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28.04.2016
Connectivity and digital technologies are fundamentally changing the way we live, work, learn, socialise, and connect.
At the recent OECD Forum 2014,  the Sharing Economy was the focus of one of the main panel debates. April Rinne, Sharing Economy and Shareable Cities Expert at Collaborative Consumption, a comprehensive online resource and network,   reported a knowledge gap.
Frederic Mazzella is CEO of successful ride sharing company BlaBlaCar, that allows drivers to find paying passengers on long distance trips.  He described the model that his company has developed to build trust between strangers, by using online profiles, ratings and active moderation of the web platform. The sharing economy is creating new business models based on trust and access rather than ownership.
If you have interesting examples to show, we would like to hear about them.  URBACT- which itself is a sharing programme, in the sense of sharing knowledge between cities- will continue to present new cases, in order to support  understanding of the potential benefits of urban collaborative consumption. Nesta, together with Collaborative Consumption,  is also conducting a survey entitled Taking stock of the European collaborative economy: surveying those operating in it. I’m looking to find out about more about who uses collaborative sharing services such as airbnb or zipcar etc., what trends there are, what are the motivations to use these services, how they can be improved and finally how companies should look to create market in which their products can be shared.
Also, if anyone has any suggestions or feedback (constructive please) then that would be great. URBACT is a European exchange and learning programme promoting sustainable urban development. This page describes technical details of the legacy GO database; if you are simply interested in browsing the database you may wish to proceed straight to AmiGO, the web interface for searching and browsing GO data. The GO database is generated from the most recent version of the ontology and the annotation files contributed by members of the GO Consortium. Those familiar with MySQL can use GOOSE, the GO Online SQL Environment, a web interface for running SQL queries against the GO database. There are several sites that provide mirrors of the GO database accessible through a MySQL client (see the SQL section below for more on SQL queries of the GO database). The EBI mirror is of the full GO database: ontology data and all associations, both manual and electronic. The GO database server and mirrors are a shared resource and thus we require data mining to be performed in a manner that allows others to utilize this resource at the same time. The GO database can be downloaded as a MySQL database dump and reconstituted on any system where MySQL is running.
You can create your own instance of a GO database, either by building one de novo, or by augmenting an existing build, e.g. To build a GO database from scratch, you will need a MySQL server, and the GO database SQL source, found in the directory sql of the go-dev software kit. To load ontologies or data from OBO files or gene association files, you will need to install go-perl and go-db-perl (found in go-dev) and use the load scripts there.
You can query the GO database using the SQL query language; either download and install the GO MySQL dump to query your local copy, or connect to one of the GO database mirror nodes. If you are unsure as to how to construct your query, the best place to start is the example queries page on the GO wiki. You can connect to a local or remote MySQL installation using the API provided by go-perl and go-db-perl, part of the go-dev software set. The GHOUL (GO Hibernate Object Layer) library provides an API for accessing GO through java calls and HQL queries. The code is avaliable from the GO sourceforge project in the svn repository can be browsed here. A relational schema specifies a collection of table definitions, providing structure for the data housed in the database instance.
The database structure can also be seen in the entity-relationship diagram shown below; please note that the database schema used is dated June 2009.
As a convention, all tables in the schema use the column named id as the primary key, and foreign key columns are all named reference_id. The terms constituting the nodes in an ontology graph represent the kinds of entities that exist within the domain of that ontology.
When performing ontology-oriented queries, it is often necessary to perform some kind of graph traversal.


