Strata NY: Best Practices for Publishing Data

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Hjalmar Gislason

A presentation by Hjalmar Gislason, founder and CEO of DataMarket at the Strata Conference in New York, October 2012

Business

F I N D A N D U N D E R S TA N D D ATA

Best Practices for

Publishing Data

Hjalmar Gislason, founder & CEO - hg@datamarket.com October, 2012

Hjalmar
Gislason
Founder and CEO

Twitter: @datamarket
Slides: http://blog.datamarket.com/

Heavy
Data Consumers

Providers of

Data Delivery
Technology

Computers Humans

| B EST PR ACT ICE S fo r PUBL IS HI NG D ATA | Hjalmar Gislason, hg@datamarket.com | October 2012

Computers Humans

• Structure • Understand and
use

| B EST PR ACT ICE S fo r PUBL IS HI NG D ATA | Hjalmar Gislason, hg@datamarket.com | October 2012

Publishing for Computers

1. Simple formats
2. Indexes, unique IDs and meta-data
3. FAQs and feedback channels

Simple Formats

"Don't anthropomorphize computers
- they hate it."
- Unknown

Simple Formats:
Tim Berners-Lee’s Five Stars

| B EST PR ACT ICE S fo r PUBL IS HI NG D ATA | Hjalmar Gislason, hg@datamarket.com | October 2012

Simple Formats:
You lost me at “Semantics”

| B EST PR ACT ICE S fo r PUBL IS HI NG D ATA | Hjalmar Gislason, hg@datamarket.com | October 2012

Standards will emerge and there will
be more and more of them

• RDF
• OData vs. GData
• DSPL
• SDMX

| B EST PR ACT ICE S fo r PUBL IS HI NG D ATA | Hjalmar Gislason, hg@datamarket.com | October 2012

Indexes, unique ids and meta-data

| B EST PR ACT ICE S fo r PUBL IS HI NG D ATA | Hjalmar Gislason, hg@datamarket.com | October 2012

Indexes, unique IDs and meta-data

• Must: Unique ID, Title, Last updated
• Should: Meta-data

• Why?
• No need for scraping
• Less load on your end
• Ensures full coverage
• Ensures content removal and updates

| B EST PR ACT ICE S fo r PUBL IS HI NG D ATA | Hjalmar Gislason, hg@datamarket.com | October 2012

Indexes, unique IDs and meta-data

• Hard to emphasize enough!

• Unique IDs for everything: Datsets, columns, entities, ...

• Why?
• Continuity: A small change for a man = giant leap for a
computer

| B EST PR ACT ICE S fo r PUBL IS HI NG D ATA | Hjalmar Gislason, hg@datamarket.com | October 2012

Indexes, unique IDs and meta-data

• Any relevant contextual information
• URL(s), descriptions, methodology, next updated, authors,
keywords, units, license information, ...

| B EST PR ACT ICE S fo r PUBL IS HI NG D ATA | Hjalmar Gislason, hg@datamarket.com | October 2012

FAQs and feedback channels

#1 reason for not publishing data:

“There are errors in the data and I don't
want others to discover them”

| B EST PR ACT ICE S fo r PUBL IS HI NG D ATA | Hjalmar Gislason, hg@datamarket.com | October 2012

FAQs and feedback channels

#1 reason for not publishing data:

“There are errors in the data and I do
want others to discover them”

| B EST PR ACT ICE S fo r PUBL IS HI NG D ATA | Hjalmar Gislason, hg@datamarket.com | October 2012

FAQs and feedback channels

| B EST PR ACT ICE S fo r PUBL IS HI NG D ATA | Hjalmar Gislason, hg@datamarket.com | October 2012

Publishing for Humans

1. Search / Discovery
2. Visualization
3. Download

Search / Discovery

• Requirements differ from web/text search
• A lot less textual content to base on
• Synonyms, dictionaries, autocomplete
• But (hopefully) good meta-data = facets and ﬁltering

• Give people ways to browse
• Categories vs. tags vs. search
• Serendipity: Random, related, interesting...

