sensors and cloud-based data analytics, utilities now are able to find, quantify and reduce losses faster – and with a smaller IT footprint. Solutions exist using Internet-enabled sensors deployed temporarily at strategic locations within the distribution grid to measure actual line loads.
Oct. 9, 2015 06:30 PM EDT Reads: 151
The Internet of Everything is re-shaping technology trends–moving away from “request/response” architecture to an “always-on” Streaming Web where data is in constant motion and secure, reliable communication is an absolute necessity. As more and more THINGS go online, the challenges that developers will need to address will only increase exponentially. In his session at @ThingsExpo, Todd Greene, Founder & CEO of PubNub, will explore the current state of IoT connectivity and review key trends and technology requirements that will drive the Internet of Things from hype to reality.
Oct. 9, 2015 05:30 PM EDT Reads: 131
The Internet of Things (IoT) is growing rapidly by extending current technologies, products and networks. By 2020, Cisco estimates there will be 50 billion connected devices. Gartner has forecast revenues of over $300 billion, just to IoT suppliers. Now is the time to figure out how you’ll make money – not just create innovative products. With hundreds of new products and companies jumping into the IoT fray every month, there’s no shortage of innovation. Despite this, McKinsey/VisionMobile data shows "less than 10 percent of IoT developers are making enough to support a reasonably sized team....
Oct. 9, 2015 04:00 PM EDT Reads: 257
You have your devices and your data, but what about the rest of your Internet of Things story? Two popular classes of technologies that nicely handle the Big Data analytics for Internet of Things are Apache Hadoop and NoSQL. Hadoop is designed for parallelizing analytical work across many servers and is ideal for the massive data volumes you create with IoT devices. NoSQL databases such as Apache HBase are ideal for storing and retrieving IoT data as “time series data.”
Oct. 9, 2015 03:45 PM EDT Reads: 515
Today’s connected world is moving from devices towards things, what this means is that by using increasingly low cost sensors embedded in devices we can create many new use cases. These span across use cases in cities, vehicles, home, offices, factories, retail environments, worksites, health, logistics, and health. These use cases rely on ubiquitous connectivity and generate massive amounts of data at scale. These technologies enable new business opportunities, ways to optimize and automate, along with new ways to engage with users.
Oct. 9, 2015 02:00 PM EDT Reads: 197
The IoT is upon us, but today’s databases, built on 30-year-old math, require multiple platforms to create a single solution. Data demands of the IoT require Big Data systems that can handle ingest, transactions and analytics concurrently adapting to varied situations as they occur, with speed at scale. In his session at @ThingsExpo, Chad Jones, chief strategy officer at Deep Information Sciences, will look differently at IoT data so enterprises can fully leverage their IoT potential. He’ll share tips on how to speed up business initiatives, harness Big Data and remain one step ahead by apply...
Oct. 9, 2015 01:45 PM EDT Reads: 571
There will be 20 billion IoT devices connected to the Internet soon. What if we could control these devices with our voice, mind, or gestures? What if we could teach these devices how to talk to each other? What if these devices could learn how to interact with us (and each other) to make our lives better? What if Jarvis was real? How can I gain these super powers? In his session at 17th Cloud Expo, Chris Matthieu, co-founder and CTO of Octoblu, will show you!
Oct. 9, 2015 01:15 PM EDT