Open Government Data in Indonesia Regional GovernmentManaging Government Data Frameworks

Suhardi Cyber Security Center

School of Electrical EngineeringInstitute of Technology Bandung

Email: suhardi@stei.itb.ac.id

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“Open Government” Acts in Indonesia National Constitution (article 28F)

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

Act 14/2008 on Public Information Transparency

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

“...(Public institution) must develop information and documentation system to manage public information efficiently... (article 13).

“...must assign Information and Documentation Management Officer (article 13)

Closed Open

Permitted Restricted

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Open Government*

Government should be transparent. Transparency promotes accountability and provides information for citizens about what their Government is doing.

Government should be participatory. Public engagement enhances the Government’s effectiveness and improves the quality of its decisions.

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

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

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 rule-based processing)

2.Information ExtractionExtract 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

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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)

THANK YOU

Q & AContact: suhardi@stei.itb.ac.id

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