Transcript Open Government Data in Indonesia

Open Government Data in
Indonesia Regional Government
Managing Government Data Frameworks
Suhardi
Cyber Security Center
School of Electrical Engineering
Institute of Technology Bandung
Email: [email protected]
“Open Government” Acts in Indonesia
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National Constitution (article 28F)
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Act 14/2008 on Public Information Transparency
Every person has the right to communicate and to obtain
information for personal development and his/her social
environment, and has also the right to seek, obtain, posses and
store information using any type of available channel
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Guarantee citizens right to be informed about plan of public
policy, public policy program, and process of public policy
decision making, and the reason behind the decission
Encourage public participation in the public policy decision
making process
Increase active public participation in the public policy
decision making process
Create good governance which transparent, effective and
efficient, accountable and responsible…"
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Implications
Closed
Open
Permitted
Restricted
 “...(Public institution) must develop information and
documentation system to manage public information
efficiently... (article 13).
 “...must assign Information and Documentation
Management Officer (article 13)
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Open Government*
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Government should be transparent.
Transparency promotes accountability and provides
information for citizens about what their Government
is doing.
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Government should be participatory.
Public engagement enhances the Government’s
effectiveness and improves the quality of its
decisions.
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Government should be collaborative.
Collaboration actively engages citizens in the work of
their Government.
*OBAMA, Barrack, Transparency and Open Government, Memorandum for the Heads of
Executive Departments And Agencies, January 21, 2009
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Open Data*
Open data is data that can be freely used,
re-used and redistributed by anyone
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Availability and Access:
the data must be available as a whole, preferably by
downloading over the internet. The data must also be
available in a convenient and modifiable form.
Re-use and Redistribution:
the data must be provided under terms that permit
re-use and redistribution including the intermixing
with other datasets.
Universal Participation:
everyone must be able to use, re-use and redistribute
– with no discrimination against persons or groups.
*Open Data Handbook Documentation Release 1.0.0, Open Knowledge Foundation, 2012
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Principles for Improving Federal Transparency
 Build end-to-end digital processes:
Automate transfer of data between systems
 Build once, use often:
Share platforms to foster collaboration.
 Tap into golden sources of data:
Pull data directly from authoritative sources
 Machine-readable data and third party applications
Machine-readable data allow public use of government information.
 Use common data standards:
Develop and use uniform, unique identifiers and data standards
 Validate data up front:
Correct errors during collection and at the point of entry
 Release data in real time and preserve for future use:
Release data as quickly as feasible to enhance its relevance and utility
 Reduce burden:
Collect data once and use it repeatedly.
 Protect privacy and security:
Safeguard the release of information to protect security.
 Incorporate user feedback:
Incorporate user feedback to help identify high-value data sets
*Vivek Kundra (White House CIO), 2011
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World’s Open Data Initiative
Open Data: Barometer 2013 Global Report, Open Data Institute, 2013
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Open Data Barometer Index
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Data Availability & Openess
Open Data Barometer 2013 Global Report, Open Data Institute, 2013
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Open Government Data in Indonesia
 OGD discussed at government institutions (the Ministry
of Finance, the National Statistics Bureau)
 President's Delivery Unit for Development Monitoring
and Oversight (UKP4) in charge of coordinating the
national Open Government initiative
 Currently, a series of initiatives are being promoted by
the Indonesian government under the national Open
Government programme
 BPS has recently become one of the first national
government institutions to announce plans for an OGD
program
Open Government Data Readiness Assessment Indonesia, WWW Foundation, June 2013
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 “...there is no common framework
(formats, standards and procedures ) that
is followed across government institutions
on government internal data processing”
 “..departments had considerable
quantities of not well-shared data sets”
Open Government Data Readiness Assessment Indonesia, WWW Foundation, June 2013
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Relevant Technological Concepts
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Data Management
Data Warehouse
Data Minning
Big Data Analysis
Linked Data
Unstructured Data
Data Intregration
Semantic Web (?)
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Managing Unstructured Data
 Unstructured data refers to the difficulty of applying IT
to dissect data (vs. databases)
 The challenge is in extracting the latent structure in
content (Metadata).
 Metadata allows: (1) Information visualization, (2)
intelligent data routing, (3) text mining
 Generating metadata:
1. Automatic Categorization
Assign documents to one or more categories (linguistic
analysis, statistical inference, machine learning, and rulebased processing)
2. Information Extraction
Extract elements of information from content based on
linguistic analysis and scanning for patterns under two level of
extraction: (1) Entity Extraction – for identifying, (2) Fact
Extraction – for connecting and contextualize
Ramana Rao, From Unstructured Data to Actionable Intelligence, 2003
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Data Integration Concept
 Data integration provide a uniform query interface to a
multitude of data sources, interact with each one in
isolation and manually combine results)
 A data integration started with identifying the data
sources that will participate in the application, and
then building a mediated schema (often called a
virtual schema)
 To answer queries the system needs mappings that
describe the semantic relationships between the
mediated schema and the schemas of the sources
(Semantic mappings).
 Query processing would begin by reformulating a query
posed over the virtual schema into queries over the
data sources
*Alon Halevy, Data Integration: The Teenage Years, 2006 14
Structuring Web Content
 Web documents contain recognizable constants
that describe the content (e.g., travel info,
sports summaries, financial statements, etc)
 Web data is unstructured and cannot be
queried using traditional query languages.
 Conceptual-modeling approach used to extract
and structure data automatically.
 Techniques for querying the Web: (1) querying
the Web with Web query languages, (2)
generating wrappers for Web pages.
 Web querying : (1) virtual database technology,
(2) Web data modeling, (3) wrapper generation,
(4) natural-language processing, (5)
semistructured data, and (6) web queries.
*D.W. Embley, Conceptual-model-based data extraction from multiple-record Web pages, 1999
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Semantic Web (1)
 Middleware evolved to connect business softwares
 SOA standards created to standardized XML frameworks
 Middleware and SOA software depend on metadata
formats which are brittle and don’t respond well to
change
 Web 3.0 is about the emergence of a data Web.
 Data web consists of structured data records that are
published to the Web in reusable and remotely
queryable Semantic Web formats.
 Data Web enables data integration, portability, and
application interoperability: making data openly
accessible and linkable as Web pages, while the data is
stored and retrieved from different locations during a
single query.
*Jeffrey T. Pollock, Semantic Web For Dummies, 2009
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Semantic Web (2)
 Semantic Web built upon: (1) XML and (2) the RDF(Resource
Description Framework),
 XML allows users to add structure documents but says nothing
about what the structures mean.
 Meaning is expressed by RDF, which encodes it in sets of triples,
each triple being rather like the subject, verb and object of an
elementary sentence(written using XML tags).
 Subject and object are each identified by a Universal Resource
Identifier (URI), just as a link on a Web page
 System must have a way to discover common meanings for various
databases it encounters.
 Ontology is a document that formally defines the relations among
terms. The most typical kind of ontology for the Web has a (1)
taxonomy and a set of (2) inference rules.
 Taxonomy defines classes of objects and relations among them.
 Inference rules supply capability to deduce information,
manipulate the terms much more effectively in ways that are
useful and meaningful to the human user.
*Tim Berners-Lee, The Semantic Web, 2001
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Planned Next Step
 Confirming semantic web implementation
 Understanding semantic web components
(XML, RDF, OWL, etc)
 Learning research landscape in Semantic
web field
 Semantic web services?
 Research topic:
Aligning Semantic Web for governmental
use (Open Government Data)
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Q&A
Contact: [email protected]
THANK YOU
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