Unleash Your Research:

The Wolfram Data Repository

Matthew Day

matthewday@wolfram.com
Manager, Data Initiative

Realizing potential

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Building the flock

Of interest to others

Novel

Non-trivial (resulting from hard work)

Well structured (for re-use)

Well described (methods and context)

Sharing benefits the sharers

Credit

Citation

Sustained growth

Data is persistent, i.e preserved

There aren’t many good business models for data

Charge users — Open Data free of use restrictions and costs

Paid-for data hosting — knowledge lacks persistence

Public funding — local burden, not dependable, not extensible

⇒  Open Access journal model is an intriguing alternative

The academic record — journals

Medicine		  Science		    Social Science

2,048,728 articles published in 2011 (Thomson Reuters Web Of Science)

The academic record — data

Academic data repositories

Almost exclusively publicly funded, and locally so

High functionality for narrow data types

Low (often no) functionality for broad data types

Poor mechanisms to give credit or track impact of datasets

Poor systems for data discovery (cf. journal content indexes)

⇒  The ecosystem of academic data is far from mature

Key features of academic data publishing

Pressure from funders and society-at-large

Long-term preservation of the academic record:

Academics retire, websites disappear, funding dries up

File formats change, bits rot

Human readable vs machine readable

Academics need incentives (career-building credit)

Why should Wolfram Research get involved?

Wolfram Research can deal with large amounts of data

Make data computable and useful

Mediate long-term data preservation

Give data creators credit

The concept

Cross disciplinary

Open Access

Journal associated, or expert reviewed

Citable (DOIs and impact metrics)

Easy data exploration tools

A corpus for knowledge discovery

Long-term preservation in partnership with third parties

The repository homepage

A dataset

Exploring the repository

Exploring a dataset

Views of data contents

Analyzing data

The long-term vision

Doing more with more data

Supporting the data-associated needs of academics and others

Supporting other organizations in their own data publishing activities (e.g. journal publishers)