Visualize

• What you should offer depends on the data

• Statistical data
• Focus on the most common charts and get them right
• Do NOT invent new visualizations or chart types

• Use standards compatible technologies
• No Flash!
• Charting and visualization libraries

Download

• Make it easy to use your data outside your tools
• Play nicely with those providing functionality beyond what
you can offer: Tableau, R, SAS, MathLab, Mathematica,
SPSS, ...

• Provide downloads in the formats most commonly used by your
users:
• Raw data: Excel, CSV, feeds (R, Excel live feeds, APIs)
• Charts and visualizations: Bitmap, vector, PPT, embeds?

Computers Humans

• Structure • Understand and use
• Simple formats • Search / Discovery
• Indexes, unique IDs and • Visualization
meta-data • Download
• FAQs and feedback
channels

| B EST PR ACT ICE S fo r PUBL IS HI NG D ATA | Hjalmar Gislason, hg@datamarket.com | October 2012

F I N D A N D U N D E R S TA N D D ATA

Hjalmar Gislason, founder & CEO

Twitter: @datamarket · Facebook: DataMarket · E-mail: hg@datamarket.com

Presented in March 2012 at the OECD Statistical Information System Collaboration Community (SIS-CC) Workshop in Paris. Video available at http://youtu.be/ZldhNV3Qt6c The digitization of information exchange processes has led in many industries to define standards to be used in the B2B side of the value chain for the conversations between key partners. The agencies involved in statistical production are not an exception and need to agree on standards that can be used in the exchange of data and metadata between them. However, before these standards have been fully adopted, new needs have arisen that have stressed the importance of machine readable formats for the reuse of the public sector information. Open data initiatives have usually found a strategic ally in the statistical offices because timeliness, punctuality and accessibility are part of the code of practice in official statistics. This has increased the necessity of standards not only for data exchange between organizations specializing in statistical production but also for dissemination to third parties. The presentation will try to address the requirements that the dissemination standards should meet in this new context.

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Strata NY: Best Practices for Publishing Data

1. F I N D A N D U N D E R S TA N D D ATA Best Practices for Publishing Data Hjalmar Gislason, founder & CEO - hg@datamarket.com October, 2012

2. Hjalmar Gislason Founder and CEO Twitter: @datamarket Slides: http://blog.datamarket.com/

5. Heavy Data Consumers Providers of Data Delivery Technology

6. Computers Humans | B EST PR ACT ICE S fo r PUBL IS HI NG D ATA | Hjalmar Gislason, hg@datamarket.com | October 2012

7. Computers Humans • Structure • Understand and use | B EST PR ACT ICE S fo r PUBL IS HI NG D ATA | Hjalmar Gislason, hg@datamarket.com | October 2012

8. Computers Humans • Structure • Understand and use | B EST PR ACT ICE S fo r PUBL IS HI NG D ATA | Hjalmar Gislason, hg@datamarket.com | October 2012

9. Publishing for Computers 1. Simple formats 2. Indexes, unique IDs and meta-data 3. FAQs and feedback channels

10. Simple Formats "Don't anthropomorphize computers - they hate it." - Unknown

11. Simple Formats

12. Simple Formats: Tim Berners-Lee’s Five Stars | B EST PR ACT ICE S fo r PUBL IS HI NG D ATA | Hjalmar Gislason, hg@datamarket.com | October 2012

13. Simple Formats: You lost me at “Semantics” | B EST PR ACT ICE S fo r PUBL IS HI NG D ATA | Hjalmar Gislason, hg@datamarket.com | October 2012

14. Standards will emerge and there will be more and more of them • RDF • OData vs. GData • DSPL • SDMX | B EST PR ACT ICE S fo r PUBL IS HI NG D ATA | Hjalmar Gislason, hg@datamarket.com | October 2012

15. Indexes, unique ids and meta-data | B EST PR ACT ICE S fo r PUBL IS HI NG D ATA | Hjalmar Gislason, hg@datamarket.com | October 2012

16. Indexes, unique ids and meta-data | B EST PR ACT ICE S fo r PUBL IS HI NG D ATA | Hjalmar Gislason, hg@datamarket.com | October 2012