This kind of query is possible with the GO database because we precompute the path from every node to all of its ancestors.
In particular, we calculate the reflexive transitive closure, which means that every term is related to itself (the distance between the terms is zero). Note that we can use the same table to query for descendants as well as ancestors; it is simply a matter of switching around term1 and term2 in the graph_path query constraints.
The diagram below shows an example of the reflexive transitive closure of cellular pigment accumulation and its ancestors.
If you have specific questions, either technical or content-related, regarding the database, please contact the GO helpdesk. The GO software group mailing list often hosts discussions of the database and related software. The schema already supports logical (complete) definitions via the complete relation qualifier, although these are not populated in the public GO database as the cross-products are still experiemntal. The GO schema is the predecessor of the ontology-based components of other bioinformatics schemas, including Chado, BioSQL and OBD. The Gene Ontology Consortium is supported by a P41 grant from the National Human Genome Research Institute (NHGRI) [grant 5U41HG002273-14].
Donald Bell is an IT architect for IBM Rational software, where he works with clients to define and adopt effective software delivery practices and tools.
The first time you sign in to developerWorks, a profile is created for you, so you need to choose a display name. Keep up with the best and latest technical info to help you tackle your development challenges. Part of this revolution has involved the rise of peer-to-peer services, allowing people to share everything from their cars and homes to their talent and time. It holds the potential to exploit valuable resources more efficiently and more sustainably, a constant challenge for many cities, especially within the current austerity framework. Experts from around the globe debated its future as an innovative approach to better sustainability.
BlaBlaCar has conducted surveys on trust levels, and Frederic believes these studies show that entering ‘sharing mode’ encourages positive behaviours.
We would like to know how cities are supporting such initiatives, what results shared economy approaches are achieving in the most advanced cities, and how results are being measured. It would be really great to get as many results as possible so that the results actually mean something. As well as allowing users to search, browse, and download terms and annotations, AmiGO has analysis tools for further data processing. Any activity that mines the GO database using AmiGO or GOOSE must be controlled so that only one request is issued at a time. The data is also available as SQL statements for use with other database management systems; unfortunately we can only supply minimal support for non-MySQL databases.
Please note that this method also creates a time stamp database with a suffix identical to the database name that you are loading.
The Advanced Query provides a reasonably flexible way to query the database, but far more powerful queries can be executed using SQL.
The API can be used to get terms, subgraphs and annotated gene products, as well as to perform more complex analyses. The schema for the GO database consists of tables for storing the terms and structure (as a graph) of the GO ontologies, along with gene product and annotation data. They are meaningless, not consistent between builds, and bear no correspondence to public identifiers such as GO:0008050.
The terms are nodes in the graph, and the relationships between them are arcs (see the ontology structure documentation for more information). This allows us to reuse the same schema structures, and potentially allows us to have hierarchies of relations, which may be required in the future. It is possible to use the term2term table to iterate through the graph, but this requires multiple database calls as MySQL does not support transitive operators such as Oracle's CONNECT BY.
In practical terms, this makes it easier to write queries such as "find all DNA binding genes", because such queries should return genes annotated directly to DNA binding, as well as to its children.


New list members must be approved before joining, but all conversations on the list are archived and can be viewed without a subscription. The Gene Ontology Consortium would like to acknowledge the assistance of many more people than can be listed here. Your display name must be unique in the developerWorks community and should not be your email address for privacy reasons. There is nothing new in swapping and sharing, and in fact city life has always facilitated the sharing of space, infrastructure, leisure and culture. It is no coincidence that many of the recent sharing economy models really took off between 2008 and 2012 in the aftermath of the economic crisis.
She stressed the need for cities to connect, to learn, to share practice and gain insights from each other, in much the same way that URBACT networks do.  April cited Seoul as the best international role model, in part due to the way it uses the sharing concept as a key principle in urban planning. Lessons from sharing services could be useful for policies aiming to encourage behaviour change in other policy areas such as energy efficiency and mobility.
The sharing economy creates value from existing assets, so is a jolt to conventional economics. Please see the annotation policies on avoiding redundancy for further information on authoritative database groups. The go-graph module is for housing the ontology; the central tables are term and term2term.
This means you should always consult the documentation here, rather than relying on the MySQL DESCRIBE TABLES command or the CREATE TABLE commands in the database dump.
Most implementations of SQL do not support the kind of recursive querying required to answer queries such as "find all DNA binding genes". You can see some examples of these in the form of unpopulated tables and columns in the database.
But with increasing connectivity this activity is moving to a different level and the so called sharing economy appears to be taking off. Of perhaps equal interest is evidence that the experience of sharing builds trust and community cohesion. The South Korean megacity has the advantages of a well-developed tech infrastructure, widespread public wifi, and high levels of digital literacy. NetServe gives you the power to host your website from home, and gives you access to a wealth of tools that allow you to Upload and Download from your computer remotely. Annotations are stored in the go-association module; the main tables are association and gene_product. The GO database schema page allows you to traverse primary and foreign key links via internal html page links. At a time when the public’s trust in government and institutions is damaged, perhaps city sponsored sharing initiatives can play a role in galvanising citizen involvement and improving social capital. The Sharing City project launched in Seoul aims to expand sharing infrastructure, promote existing sharing enterprises, incubate sharing economy start-ups, utilise idle public resources, and provide more access to data and digital works. Does AirBnB, for instance, bring new local economic benefit, as it claims, to neighbourhoods outside of city centres, where many hosts offer space? Also features WebDAV that you can use with other WebDAV enabled products such as Microsoft Office and Adobe to read add write your files directly on your server.
An extra line disconnects thoughts, length accentuates the connection.Curved lines give visual rhythm and variety and so are easier to remember, more pleasant to draw and less boring to look at. The Mind Map allows you to catch and keep whatever ‘thought ball’ is thrown by your brain.8. Have fun!Add a little humour, exaggeration or absurdity wherever you can.Your brain will delight in getting the maximum use and enjoyment from this process and will therefore learn faster, recall more effectively and think more clearly.



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