why the data train needs semantic rails -- the case of linked scientometrics (ape 2015)

AMisunderstanding Semantic Web Value Proposition Scientometrics Final Notes

Why the Data Train Needs Semantic Rails

The Case of Linked Scientometrics

Krzysztof JanowiczSTKO Lab, University of California, Santa Barbara, USA

APE 2015, Berlin, Germany

Why the Data Train Needs Semantic Rails K. Janowicz


HowWe Think About Data

Big Data As The New Natural Resource

http://www.ibmbigdatahub.com/infographic/big-data-new-natural-resource






A suitable analogy?Natural, i.e., not man-madeExhaustible, finite quantityRenewable, replenishableConsumed, alteredBuilding block






A suitable analogy?Natural, i.e., not man-madeExhaustible, finite quantityRenewable, replenishableConsumed, alteredBuilding block

If we don’t even understand what data are, how should we make sense out of them?




Intoday’s discussion about data analytics,we take data discovery, sensemaking,and interoperability as a given.



Retrieval

The Data Retrieval Problem Is Real

Even the major data hubs such as Data.gov still rely on keyword-based searchand have unreliable, incomplete, and missing metadata. For this type ofretrieval problems, even ’a little semantics goes a long way’ (Hendler 1997).



Sensemaking

Sensemaking is Difficult – Fitness for Puspose is Key

There is no shortage of data, butfinding data that is fit for a certainpurpose is difficult.Data as statements not as truth.Heterogeneity is caused by culturaldifferences, progress in science,viewpoints, granularity, ...semantics does not come for free.Lack of provenance informationSensemaking requires morepowerful semantic technologies andontologies (compared to IR).



Interoperability

Meaningful Analysis and Synthesis is Difficult

Ensuring that data is analyzed andcombined in a meaningful way is farfrom trivial.What if the information on how touse the data would come togetherwith these data?Focus on smart data instead of(merely on) smart applications.The purpose of ontologies is not toagree on the meaning of terms but tomake the data provider’s intendedmeaning explicit.



Semantics-Enabled Linked-Data-Driven Scientometrics

Howdoes this relate to scientometrics?




Value Proposition

Why do we use Semantic Web and Linked Data for Scientometrics

Federated queries over multiple data sourcesUnique global identifiers easy conflation and deduplicationTransparent data model; reduces the need for guessingNo data silos, no API restrictionsMany pre-defined lightweight vocabularies (ontologies)Smart data reduces the need for smart applicationsMachine reasoning support

So do we still need a deeper knowledge representation beyondsurface semantics?



Web@25

Web@25 Installation: Timeline

Keyword frequency for Semantic Web; WWW conference series (1994-2013)



Web@25

Web@25 Installation: Timeline

Keyword frequency for Linked Data; WWW conference series (1994-2013)



An Interesting Question


Given the keyword timeline, is the Semantic Web as a research fielddisappearing, diversifying, radiating, ...?




Letthe data speak for themselves



Web@25

Community detection

Colors: community membership, node size: frequency, line width: co-occurrence strength



Web@25

Web@25 Installation: Self-organizing Map

Landscape analogy: counties, mountains, and valleysWhy the Data Train Needs Semantic Rails K. Janowicz


Web@25

Web@25 Installation: Mapping

Location of top institutions that published on Semantic Web between 2009-2013.



Web@25


Similar pattern for Linked Data keyword between 2009-2013.



Web@25


Dissimilar pattern for Search Engine keyword between 2009-2013.



A Tale of Three Papers

Three Papers That Shaped the Semantic Web

Citations peaked 2009 for the Ontology and Semantic Web papers.More interestingly, why would you still cite these papers today?





Top keywords: {Ontology, SW},{Semantic Web, Ontology}, {Linked Data, Semantic Web, Ontology}





If a paper makes impact beyond its own home community, we should see anincrease in keyword variability (entropy).



And Now?

Sois the Semantic Webdisapearing, diversifying, radiating,...?



And Now?

Sois the Semantic Webdisapearing, diversifying, radiating,...?

No amount of data analytics is going to answer such questions beforewe precisely define and communicate what we mean by those terms.



The Semantic Cube

The Semantic Cube

Inductive and deductive techniques should be combined instead ofcompeting over the prerogative of interpretation



The Semantic Web Journal

The Semantic Web Journal

Open:Submitted manuscripts andreviews are publicly availableTransparent:Editor and reviewer names arepublished together with thepaper. Editorial decisions andpaper histories are availableVolunteered:Visitors can submit opencomments thereby contributing tothe review process


why the data train needs semantic rails -- the case of linked scientometrics (ape 2015)

Science

data train

databig data

smart data

data discovery

shortage of data

data analytics

butfinding data

major data hubs