17. Indexes, unique ids and meta-data | B EST PR ACT ICE S fo r PUBL IS HI NG D ATA | Hjalmar Gislason, hg@datamarket.com | October 2012

18. Indexes, unique IDs and meta-data • Must: Unique ID, Title, Last updated • Should: Meta-data • Why? • No need for scraping • Less load on your end • Ensures full coverage • Ensures content removal and updates | B EST PR ACT ICE S fo r PUBL IS HI NG D ATA | Hjalmar Gislason, hg@datamarket.com | October 2012

19. Indexes, unique IDs and meta-data • Hard to emphasize enough! • Unique IDs for everything: Datsets, columns, entities, ... • Why? • Continuity: A small change for a man = giant leap for a computer | B EST PR ACT ICE S fo r PUBL IS HI NG D ATA | Hjalmar Gislason, hg@datamarket.com | October 2012

20. Indexes, unique IDs and meta-data • Any relevant contextual information • URL(s), descriptions, methodology, next updated, authors, keywords, units, license information, ... | B EST PR ACT ICE S fo r PUBL IS HI NG D ATA | Hjalmar Gislason, hg@datamarket.com | October 2012

21. FAQs and feedback channels #1 reason for not publishing data: “There are errors in the data and I don't want others to discover them” | B EST PR ACT ICE S fo r PUBL IS HI NG D ATA | Hjalmar Gislason, hg@datamarket.com | October 2012

22. FAQs and feedback channels #1 reason for not publishing data: “There are errors in the data and I do want others to discover them” | B EST PR ACT ICE S fo r PUBL IS HI NG D ATA | Hjalmar Gislason, hg@datamarket.com | October 2012

23. FAQs and feedback channels | B EST PR ACT ICE S fo r PUBL IS HI NG D ATA | Hjalmar Gislason, hg@datamarket.com | October 2012

24. FAQs and feedback channels | B EST PR ACT ICE S fo r PUBL IS HI NG D ATA | Hjalmar Gislason, hg@datamarket.com | October 2012

25. Publishing for Computers 1. Simple formats 2. Indexes, unique IDs and meta-data 3. FAQs and feedback channels

26. Computers Humans • Structure • Understand and use | B EST PR ACT ICE S fo r PUBL IS HI NG D ATA | Hjalmar Gislason, hg@datamarket.com | October 2012

27. Publishing for Humans 1. Search / Discovery 2. Visualization 3. Download

28. Search / Discovery • Requirements differ from web/text search • A lot less textual content to base on • Synonyms, dictionaries, autocomplete • But (hopefully) good meta-data = facets and ﬁltering • Give people ways to browse • Categories vs. tags vs. search • Serendipity: Random, related, interesting...

29. Search / Discovery

30. Visualize

31.

32. 109 columns x 340 lines = 37.060 cells

33.

34.

35.

36. Visualize • What you should offer depends on the data • Statistical data • Focus on the most common charts and get them right • Do NOT invent new visualizations or chart types • Use standards compatible technologies • No Flash! • Charting and visualization libraries

37. Visualize

38. Visualize

39. Download • Make it easy to use your data outside your tools • Play nicely with those providing functionality beyond what you can offer: Tableau, R, SAS, MathLab, Mathematica, SPSS, ... • Provide downloads in the formats most commonly used by your users: • Raw data: Excel, CSV, feeds (R, Excel live feeds, APIs) • Charts and visualizations: Bitmap, vector, PPT, embeds?

40. Computers Humans • Structure • Understand and use • Simple formats • Search / Discovery • Indexes, unique IDs and • Visualization meta-data • Download • FAQs and feedback channels | B EST PR ACT ICE S fo r PUBL IS HI NG D ATA | Hjalmar Gislason, hg@datamarket.com | October 2012

41. F I N D A N D U N D E R S TA N D D ATA Hjalmar Gislason, founder & CEO Twitter: @datamarket · Facebook: DataMarket · E-mail: hg@datamarket.com

Strata NY: Best Practices for Publishing Data

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